17.1.3.5 Walking, Gait Recognition, Gait Analysis

Chapter Contents (Back)
Walking. Gait Analysis. Gait Recognition.
See also Walking, Gait Recognition, Neural Networks, CNN, Learning.
See also Gait Analysis, Depth, 3-D Data, LiDAR, Radar, 3-D from Gait.
See also Gender Analysis using Gait.
See also Legged Locomotion Robots, Assistants.

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Converging Approaches to Extracting Structure from Motion: Psychophysical and Computational Investigations of Recovering Connectivity from Moving Point-Light Displays,
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Dockstader, S.L., Berg, M.J., Tekalp, A.M.,
Stochastic kinematic modeling and feature extraction for gait analysis,
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See also On the Tracking of Articulated and Occluded Video Object Motion. BibRef

Dockstader, S.L., Imennov, N.S., Berg, M.J., Tekalp, A.M.,
Fault-tolerant tracking for gait analysis,
ICIP03(II: 89-92).
IEEE DOI 0312
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Dockstader, S.L.[Shiloh L.], Imennov, N.S.,
Prediction for Human Motion Tracking Failures,
IP(15), No. 2, February 2006, pp. 411-421.
IEEE DOI 0602
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Dockstader, S.L., Imennov, N.S., Tekalp, A.M.,
Markov-based failure prediction for human motion analysis,
ICCV03(1283-1288).
IEEE DOI 0311
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Dockstader, S.I., Bergkessel, K.A., Tekalp, A.M.,
Feature extraction for the analysis of gait and human motion,
ICPR02(I: 5-8).
IEEE DOI 0211
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Robledo Vega, I.[Isidro], Sarkar, S.[Sudeep],
Statistical motion model based on the change of feature relationships: Human gait-based recognition,
PAMI(25), No. 10, October 2003, pp. 1323-1328.
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Earlier:
Experiments on gait analysis by exploiting nonstationarity in the distribution of feature relationships,
ICPR02(I: 1-4).
IEEE DOI 0211
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Earlier: A2, A1:
Discrimination of Motion Based on Traces in the Space of Probability Functions over Feature Relations,
CVPR01(I:976-983).
IEEE DOI 0110
Walking motion recognition from change in relational statistics of features. BibRef

Moustakas, K.[Konstantinos], Tzovaras, D.[Dimitrios], Stavropoulos, G.,
Gait Recognition Using Geometric Features and Soft Biometrics,
SPLetters(17), No. 4, April 2010, pp. 367-370.
IEEE DOI 1003
BibRef

Argyropoulos, S., Tzovaras, D., Ioannidis, D., Strintzis, M.G.,
Gait authentication using distributed source coding,
ICIP08(3108-3111).
IEEE DOI 0810
BibRef

Gonzàlez, J.[Jordi], Varona, J.[Javier], Roca, F.X.[F. Xavier], Villanueva, J.J.[Juan J.],
A Comparison Framework for Walking Performances using aSpaces,
ELCVIA(5), No. 3, 2005, pp. 105-116.
DOI Link 0506
BibRef
Earlier:
Analysis of Human Walking Based on aSpaces,
AMDO04(177-188).
Springer DOI 0505
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Earlier: A2, A1, A3, A4:
iTrack: Image-based Probabilistic Tracking of People,
ICPR00(Vol III: 1110-1113).
IEEE DOI 0009
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Fernandez, C.[Carles], Baiget, P.[Pau], Roca, F.X.[F. Xavier], Gonzàlez, J.[Jordi],
Augmenting video surveillance footage with virtual agents for incremental event evaluation,
PRL(32), No. 6, 15 April 2011, pp. 878-889.
Elsevier DOI 1103
BibRef
Earlier: A2, A3, A4, Only:
Autonomous Virtual Agents for Performance Evaluation of Tracking Algorithms,
AMDO08(xx-yy).
Springer DOI 0807
Human behavior analysis; Smart video surveillance; Benchmarking; Ontologies BibRef

Mazzaro, M.C.[Maria Cecilla], Sznaier, M.[Mario], Camps, O.I.[Octavia I.],
A Model (In)Validation Approach to Gait Classification,
PAMI(27), No. 11, November 2005, pp. 1820-1825.
IEEE DOI 0510
Nominal model with noise and uncertainity. BibRef

Mazzaro, M.C., Sznaier, M., Camps, O.I., Soatto, S., Bissacco, A.,
A model (In)validation approach to gait recognition,
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Xu, D., Yan, S., Tao, D., Zhang, L., Li, X., Zhang, H.J.,
Human Gait Recognition With Matrix Representation,
CirSysVideo(16), No. 7, July 2006, pp. 896-903.
IEEE DOI 0608
BibRef

Xu, D., Yan, S.C.[Shui-Cheng], Tao, D.C.[Da-Cheng], Lin, S., Zhang, H.J.,
Marginal Fisher Analysis and Its Variants for Human Gait Recognition and Content-Based Image Retrieval,
IP(16), No. 11, November 2007, pp. 2811-2821.
IEEE DOI 0709

See also Face Recognition: A Generalized Marginal Fisher Analysis Approach. BibRef

Boulgouris, N.V.[Nikolaos V.], Plataniotis, K.N.[Konstantinos N.], Hatzinakos, D.[Dimitrios],
Gait recognition using linear time normalization,
PR(39), No. 5, May 2006, pp. 969-979.
Elsevier DOI 0604
BibRef
Earlier:
An angular transform of gait sequences for gait assisted recognition,
ICIP04(II: 857-860).
IEEE DOI 0505
Angular analysis; Time normalization; Recognition; Verification BibRef

Lu, H.P.[Hai-Ping], Plataniotis, K.N., Venetsanopoulos, A.N.,
Boosting Discriminant Learners for Gait Recognition Using MPCA Features,
JIVP(2009), No. 2009, pp. xx-yy.
DOI Link 0911
BibRef
Earlier:
A Layered Deformable Model for Gait Analysis,
FGR06(249-256).
IEEE DOI 0604
BibRef
And:
Multilinear Principal Component Analysis of Tensor Objects for Recognition,
ICPR06(II: 776-779).
IEEE DOI 0609
BibRef

Boulgouris, N.V.[Nikolaos V.], Chi, Z.X.,
Gait Recognition Using Radon Transform and Linear Discriminant Analysis,
IP(16), No. 3, March 2007, pp. 731-740.
IEEE DOI 0703
BibRef
Earlier:
Gait Representation and Recognition Based on Radon Transform,
ICIP06(2665-2668).
IEEE DOI 0610
BibRef

Boulgouris, N.V.[Nikolaos V.], Chi, Z.W.X.[Zhi-Wei X.],
Human gait recognition based on matching of body components,
PR(40), No. 6, June 2007, pp. 1763-1770.
Elsevier DOI 0704
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And:
Gait Recognition Based on Human Body Components,
ICIP07(I: 353-356).
IEEE DOI 0709
Human gait; Recognition; Verification BibRef

Huang, X.X.[Xia-Xi], Boulgouris, N.V.[Nikolaos V.],
Gait Recognition With Shifted Energy Image and Structural Feature Extraction,
IP(21), No. 4, April 2012, pp. 2256-2268.
IEEE DOI 1204
BibRef
Earlier:
Gait recognition using Linear Discriminant Analysis with artificial walking conditions,
ICIP10(2461-2464).
IEEE DOI 1009
BibRef

Boulgouris, N.V., Huang, X.X.,
Gait Recognition Using HMMs and Dual Discriminative Observations for Sub-Dynamics Analysis,
IP(22), No. 9, 2013, pp. 3636-3647.
IEEE DOI 1309
Gait; biometrics; recognition; surveillance BibRef

Bissacco, A.[Alessandro], Chiuso, A.[Alessandro], Soatto, S.[Stefano],
Classification and Recognition of Dynamical Models: The Role of Phase, Independent Components, Kernels and Optimal Transport,
PAMI(29), No. 11, November 2007, pp. 1958-1972.
IEEE DOI 0711
Extend classification to handle periodic modes. BibRef

Bissacco, A.[Alessandro], Soatto, S.[Stefano],
Hybrid Dynamical Models of Human Motion for the Recognition of Human Gaits,
IJCV(85), No. 1, October 2009, pp. xx-yy.
Springer DOI 0907
BibRef
Earlier:
On the Blind Classification of Time Series,
CVPR07(1-7).
IEEE DOI 0706
BibRef
Earlier:
Classifying Human Dynamics Without Contact Forces,
CVPR06(II: 1678-1685).
IEEE DOI 0606
Blind: input is not really known. Classify gait. BibRef

Bissacco, A., Chiuso, A., Ma, Y., Soatto, S.,
Recognition of Human Gaits,
CVPR01(II:52-57).
IEEE DOI
PS File. 0110
BibRef

Bissacco, A.[Alessandro],
Modeling and Learning Contact Dynamics in Human Motion,
CVPR05(I: 421-428).
IEEE DOI 0507
BibRef

Bissacco, A.[Alessandro], Yang, M.H.[Ming-Hsuan], Soatto, S.[Stefano],
Fast Human Pose Estimation using Appearance and Motion via Multi-Dimensional Boosting Regression,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Chan, K.L.,
Video-based Gait Analysis By Silhouette Chamfer Distance And Kalman Filter,
IJIG(8), No. 3, July 2008, pp. 383-418. 0807

See also Detection of swimmer using dense optical flow motion map and intensity information. BibRef

Chen, C., Liang, J., Zhao, H., Hu, H., Tian, J.,
Factorial HMM and Parallel HMM for Gait Recognition,
SMC-C(38), No. 1, January 2008, pp. 114-123.
IEEE DOI 0901
BibRef

Barnich, O.[Olivier], van Droogenbroeck, M.[Marc],
Frontal-view gait recognition by intra- and inter-frame rectangle size distribution,
PRL(30), No. 10, 15 July 2009, pp. 893-901.
Elsevier DOI 0906
Gait recognition; Mathematical morphology; Histogram; Motion detection; Shape analysis BibRef

Chen, C.H.[Chang-Hong], Liang, J.M.[Ji-Min], Zhao, H.[Heng], Hu, H.H.[Hai-Hong], Tian, J.[Jie],
Frame difference energy image for gait recognition with incomplete silhouettes,
PRL(30), No. 11, 1 August 2009, pp. 977-984,.
Elsevier DOI 0909
Gait recognition; Incomplete silhouettes; Frame difference energy image; Hidden Markov model BibRef

Chen, C.H.[Chang-Hong], Liang, J.M.[Ji-Min], Hu, H.H.[Hai-Hong], Jiao, L.C.[Li-Cheng], Yang, X.[Xin],
Factorial Hidden Markov Models for Gait Recognition,
ICB07(124-133).
Springer DOI 0708
BibRef

Chen, C.H.[Chang-Hong], Liang, J.M.[Ji-Min], Zhu, X.C.[Xiu-Chang],
Gait recognition based on improved dynamic Bayesian networks,
PR(44), No. 4, April 2011, pp. 988-995.
Elsevier DOI 1101
BibRef
Earlier:
Logistic dynamic texture model for human activity and gait recognition,
ICIP10(2473-2476).
IEEE DOI 1009
Gait recognition; Improved dynamic Bayesian networks; Layered time series model; Logistic dynamic texture model; Hidden Markov model BibRef

Makihara, Y.S.[Yasu-Shi], Sagawa, R.[Ryusuke], Mukaigawa, Y.[Yasuhiro], Echigo, T.[Tomio], Yagi, Y.S.[Yasu-Shi],
Gait Identification Considering Body Tilt by Walking Direction Changes,
ELCVIA(8), No. 1, July 2009, pp. xx-yy.
DOI Link 0909
BibRef
Earlier:
Adaptation to Walking Direction Changes for Gait Identification,
ICPR06(II: 96-99).
IEEE DOI 0609
BibRef
Earlier:
Which Reference View is Effective for Gait Identification Using a View Transformation Model?,
Biometrics06(45).
IEEE DOI 0609
BibRef
And:
Gait Recognition Using a View Transformation Model in the Frequency Domain,
ECCV06(III: 151-163).
Springer DOI 0608
BibRef

Echigo, T.[Tomio], Maeda, J.J.[Jun-Ji], Nakano, H.[Hiroki],
Method for classifying an object in a moving picture,
US_Patent6,606,412, Aug 12, 2003
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Hossain, M.A.[M. Altab], Makihara, Y.S.[Yasu-Shi], Wang, J.Q.[Jun-Qiu], Yagi, Y.S.[Yasu-Shi],
Clothing-invariant gait identification using part-based clothing categorization and adaptive weight control,
PR(43), No. 6, June 2010, pp. 2281-2291.
Elsevier DOI 1003
BibRef
Earlier:
Clothes-invariant gait identification using part-based adaptive weight control,
ICPR08(1-4).
IEEE DOI 0812
Gait identification; Clothing-invariant; Part-based; Adaptive weight control; Biometrics BibRef

Wang, J.Q.[Jun-Qiu], Yagi, Y.S.[Yasu-Shi], Makihara, Y.S.[Yasu-Shi],
People Tracking and Segmentation Using Efficient Shape Sequences Matching,
ACCV09(II: 204-213).
Springer DOI 0909
BibRef
Earlier: A1, A3, A2:
People tracking and segmentation using spatiotemporal shape constraints,
VNBA08(31-38).
DOI Link 1208
Tracking and segmentation algorithm for gait recognition. BibRef

Tsuji, A.[Akira], Makihara, Y.S.[Yasu-Shi], Yagi, Y.S.[Yasu-Shi],
Silhouette transformation based on walking speed for gait identification,
CVPR10(717-722).
IEEE DOI 1006
BibRef

Li, X.[Xiang], Makihara, Y.S.[Yasu-Shi], Xu, C.[Chi], Yagi, Y.S.[Yasu-Shi],
End-to-end Model-based Gait Recognition using Synchronized Multi-view Pose Constraint,
HTCV21(4089-4098)
IEEE DOI 2112
Training, Legged locomotion, Shape, Fitting, Synchronization, n/a BibRef

Sugiura, K.[Kazushige], Makihara, Y.S.[Yasu-Shi], Yagi, Y.S.[Yasu-Shi],
Omnidirectional Gait Identification by Tilt Normalization and Azimuth View Transformation,
OMNIVIS08(xx-yy). 0810
BibRef
And:
Gait Identification Based on Multi-view Observations Using Omnidirectional Camera,
ACCV07(I: 452-461).
Springer DOI 0711
BibRef

Fihl, P.[Preben], Moeslund, T.B.[Thomas B.],
Invariant gait continuum based on the duty-factor,
SIViP(3), No. 4, December 2009, pp. xx-yy.
Springer DOI 0911
BibRef
Earlier:
Invariant Classification of Gait Types,
CRV08(179-185).
IEEE DOI 0805
BibRef
Earlier:
Classification of gait types based on the duty-factor,
AVSBS07(318-323).
IEEE DOI 0709
BibRef

Kim, D.H.[Dae-Hee], Paik, J.K.[Joon-Ki],
Gait recognition using active shape model and motion prediction,
IET-CV(4), No. 1, March 2010, pp. 25-36.
DOI Link 1001
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Cho, W.[Woon], Kim, T.K.[Tae-Kyung], Paik, J.K.[Joon-Ki],
Gait Recognition Using Active Shape Models,
ACIVS07(384-394).
Springer DOI 0708
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Kim, D.H.[Dong-Hyeon], Kim, D.H.[Dae-Hee], Paik, J.K.[Joon-Ki],
Model-Based Gait Recognition Using Multiple Feature Detection,
ACIVS08(xx-yy).
Springer DOI 0810
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Maik, V., Paik, D.T., Lim, J., Park, K., Paik, J.,
Hierarchical pose classification based on human physiology for behaviour analysis,
IET-CV(4), No. 1, March 2010, pp. 12-24.
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Ekinci, M.[Murat], Aykut, M.[Murat],
Improved gait recognition by multiple-projections normalization,
MVA(21), No. 2, February 2010, pp. xx-yy.
Springer DOI 1002
BibRef
Earlier: A1 Only:
Gait Recognition Using Multiple Projections,
FGR06(517-522).
IEEE DOI 0604
Silhouette represented by 4 1-D features - difference between bounding box and silhouette. BibRef

Ekinci, M.[Murat], Gedikli, E.[Eyup],
A Novel Approach on Silhouette Based Human Motion Analysis for Gait Recognition,
ISVC05(219-226).
Springer DOI 0512
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Trivino, G.[Gracian], Alvarez-Alvarez, A.[Alberto], Bailador, G.[Gonzalo],
Application of the computational theory of perceptions to human gait pattern recognition,
PR(43), No. 7, July 2010, pp. 2572-2581.
Elsevier DOI 1003
Gait recognition; Fuzzy logic; Fuzzy finite state machine; Computational theory of perceptions; Authentication BibRef

Xue, Z.J.[Zhao-Jun], Ming, D.[Dong], Song, W.[Wei], Wan, B.K.[Bai-Kun], Jin, S.J.[Shi-Jiu],
Infrared gait recognition based on wavelet transform and support vector machine,
PR(43), No. 8, August 2010, pp. 2904-2910.
Elsevier DOI 1006
Gait recognition; Infrared thermal imaging; Wavelet transform; Support vector machine; Feature extraction BibRef

Bashir, K.[Khalid], Xiang, T.[Tao], Gong, S.G.[Shao-Gang],
Gait recognition without subject cooperation,
PRL(31), No. 13, 1 October 2010, pp. 2052-2060.
Elsevier DOI 1003
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And:
Cross-view Gait Recognition Using Correlation Strength,
BMVC10(xx-yy).
HTML Version. 1009
BibRef
Earlier:
Gait Representation Using Flow Fields,
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PDF File. 0909
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Earlier:
Feature Selection for Gait Recognition without Subject Cooperation,
BMVC08(xx-yy).
PDF File. 0809
Biometrics; Gait recognition; Gait Energy Image; Feature selection; Adaptive Component and Discriminant Analysis BibRef

Nizami, I.F.[Imran Fareed], Hong, S.J.[Sung-Jun], Lee, H.S.[Hee-Sung], Lee, B.Y.[Byung-Yun], Kim, E.T.[Eun-Tai],
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Nassar, H.[Hamed], El-Taweel, G.[Ghada], Mahmoud, E.[Eman],
A Novel Feature Extraction Scheme For Human Gait Recognition,
IJIG(10), No. 4, October 2010, pp. 575-587.
DOI Link 1101
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Xu, D., Huang, Y., Zeng, Z., Xu, X.,
Human Gait Recognition Using Patch Distribution Feature and Locality-Constrained Group Sparse Representation,
IP(21), No. 1, January 2012, pp. 316-326.
IEEE DOI 1112
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Zheng, S.[Shuai], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu], Tao, D.C.[Da-Cheng],
A cascade fusion scheme for gait and cumulative foot pressure image recognition,
PR(45), No. 10, October 2012, pp. 3603-3610.
Elsevier DOI 1206
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Evaluation framework on translation-invariant representation for cumulative foot pressure image,
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Gait; Foot pressure image; Human recognition BibRef

Ryu, J.[Jegoon], Kamata, S.I.[Sei-Ichiro], Ahrary, A.[Alireza],
SSM-HPC: Front View Gait Recognition Using Spherical Space Model with Human Point Clouds,
IEICE(E95-D), No. 7, July 2012, pp. 1969-1978.
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Ryu, J.[Jegoon], Kamata, S.I.[Sei-Ichiro],
Front view gait recognition using Spherical Space Model with Human Point Clouds,
ICIP11(3209-3212).
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Vahidpour, M., Sarabandi, K.,
Millimeter-Wave Doppler Spectrum and Polarimetric Response of Walking Bodies,
GeoRS(50), No. 7, July 2012, pp. 2866-2879.
IEEE DOI 1208
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Vondrak, M.[Marek], Sigal, L.[Leonid], Jenkins, O.C.[Odest Chadwicke],
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IEEE DOI 1212
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Earlier:
Physical simulation for probabilistic motion tracking,
CVPR08(1-8).
IEEE DOI 0806
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Lee, C.P.[Chin Poo], Tan, A.W.C.[Alan W.C.], Tan, S.C.A.[Shing Chi-Ang],
Gait recognition via optimally interpolated deformable contours,
PRL(34), No. 6, 15 April 2013, pp. 663-669.
Elsevier DOI 1303
Gait recognition; Fourier descriptor; Shape interpolation BibRef

Lee, C.P.[Chin Poo], Tan, A.W.C.[Alan W.C.], Tan, S.C.A.[Shing Chi-Ang],
Gait recognition with Transient Binary Patterns,
JVCIR(33), No. 1, 2015, pp. 69-77.
Elsevier DOI 1512
Gait recognition BibRef

Lee, C.P.[Chin Poo], Tan, A.W.C.[Alan W.C.], Tan, S.C.A.[Shing Chi-Ang],
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Elsevier DOI 1406
Gait BibRef

Dupuis, Y., Savatier, X., Vasseur, P.,
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IVC(31), No. 8, August 2013, pp. 580-591.
Elsevier DOI 1306
Feature selection; Gait recognition; Model-free; Panoramic; Random forest BibRef

Maki, A.[Atsuto], Perbet, F.[Frank], Stenger, B.[Björn], Cipolla, R.[Roberto],
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Elsevier DOI 1309
Motion BibRef

He, R.[Ran], Zheng, W.S.[Wei-Shi], Tan, T.N.[Tie-Niu], Sun, Z.A.[Zhen-An],
Half-Quadratic-Based Iterative Minimization for Robust Sparse Representation,
PAMI(36), No. 2, February 2014, pp. 261-275.
IEEE DOI 1402
computer vision BibRef

He, R.[Ran], Zhang, Y.Y.[Ying-Ya], Sun, Z.A.[Zhen-An], Yin, Q.Y.[Qi-Yue],
Robust Subspace Clustering With Complex Noise,
IP(24), No. 11, November 2015, pp. 4001-4013.
IEEE DOI 1509
computer vision BibRef

Zhang, Y.Y.[Ying-Ya], Sun, Z.A.[Zhen-An], He, R.[Ran], Tan, T.N.[Tie-Niu],
Robust Subspace Clustering via Half-Quadratic Minimization,
ICCV13(3096-3103)
IEEE DOI 1403
BibRef
And:
Robust Low-Rank Representation via Correntropy,
ACPR13(461-465)
IEEE DOI 1408
iterative methods BibRef

Zheng, S.[Shuai], Zhang, J.G.[Jun-Ge], Huang, K.Q.[Kai-Qi], He, R.[Ran], Tan, T.N.[Tie-Niu],
Robust View Transformation Model for Gait Recognition,
ICIP11(2073-2076).
IEEE DOI 1201
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Steinicke, F., Visell, Y., Campos, J., Lécuyer, A., (Eds.)


Human Walking in Virtual Environments: Perception, Technology, and Applications,
Springer2013. ISBN 978-1-4419-8431-9.
WWW Link. 1404
A survey of past and recent developments on human walking in virtual environments with an emphasis on human self-motion perception, the multisensory nature of experiences of walking, conceptual design approaches, current technologies, and applications. BibRef

Guan, Y.[Yu], Sun, Y.L.[Yun-Lian], Li, C.T.[Chang-Tsun], Tistarelli, M.,
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IET-Bio(3), No. 2, June 2014, pp. 84-93.
DOI Link 1407
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Iwashita, Y.[Yumi], Ogawara, K.[Koichi], Kurazume, R.[Ryo],
Identification of people walking along curved trajectories,
PRL(48), No. 1, 2014, pp. 60-69.
Elsevier DOI 1410
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Earlier: A1, A3, A2:
Expanding gait identification methods from straight to curved trajectories,
WACV13(193-199).
IEEE DOI 1303
Gait BibRef

Lai, Z.H.[Zhi-Hui], Xu, Y.[Yong], Jin, Z.[Zhong], Zhang, D.,
Human Gait Recognition via Sparse Discriminant Projection Learning,
CirSysVideo(24), No. 10, October 2014, pp. 1651-1662.
IEEE DOI 1411
feature extraction BibRef

Ngo, T.T.[Trung Thanh], Makihara, Y.S.[Yasu-Shi], Nagahara, H.[Hajime], Mukaigawa, Y.[Yasuhiro], Yagi, Y.S.[Yasu-Shi],
Similar gait action recognition using an inertial sensor,
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On covariate factor detection and removal for robust gait recognition,
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IEEE DOI 1506
Analytical models BibRef

Muramatsu, D., Makihara, Y., Yagi, Y.,
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View Transformation Model Incorporating Quality Measures for Cross-View Gait Recognition,
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IEEE DOI 1606
Accuracy BibRef

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Frontal gait recognition from occluded scenes,
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Accelerometer-Based Gait Recognition by Sparse Representation of Signature Points With Clusters,
Cyber(45), No. 9, September 2015, pp. 1864-1875.
IEEE DOI 1509
accelerometers BibRef

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On how to improve tracklet-based gait recognition systems,
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Castro, F.M.[Francisco M.], Delgado-Escaño, R.[Rubén], Hernández-García, R.[Ruber], Marín-Jiménez, M.J.[Manuel J.], Guil, N.[Nicolás],
AttenGait: Gait recognition with attention and rich modalities,
PR(148), 2024, pp. 110171.
Elsevier DOI Code:
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Gait, Optical flow, Deep learning, Attention, Biometrics BibRef

Xing, X.L.[Xiang-Lei], Wang, K.[Kejun], Yan, T.[Tao], Lv, Z.W.[Zhuo-Wen],
Complete canonical correlation analysis with application to multi-view gait recognition,
PR(50), No. 1, 2016, pp. 107-117.
Elsevier DOI 1512
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Rida, I., Jiang, X., Marcialis, G.L.,
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SPLetters(23), No. 1, January 2016, pp. 154-158.
IEEE DOI 1601
Clothing BibRef

Guan, S., Gray, H.A., Keynejad, F., Pandy, M.G.,
Mobile Biplane X-Ray Imaging System for Measuring 3D Dynamic Joint Motion During Overground Gait,
MedImg(35), No. 1, January 2016, pp. 326-336.
IEEE DOI 1601
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Shi, J.L.[Jin-Long], Sun, Z.X.[Zheng-Xing],
Large-scale three-dimensional measurement based on LED marker tracking,
VC(32), No. 2, February 2016, pp. 179-190.
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Nangtin, P.[Prasit], Kumhom, P.[Pinit], Chamnongthai, K.[Kosin],
Gait identification with partial occlusion using six modules and consideration of occluded module exclusion,
JVCIR(36), No. 1, 2016, pp. 107-121.
Elsevier DOI 1603
Gait identification BibRef

Sung, Y., Chung, W.,
Hierarchical Sample-Based Joint Probabilistic Data Association Filter for Following Human Legs Using a Mobile Robot in a Cluttered Environment,
HMS(46), No. 3, June 2016, pp. 340-349.
IEEE DOI 1605
Estimation BibRef

Lao, S.H.[Shi-Hong], Wang, D.[Dong], li, F.[Fu], Zhang, H.H.[Hai-Hong],
Human running detection: Benchmark and baseline,
CVIU(153), No. 1, 2016, pp. 143-150.
Elsevier DOI 1612
Running detection BibRef

Van Nguyen, L., La, H.M.,
Real-Time Human Foot Motion Localization Algorithm With Dynamic Speed,
HMS(46), No. 6, December 2016, pp. 822-833.
IEEE DOI 1612
Kalman filters BibRef

Ortells, J.[Javier], Mollineda, R.A.[Ramón A.], Mederos, B.[Boris], Martín-Félez, R.[Raúl],
Gait recognition from corrupted silhouettes: A robust statistical approach,
MVA(28), No. 1-2, February 2017, pp. 15-33.
Springer DOI 1702
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Human gait recognition from motion capture data in signature poses,
IET-Bio(6), No. 2, March 2017, pp. 129-137.
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Balazia, M.[Michal], Hlavácková-Schindler, K.[Katerina], Sojka, P.[Petr], Plant, C.[Claudia],
Interpretable Gait Recognition by Granger Causality,
ICPR22(1069-1075)
IEEE DOI 2212
Measurement, Analytical models, Neural networks, Video surveillance, Skeleton, Motion capture BibRef

Balazia, M.[Michal], Sojka, P.[Petr],
Walker-Independent Features for Gait Recognition from Motion Capture Data,
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Springer DOI 1611
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Chhatrala, R.[Risil], Jadhav, D.V.[Dattatray V.],
Multilinear Laplacian discriminant analysis for gait recognition,
IET-CV(11), No. 2, March 2017, pp. 153-160.
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Ryu, J.[Jaehwan], Lee, B.H.[Byeong-Hyeon], Kim, D.H.[Deok-Hwan],
sEMG Signal-Based Lower Limb Human Motion Detection Using a Top and Slope Feature Extraction Algorithm,
SPLetters(24), No. 7, July 2017, pp. 929-932.
IEEE DOI 1706
Feature extraction, Legged locomotion, Motion detection, Muscles, Reactive power, Signal processing algorithms, Timing, Electromyography (EMG), feature extraction, gait recognition, human-computer interaction, locomotion, mode BibRef

Verlekar, T.T.[Tanmay T.], Correia, P.L.[Paulo L.], Soares, L.D.[Luís D.],
View-invariant gait recognition system using a gait energy image decomposition method,
IET-Bio(6), No. 4, July 2017, pp. 299-306.
DOI Link 1707
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Verlekar, T.T.[Tanmay Tulsidas], Soares, L.D.[Luís Ducla], Correia, P.L.[Paulo Lobato],
Gait recognition in the wild using shadow silhouettes,
IVC(76), 2018, pp. 1-13.
Elsevier DOI 1808
Shadow biometrics, Gait recognition, Biometric recognition, View invariant BibRef

Lishani, A.O.[Ait O.], Boubchir, L.[Larbi], Khalifa, E.[Emad], Bouridane, A.[Ahmed],
Human gait recognition based on Haralick features,
SIViP(11), No. 6, September 2017, pp. 1123-1130.
Springer DOI 1708
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Isaac, E.R.H.P., Elias, S., Rajagopalan, S., Easwarakumar, K.S.,
View-Invariant Gait Recognition Through Genetic Template Segmentation,
SPLetters(24), No. 8, August 2017, pp. 1188-1192.
IEEE DOI 1708
gait analysis, genetic algorithms, image recognition, image segmentation, active energy image template, boundary selection process, gait energy image template, gait entropy image template, genetic algorithm, genetic template segmentation, template-based model-free approach, view-invariant gait recognition, Biological cells, Clothing, Feature extraction, Gait recognition, Genetic algorithms, Genetics, Legged locomotion, Biometrics, gait recognition, genetic algorithms (GAs), linear, discriminant, analysis, (LDA) BibRef

Chaurasia, P., Yogarajah, P., Condell, J.V.[Joan V.], Prasad, G.[Girijesh],
Fusion of Random Walk and Discrete Fourier Spectrum Methods for Gait Recognition,
HMS(47), No. 6, December 2017, pp. 751-762.
IEEE DOI 1712
Clothing, Data mining, Discrete Fourier transforms, Feature extraction, Fourier transforms, Gait recognition, random walk (RW) BibRef

Zou, Q., Ni, L., Wang, Q., Li, Q., Wang, S.,
Robust Gait Recognition by Integrating Inertial and RGBD Sensors,
Cyber(48), No. 4, April 2018, pp. 1136-1150.
IEEE DOI 1804
Feature extraction, Gait recognition, Hidden Markov models, Image color analysis, Legged locomotion, Sensors, Trajectory, person identification BibRef

Medikonda, J.[Jeevan], Madasu, H.[Hanmandlu], Ketan, P.B.[Panigrahi Bijaya],
Information set based features for the speed invariant gait recognition,
IET-Bio(7), No. 3, May 2018, pp. 269-277.
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Jia, N.[Ning], Sanchez, V.[Victor], Li, C.T.[Chang-Tsun],
On view-invariant gait recognition: a feature selection solution,
IET-Bio(7), No. 4, July 2018, pp. 287-295.
DOI Link 1807
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Zhang, Z., Chen, J., Wu, Q., Shao, L.,
GII Representation-Based Cross-View Gait Recognition by Discriminative Projection With List-Wise Constraints,
Cyber(48), No. 10, October 2018, pp. 2935-2947.
IEEE DOI 1809
Gait recognition, Cameras, Feature extraction, Robustness, Correlation, Probes, Databases, Cross-view gait recognition, list-wise constraints BibRef

Khan, M.H., Farid, M.S., Zahoor, M., Grzegorzek, M.,
Cross- View Gait Recognition Using Non-Linear View Transformations of Spatiotemporal Features,
ICIP18(773-777)
IEEE DOI 1809
Spatiotemporal phenomena, Gait recognition, Support vector machines, Training, view transformation BibRef

Rida, I.[Imad], Almaadeed, N.[Noor], Almaadeed, S.[Somaya],
Robust gait recognition: a comprehensive survey,
IET-Bio(8), No. 1, January 2019, pp. 14-28.
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Wang, M.[Mo], Wang, X.[Xin'an], Fan, Z.C.[Zhuo-Chen], Chen, F.[Fei], Zhang, S.[Sixu], Peng, C.[Chen],
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JVCIR(58), 2019, pp. 525-531.
Elsevier DOI 1901
Plantar pressure, Feature extraction, Image denoising, Clustering analysis, Gait analysis BibRef

Ghaeminia, M.H.[Mohammad H.], Shokouhi, S.B.[Shahriar B.],
On the selection of spatiotemporal filtering with classifier ensemble method for effective gait recognition,
SIViP(13), No. 1, February 2019, pp. 43-51.
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A new paradigm for autonomous human motion description and evaluation: Application to the Get Up & Go test use case,
PRL(118), 2019, pp. 51-60.
Elsevier DOI 1902
Human motion analysis, Socially assistive robots, Gait analysis BibRef

Ben, X.[Xianye], Zhang, P.[Peng], Lai, Z.H.[Zhi-Hui], Yan, R.[Rui], Zhai, X.L.[Xin-Liang], Meng, W.X.[Wei-Xiao],
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PR(90), 2019, pp. 87-98.
Elsevier DOI 1903
Gait recognition, Cross-view gait, Tensor representation, Framework BibRef

Zhang, P.[Peng], Xu, J.S.[Jing-Song], Wu, Q.[Qiang], Huang, Y.[Yan], Ben, X.[Xianye],
Learning Spatial-Temporal Representations Over Walking Tracklet for Long-Term Person Re-Identification in the Wild,
MultMed(23), 2021, pp. 3562-3576.
IEEE DOI 2110
Skeleton, Tracking, Image color analysis, Cameras, Streaming media, Trajectory, dataset collection BibRef

Behera, P.K.[Pravat Kumar], Mandava, R.K.[Ravi Kumar], Vundavilli, P.R.[Pandu Ranga],
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Springer DOI 1904
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Spatiotemporal features of human motion for gait recognition,
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Coupled Patch Alignment for Matching Cross-View Gaits,
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IEEE DOI 1905
Gait recognition, Cameras, Feature extraction, Optimization, Probes, Clothing, multi-dimensional patch alignment BibRef

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Gait recognition, Human body pose, Spatio-temporal feature, BibRef

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Gait Lateral Network: Learning Discriminative and Compact Representations for Gait Recognition,
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Hirose, Y.[Yuki], Nakamura, K.[Kazuaki], Nitta, N.[Naoko], Babaguchi, N.[Noboru],
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Wu, H., Tian, J., Fu, Y., Li, B., Li, X.,
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IP(30), 2021, pp. 2734-2744.
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Feature extraction, Gait recognition, Adaptation models, Data models, Shape, Legged locomotion, Geometry, Gait recognition, geometry-guided data augmentation BibRef

Iwamura, M.[Masakazu], Mori, S.[Shunsuke], Nakamura, K.[Koichiro], Tanoue, T.[Takuya], Utsumi, Y.[Yuzuko], Makihara, Y.S.[Yasu-Shi], Muramatsu, D.[Daigo], Kise, K.[Koichi], Yagi, Y.S.[Yasu-Shi],
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Elsevier DOI 2109
Survey, Gait. Human gait recognition, Spatio-temporal features, Gait databases, Gait recognition representation, Gait prediction BibRef

Hasan, M.M.[Md Mahedi], Mustafa, H.A.[Hossen Asiful],
Learning view-invariant features using stacked autoencoder for skeleton-based gait recognition,
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Gait recognition based on sparse linear subspace,
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Tan, X.W.[Xiao-Wei], Zhang, B.[Bi], Liu, G.J.[Guang-Jun], Zhao, X.G.[Xin-Gang], Zhao, Y.W.[Yi-Wen],
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IEEE DOI 2112
Activity recognition, Classification algorithms, Gait recognition, Patient monitoring, Legged locomotion, phase BibRef

Gao, S.[Shuo], Yun, J.[Jing], Zhao, Y.[Yumeng], Liu, L.M.[Li-Min],
Gait-D: Skeleton-based gait feature decomposition for gait recognition,
IET-CV(16), No. 2, 2022, pp. 111-125.
DOI Link 2202
biometrics, convolutional neural nets, feature extraction, pose estimation, video signal processing BibRef

Liu, X.K.[Xiao-Kai], You, Z.Y.[Zhao-Yang], He, Y.X.[Yu-Xiang], Bi, S.[Sheng], Wang, J.[Jie],
Symmetry-Driven hyper feature GCN for skeleton-based gait recognition,
PR(125), 2022, pp. 108520.
Elsevier DOI 2203
Dynamics of skeleton, Gait recognition, Graph convolutional networks, Symmetric interaction pattern, Hyper feature BibRef

Li, H.K.[Hua-Kang], Qiu, Y.[Yidan], Zhao, H.M.[Hui-Min], Zhan, J.[Jin], Chen, R.J.[Rong-Jun], Wei, T.J.[Tuan-Jie], Huang, Z.H.[Zhi-Hui],
GaitSlice: A gait recognition model based on spatio-temporal slice features,
PR(124), 2022, pp. 108453.
Elsevier DOI 2203
Gait recognition, Key frame, Cross-view, Attention mechanism, Slice feature, GaitSlice BibRef

Han, F.[Feng], Li, X.J.[Xue-Jian], Zhao, J.[Jian], Shen, F.[Furao],
A unified perspective of classification-based loss and distance-based loss for cross-view gait recognition,
PR(125), 2022, pp. 108519.
Elsevier DOI 2203
Biometrics, Gait recognition, Computer vision, Metric learning, Angular softmax loss function, Triplet loss function BibRef

Song, X.[Xu], Huang, Y.[Yan], Huang, Y.[Yan], Shan, C.F.[Cai-Feng], Wang, J.L.[Ji-Long], Chen, Y.[Yu],
Distilled light GaitSet: Towards scalable gait recognition,
PRL(157), 2022, pp. 27-34.
Elsevier DOI 2205
Gait recognition, Lightweight network, Knowledge distillation BibRef

Qin, H.[Hao], Chen, Z.[Zhenxue], Guo, Q.Q.[Qing-Qiang], Wu, Q.M.J.[Q. M. Jonathan], Lu, M.X.[Meng-Xu],
RPNet: Gait Recognition With Relationships Between Each Body-Parts,
CirSysVideo(32), No. 5, May 2022, pp. 2990-3000.
IEEE DOI 2205
Feature extraction, Gait recognition, Legged locomotion, Data models, Analytical models, Convolutional neural networks, different scale blocks BibRef

Yao, L.X.[Ling-Xiang], Kusakunniran, W.[Worapan], Wu, Q.[Qiang], Xu, J.S.[Jing-Song], Zhang, J.[Jian],
Collaborative Feature Learning for Gait Recognition Under Cloth Changes,
CirSysVideo(32), No. 6, June 2022, pp. 3615-3629.
IEEE DOI 2206
Feature extraction, Gait recognition, Clothing, Skeleton, Transformers, Visualization, Legged locomotion, Gait recognition, deep learning BibRef

Wang, Y.X.[Yan-Xiang], Zhang, X.[Xian], Shen, Y.R.[Yi-Ran], Du, B.[Bowen], Zhao, G.R.[Guang-Rong], Cui, L.Z.[Li-Zhen], Wen, H.K.[Hong-Kai],
Event-Stream Representation for Human Gaits Identification Using Deep Neural Networks,
PAMI(44), No. 7, July 2022, pp. 3436-3449.
IEEE DOI 2206
Sensors, Voltage control, Feature extraction, Cameras, Task analysis, Gait recognition, Convolution, Gait recognition, graph-based convolutional networks BibRef

Wang, Y.X.[Yan-Xiang], Du, B.[Bowen], Shen, Y.R.[Yi-Ran], Wu, K.[Kai], Zhao, G.R.[Guang-Rong], Sun, J.G.[Jian-Guo], Wen, H.K.[Hong-Kai],
EV-Gait: Event-Based Robust Gait Recognition Using Dynamic Vision Sensors,
CVPR19(6351-6360).
IEEE DOI 2002
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Wang, L.K.[Li-Kai], Chen, J.Y.[Jin-Yan], Liu, Y.X.[Yu-Xin],
Frame-level refinement networks for skeleton-based gait recognition,
CVIU(222), 2022, pp. 103500.
Elsevier DOI 2209
Gait recognition, Graph convolution, Frame-level refinement BibRef

He, Z.[Ziwen], Wang, W.[Wei], Dong, J.[Jing], Tan, T.N.[Tie-Niu],
Temporal sparse adversarial attack on sequence-based gait recognition,
PR(133), 2023, pp. 109028.
Elsevier DOI 2210
Adversarial attack, Gait recognition, Temporal sparsity BibRef

Parashar, A.[Anubha], Parashar, A.[Apoorva], Shekhawat, R.S.[Rajveer Singh],
A robust covariate-invariant gait recognition based on pose features,
IET-Bio(11), No. 6, 2022, pp. 601-613.
DOI Link 2212
biometrics, covariates, deep learning, gait recognition, pose estimation BibRef

Shi, X.[Xin], Wang, Z.[Zhelong], Zhao, H.Y.[Hong-Yu], Qiu, S.[Sen], Liu, R.[Ruichen], Lin, F.[Fang], Tang, K.[Kai],
Threshold-Free Phase Segmentation and Zero Velocity Detection for Gait Analysis Using Foot-Mounted Inertial Sensors,
HMS(53), No. 1, February 2023, pp. 176-186.
IEEE DOI 2301
Micromechanical devices, Inertial sensors, Estimation, Quaternions, Manuals, Man-machine systems, Labeling, Gait analysis, zero velocity updates (ZUPT) BibRef

Shehata, A.[Allam], Makihara, Y.S.[Yasu-Shi], Muramatsu, D.[Daigo], Ahad, M.A.R.[Md Atiqur Rahman], Yagi, Y.S.[Yasu-Shi],
Annotator-dependent uncertainty-aware estimation of gait relative attributes,
PR(136), 2023, pp. 109197.
Elsevier DOI 2301
Gait relative attribute, Relative label distribution, Relative score distribution, Annotator's uncertainty, Transition matrix BibRef

Li, X.[Xiang], Makihara, Y.S.[Yasu-Shi], Xu, C.[Chi], Yagi, Y.S.[Yasu-Shi], Yu, S.Q.[Shi-Qi], Ren, M.W.[Ming-Wu],
End-to-end Model-based Gait Recognition,
ACCV20(III:3-20).
Springer DOI 2103
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Song, C.F.[Chun-Feng], Huang, Y.Z.[Yong-Zhen], Wang, W.N.[Wei-Ning], Wang, L.[Liang],
CASIA-E: A Large Comprehensive Dataset for Gait Recognition,
PAMI(45), No. 3, March 2023, pp. 2801-2815.
IEEE DOI 2302
Dataset, Gait Recognition. Videos, Gait recognition, Legged locomotion, Face recognition, Training, Lighting, Benchmark testing, Deep learning, gait dataset, soft biometrics BibRef

Yao, L.X.[Ling-Xiang], Kusakunniran, W.[Worapan], Zhang, P.[Peng], Wu, Q.[Qiang], Zhang, J.[Jian],
Improving Disentangled Representation Learning for Gait Recognition Using Group Supervision,
MultMed(25), 2023, pp. 4187-4198.
IEEE DOI 2310
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Fan, C.[Chao], Hou, S.[Saihui], Wang, J.[Jilong], Huang, Y.Z.[Yong-Zhen], Yu, S.Q.[Shi-Qi],
Learning Gait Representation From Massive Unlabelled Walking Videos: A Benchmark,
PAMI(45), No. 12, December 2023, pp. 14920-14937.
IEEE DOI 2311
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Chen, Y.F.[Yi-Fan], Li, X.L.[Xue-Long],
Gait feature learning via spatio-temporal two-branch networks,
PR(147), 2024, pp. 110090.
Elsevier DOI 2312
Gait recognition, Spatio-temporal gait feature, Convolutional neural networks BibRef

Sezavar, A.[Ahmadreza], Atta, R.[Randa], Ghanbari, M.[Mohammed],
DCapsNet: Deep capsule network for human activity and gait recognition with smartphone sensors,
PR(147), 2024, pp. 110054.
Elsevier DOI 2312
Gait recognition, Human activity recognition, Capsule network, Smartphone sensors BibRef

Vijayvargiya, A.[Ankit], Kumar, R.[Rajesh], Sharma, P.[Parul],
PC-GNN: Pearson Correlation-Based Graph Neural Network for Recognition of Human Lower Limb Activity Using sEMG Signal,
HMS(53), No. 6, December 2023, pp. 945-954.
IEEE DOI 2312
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Deng, M.Q.[Mu-Qing], Fan, Z.Y.[Zhu-Yao], Lin, P.[Peng], Feng, X.R.[Xiao-Reng],
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IEEE DOI 2401
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Li, A.[Aoqi], Hou, S.[Saihui], Cai, Q.Y.[Qing-Yuan], Fu, Y.[Yang], Huang, Y.Z.[Yong-Zhen],
Gait Recognition With Drones: A Benchmark,
MultMed(26), 2024, pp. 3530-3540.
IEEE DOI 2402
Gait recognition, Drones, Cameras, Task analysis, Feature extraction, Probes, Gait recognition, drones, high vertical views BibRef

Wang, R.S.[Run-Sheng], Shi, Y.X.[Yu-Xuan], Ling, H.[Hefei], Li, Z.Y.[Zong-Yi], Zhao, C.X.[Cheng-Xin], Wei, B.[Bohao], Li, H.[He], Li, P.[Ping],
Gait Recognition With Multi-Level Skeleton-Guided Refinement,
MultMed(26), 2024, pp. 4515-4526.
IEEE DOI 2403
Feature extraction, Bones, Joints, Visualization, Heating systems, Gait recognition, Semantics, Gait recognition, multi-modality BibRef


Guo, H.J.[Hong-Ji], Ji, Q.[Qiang],
Physics-Augmented Autoencoder for 3D Skeleton-Based Gait Recognition,
ICCV23(19570-19581)
IEEE DOI 2401
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Wang, L.[Lei], Liu, B.[Bo], Liang, F.F.[Fang-Fang], Wang, B.[Bincheng],
Hierarchical Spatio-Temporal Representation Learning for Gait Recognition,
ICCV23(19582-19592)
IEEE DOI Code:
WWW Link. 2401
BibRef

Xu, C.[Chi], Tsuji, S.[Shogo], Makihara, Y.S.[Yasu-Shi], Li, X.[Xiang], Yagi, Y.S.[Yasu-Shi],
Occluded Gait Recognition via Silhouette Registration Guided by Automated Occlusion Degree Estimation,
AMFG23(3191-3201)
IEEE DOI 2401
BibRef

Ma, K.[Kang], Fu, Y.[Ying], Zheng, D.[Dezhi], Peng, Y.J.[Yun-Jie], Cao, C.[Chunshui], Huang, Y.Z.[Yong-Zhen],
Fine-grained Unsupervised Domain Adaptation for Gait Recognition,
ICCV23(11279-11288)
IEEE DOI 2401
BibRef

Wang, M.[Ming], Guo, X.[Xianda], Lin, B.B.[Bei-Bei], Yang, T.[Tian], Zhu, Z.[Zheng], Li, L.[Lincheng], Zhang, S.[Shunli], Yu, X.[Xin],
DyGait: Exploiting Dynamic Representations for High-performance Gait Recognition,
ICCV23(13378-13387)
IEEE DOI 2401
BibRef

Fu, Y.[Yang], Meng, S.[Shibei], Hou, S.[Saihui], Hu, X.C.[Xue-Cai], Huang, Y.Z.[Yong-Zhen],
GPGait: Generalized Pose-based Gait Recognition,
ICCV23(19538-19547)
IEEE DOI Code:
WWW Link. 2401
BibRef

Yu, H.[Hao], Liang, Y.C.[Yu-Chen], Liu, Y.H.[Yue-Hu], Zhang, C.[Chi],
Reuse Non-Terrain Policies for Learning Terrain-Adaptive Humanoid Locomotion Skills,
ICIP23(695-699)
IEEE DOI 2312
BibRef

Wang, L.[Lei], Liu, B.[Bo], Wang, B.C.[Bin-Cheng], Yu, F.Q.[Fu-Qiang],
GAITMM: Multi-Granularity Motion Sequence Learning for Gait Recognition,
ICIP23(845-849)
IEEE DOI 2312
BibRef

Xu, C.[Chi], Makihara, Y.S.[Yasu-Shi], Li, X.[Xiang], Yagi, Y.S.[Yasu-Shi],
Gait Recognition from Fisheye Images,
Biometrics23(1030-1040)
IEEE DOI 2309
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Fan, C.[Chao], Liang, J.H.[Jun-Hao], Shen, C.[Chuanfu], Hou, S.[Saihui], Huang, Y.Z.[Yong-Zhen], Yu, S.Q.[Shi-Qi],
OpenGait: Revisiting Gait Recognition Toward Better Practicality,
CVPR23(9707-9716)
IEEE DOI 2309
BibRef

Cui, Y.F.[Yu-Feng], Kang, Y.[Yimei],
Multi-modal Gait Recognition via Effective Spatial-Temporal Feature Fusion,
CVPR23(17949-17957)
IEEE DOI 2309
BibRef

Dou, H.Z.[Huan-Zhang], Zhang, P.Y.[Peng-Yi], Su, W.[Wei], Yu, Y.L.[Yun-Long], Lin, Y.[Yining], Li, X.[Xi],
GaitGCI: Generative Counterfactual Intervention for Gait Recognition,
CVPR23(5578-5588)
IEEE DOI 2309
BibRef

Das, D.[Dhritimaan], Agarwal, A.[Ayush], Chattopadhyay, P.[Pratik],
Gait Recognition from Occluded Sequences in Surveillance Sites,
RealWorld22(703-719).
Springer DOI 2304
BibRef

Zhu, H.D.[Hai-Dong], Zheng, Z.H.[Zhao-Heng], Nevatia, R.[Ram],
Gait Recognition Using 3-D Human Body Shape Inference,
WACV23(909-918)
IEEE DOI 2302
Training, Legged locomotion, Shape, Clothing, Cameras, Task analysis, Algorithms: Biometrics, face, gesture, body pose BibRef

Segundo, M.P.[Mauricio Pamplona], Hill, C.[Cole], Sarkar, S.[Sudeep],
Long range gait matching using 3D body fitting with gait-specific motion constraints,
LongRange23(603-612)
IEEE DOI 2302
Legged locomotion, Deformable models, Training, Solid modeling, Shape, Fitting BibRef

Chen, L.[Lu], Wei, Q.[Qing], Zhang, Z.[Zhitong], Chang, X.[Xu], Wei, X.J.[Xiao-Jian], An, H.L.[Hong-Lei],
Learning to Walk on Low Friction Terrain by Reinforcement Learning,
ICRVC22(355-359)
IEEE DOI 2301
Legged locomotion, Training, Friction, Reinforcement learning, Robustness, Nonlinear dynamical systems, legged robot, low friction BibRef

Li, Z.Q.[Zi-Qiong], Li, Y.R.[Yan-Ran], Yu, S.Q.[Shi-Qi],
FedGait: A Benchmark for Federated Gait Recognition,
ICPR22(1371-1377)
IEEE DOI 2212
Training, Privacy, Data privacy, Machine learning algorithms, Federated learning, Satellite broadcasting, Benchmark testing BibRef

Hsu, H.M.[Hung-Min], Wang, Y.Z.[Yi-Zhou], Yang, C.Y.[Cheng-Yen], Hwang, J.N.[Jenq-Neng], Thuc, H.L.U.[Hoang Le Uyen], Kim, K.J.[Kwang-Ju],
GAITTAKE: Gait Recognition by Temporal Attention and Keypoint-Guided Embedding,
ICIP22(2546-2550)
IEEE DOI 2211
Legged locomotion, Image recognition, Shape, Fuses, Forensics, Pose estimation, Benchmark testing, Gait Recognition, Human Pose Estimation BibRef

Teepe, T.[Torben], Gilg, J.[Johannes], Herzog, F.[Fabian], Hörmann, S.[Stefan], Rigoll, G.[Gerhard],
Towards a Deeper Understanding of Skeleton-based Gait Recognition,
Biometrics22(1568-1576)
IEEE DOI 2210
Training, Visualization, Pose estimation, Performance gain, Feature extraction, Pattern recognition BibRef

Chai, T.R.[Tian-Rui], Li, A.[Annan], Zhang, S.X.[Shao-Xiong], Li, Z.L.[Zi-Long], Wang, Y.H.[Yun-Hong],
Lagrange Motion Analysis and View Embeddings for Improved Gait Recognition,
CVPR22(20217-20226)
IEEE DOI 2210
Legged locomotion, Representation learning, Visualization, Shape, Mathematical models, Pattern recognition, Biometrics, Representation learning BibRef

Huang, X.H.[Xiao-Hu], Zhu, D.W.[Duo-Wang], Wang, H.[Hao], Wang, X.G.[Xing-Gang], Yang, B.[Bo], He, B.T.[Bo-Tao], Liu, W.Y.[Wen-Yu], Feng, B.[Bin],
Context-Sensitive Temporal Feature Learning for Gait Recognition,
ICCV21(12889-12898)
IEEE DOI 2203
Representation learning, Legged locomotion, Adaptation models, Codes, Convolution, Aggregates, Action and behavior recognition, Gestures and body pose BibRef

Zhu, Z.[Zheng], Guo, X.D.[Xian-Da], Yang, T.[Tian], Huang, J.J.[Jun-Jie], Deng, J.K.[Jian-Kang], Huang, G.[Guan], Du, D.L.[Da-Long], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Gait Recognition in the Wild: A Benchmark,
ICCV21(14769-14779)
IEEE DOI 2203
Dataset, Gait Recognition.
WWW Link. Biometrics, Datasets and evaluation, Emergency Reviewer BibRef

Huang, Z.[Zhen], Xue, D.X.[Di-Xiu], Shen, X.[Xu], Tian, X.M.[Xin-Mei], Li, H.Q.[Hou-Qiang], Huang, J.Q.[Jian-Qiang], Hua, X.S.[Xian-Sheng],
3D Local Convolutional Neural Networks for Gait Recognition,
ICCV21(14900-14909)
IEEE DOI 2203
Torso, Legged locomotion, Convolutional codes, Solid modeling, Shape, Spatiotemporal phenomena, Biometrics, Recognition and classification BibRef

Wang, M.[Ming], Lin, B.B.[Bei-Bei], Guo, X.D.[Xian-Da], Li, L.C.[Lin-Cheng], Zhu, Z.[Zheng], Sun, J.D.[Jian-De], Zhang, S.[Shunli], Liu, Y.[Yu], Yu, X.[Xin],
Gaitstrip: Gait Recognition via Effective Strip-based Feature Representations and Multi-level Framework,
ACCV22(IV:711-727).
Springer DOI 2307
BibRef

Lin, B.B.[Bei-Bei], Zhang, S.L.[Shun-Li], Yu, X.[Xin],
Gait Recognition via Effective Global-Local Feature Representation and Local Temporal Aggregation,
ICCV21(14628-14636)
IEEE DOI 2203
Visualization, Convolution, Aggregates, Feature extraction, Data mining, Biometrics, BibRef

Lin, B.B.[Bei-Bei], Zhang, S.[Shunli], Liu, Y.[Yu], Qin, S.[Shengdi],
Multi-Scale Temporal Information Extractor for Gait Recognition,
ICIP21(2998-3002)
IEEE DOI 2201
Image recognition, Aggregates, Feature extraction, Data mining, Convolutional neural networks, Gait recognition, Combined loss function BibRef

Chai, T.R.[Tian-Rui], Mei, X.Y.[Xin-Yu], Li, A.[Annan], Wang, Y.H.[Yun-Hong],
Silhouette-Based View-Embeddings for Gait Recognition Under Multiple Views,
ICIP21(2319-2323)
IEEE DOI 2201
Training, Image recognition, Refining, Estimation, Pattern recognition, Gait recognition, silhouette-based, multi-task BibRef

Su, J.R.[Jing-Ran], Zhao, Y.[Yang], Li, X.L.[Xue-Long],
Progressive Spatio-Temporal Feature Extraction Model for Gait Recognition,
ICIP21(1004-1008)
IEEE DOI 2201
Adaptation models, Image recognition, Fuses, Biological system modeling, Feature extraction, spatiotemporal feature extraction BibRef

Chen, Y.F.[Yi-Fan], Zhao, Y.[Yang], Li, X.L.[Xue-Long],
Effective Gait Feature Extraction Using Temporal Fusion and Spatial Partial,
ICIP21(1244-1248)
IEEE DOI 2201
Legged locomotion, Emotion recognition, Image recognition, Fuses, Feature extraction, Finite element analysis, Gait Recognition, Fine-grained Feature Extraction BibRef

Delgado-Escaño, R.[Rubén], Castro, F.M.[Francisco M.], Guil, N.[Nicolás], Kalogeiton, V.[Vicky], Marín-Jiménez, M.J.[Manuel J.],
Multimodal Gait Recognition Under Missing Modalities,
ICIP21(3003-3007)
IEEE DOI 2201
Image processing, Logic gates, Sensors, Gait recognition, Optical flow BibRef

Zhang, S.X.[Shao-Xiong], Wang, Y.H.[Yun-Hong], Li, A.[Annan],
Cross-View Gait Recognition with Deep Universal Linear Embeddings,
CVPR21(9091-9100)
IEEE DOI 2111
Legged locomotion, Visualization, Linear approximation, Feature extraction, Solids, Nonlinear dynamical systems, Task analysis BibRef

Yu, J., Xia, C., Xie, J., Zhang, H.,
Research on Feature Importance of Gait Mechanomyography Signal Based on Random Forest,
CVIDL20(191-196)
IEEE DOI 2102
accelerometers, biomechanics, electromyography, feature extraction, gait analysis, medical signal processing, muscle, random forest BibRef

Fan, C., Peng, Y., Cao, C., Liu, X., Hou, S., Chi, J., Huang, Y., Li, Q., He, Z.,
GaitPart: Temporal Part-Based Model for Gait Recognition,
CVPR20(14213-14221)
IEEE DOI 2008
Feature extraction, Convolution, Gait recognition, Biological system modeling, Task analysis, Kernel, Legged locomotion BibRef

Hosni, N., Amor, B.B.,
A Geometric ConvNet on 3D Shape Manifold for Gait Recognition,
Diff-CVML20(3725-3734)
IEEE DOI 2008
Pattern recognition BibRef

Mangalam, K., Adeli, E., Lee, K., Gaidon, A., Niebles, J.C.,
Disentangling Human Dynamics for Pedestrian Locomotion Forecasting with Noisy Supervision,
WACV20(2773-2782)
IEEE DOI 2006
Forecasting, Trajectory, Noise measurement, Task analysis, Predictive models, Vehicle dynamics, Dynamics BibRef

Pandey, N., Abdulla, W., Salcic, Z.,
Multi-view Gait recognition using sparse representation,
IVCNZ19(1-6)
IEEE DOI 2004
feature extraction, gait analysis, image motion analysis, image representation, minimisation, minimization, biometrics BibRef

Kato, H.[Hirotaka], Hirayama, T.[Takatsugu], Ide, I.[Ichiro], Doman, K.[Keisuke], Kawanishi, Y.[Yasutomo], Deguchi, D.[Daisuke], Murase, H.[Hiroshi],
More-natural Mimetic Words Generation for Fine-grained Gait Description,
MMMod20(II:214-225).
Springer DOI 2003
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Nouredanesh, M.[Mina], Li, A.W.[Aaron W.], Godfrey, A.[Alan], Hoey, J.[Jesse], Tung, J.[James],
Chasing Feet in the Wild: A Proposed Egocentric Motion-Aware Gait Assessment Tool,
ACVR18(VI:176-192).
Springer DOI 1905
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Dehzangi, O., Sahu, V.,
IMU-Based Robust Human Activity Recognition using Feature Analysis, Extraction, and Reduction,
ICPR18(1402-1407)
IEEE DOI 1812
Feature extraction, Legged locomotion, Activity recognition, Accelerometers, Dimensionality reduction, Kernel, Generalization. BibRef

Narváez, F.[Fabián], Árbito, F.[Fernando], Proaño, R.[Ricardo],
A Quaternion-Based Method to IMU-to-Body Alignment for Gait Analysis,
DHM18(217-231).
Springer DOI 1807
BibRef

Evans, M., Colyer, S., Cosker, D., Salo, A.,
Foot Contact Timings and Step Length for Sprint Training,
WACV18(1652-1660)
IEEE DOI 1806
gait analysis, motion measurement, sport, biomechanics, coaching staff, computer vision based approach, Tracking BibRef

Liu, D.[Dan], Ye, M.[Mao], Li, X.D.[Xu-Dong], Zhang, F.[Feng], Lin, L.[Lan],
Memory-based Gait Recognition,
BMVC16(xx-yy).
HTML Version. 1805
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Yao, L., Kusakunniran, W., Wu, Q., Zhang, J., Tang, Z.,
Robust Gait Recognition under Unconstrained Environments Using Hybrid Descriptions,
DICTA17(1-7)
IEEE DOI 1804
clothing, feature extraction, gait analysis, image motion analysis, image sequences, video signal processing, Gait Energy Image, Videos BibRef

Matsumoto, R., Yoshimura, H., Nishiyama, M., Iwai, Y.,
Feature extraction using gaze of participants for classifying gender of pedestrians in images,
ICIP17(3545-3549)
IEEE DOI 1803
Atmospheric measurements, Feature extraction, Kernel, Particle measurements, Task analysis, Training, Visualization, Gender BibRef

Kato, H., Hirayama, T., Kawanishi, Y., Doman, K., Ide, I., Deguchi, D., Murase, H.,
Toward Describing Human Gaits by Onomatopoeias,
AMFG17(1573-1580)
IEEE DOI 1802
Computational modeling, Feature extraction, Kinetic theory, Legged locomotion, Videos, Visualization BibRef

Wang, Q., Potaraju, C., Turaga, P.,
Measuring Glide-Reflection Symmetry in Human Movements Using Elastic Shape Analysis,
Diff-CVML17(709-716)
IEEE DOI 1709
Foot, Legged locomotion, Real-time systems, Shape, Trajectory BibRef

Yeoh, T.[Tze_Wei], Aguirre, H.E.[Hernán E.], Tanaka, K.[Kiyoshi],
Stacked Progressive Auto-Encoders for Clothing-Invariant Gait Recognition,
CAIP17(II: 151-161).
Springer DOI 1708
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Yu, S., Wang, Q.[Qing], Shen, L.L.[Lin-Lin], Huang, Y.Z.[Yong-Zhen],
View invariant gait recognition using only one uniform model,
ICPR16(889-894)
IEEE DOI 1705
Computational modeling, Feature extraction, Gait recognition, Legged locomotion, Probes, Training, Transforms BibRef

Matin, A., Paul, J., Sayeed, T.,
Segment based co-factor detection and elimination for effective gait recognition,
IVPR17(1-5)
IEEE DOI 1704
Databases BibRef

Kellokumpu, V.[Vili], Särkiniemi, M.[Markus], Zhao, G.Y.[Guo-Ying],
Affective Gait Recognition and Baseline Evaluation from Real World Samples,
SFBA16(I: 567-575).
Springer DOI 1704
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Binsaadoon, A.G.[Amer G.], El-Alfy, E.S.M.[El-Sayed M.],
Multi-Kernel Fuzzy-Based Local Gabor Patterns for Gait Recognition,
ISVC16(I: 790-799).
Springer DOI 1701
BibRef

Manikashani, P.[Peyman], Boyd, J.E.[Jeffrey E.],
A Phase-Entrained Particle Filter for Audio-Locomotion Synchronization,
CRV16(242-249)
IEEE DOI 1612
gait analysis; particle filter; sonification; syncrhonization BibRef

Liang, G., Li, Q., Kang, X.,
Pedestrian detection via a leg-driven physiology framework,
ICIP16(2926-2930)
IEEE DOI 1610
Context BibRef

Lai, C.Y.[Cheng-Yuan], McMahan, R.P., Hall, J.,
March-and-Reach: A realistic ladder climbing technique,
3DUI15(15-18)
IEEE DOI 1511
gait analysis BibRef

Yeoh, T.W.[Tze Wei], Zapotecas-Martínez, S.[Saúl], Akimoto, Y.[Youhei], Aguirre, H.E.[Hernán E.], Tanaka, K.[Kiyoshi],
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Springer DOI 1511
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Kappel, M.[Moritz], Golyanik, V.[Vladislav], Elgharib, M.[Mohamed], Henningson, J.O.[Jann-Ole], Seidel, H.P.[Hans-Peter], Castillo, S.[Susana], Theobalt, C.[Christian], Magnor, M.[Marcus],
High-Fidelity Neural Human Motion Transfer from Monocular Video,
CVPR21(1541-1550)
IEEE DOI 2111
Deep learning, Visualization, Codes, Shape, Image synthesis, Clothing BibRef

Alldieck, T.[Thiemo], Kassubeck, M.[Marc], Wandt, B.[Bastian], Rosenhahn, B.[Bodo], Magnor, M.[Marcus],
Optical Flow-Based 3D Human Motion Estimation from Monocular Video,
GCPR17(347-360).
Springer DOI 1711
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Joint 3D Human Motion Capture and Physical Analysis from Monocular Videos,
Cognition17(17-26)
IEEE DOI 1709
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GCPR15(169-180).
Springer DOI 1511
Cameras, Computational modeling, Optimization, Solid modeling, Torque. BibRef

Iwashita, Y.[Yumi], Sakano, H.[Hitoshi], Kurazume, R.[Ryo],
Gait Recognition Robust to Speed Transition Using Mutual Subspace Method,
CIAP15(I:141-149).
Springer DOI 1511
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Derlatka, M.[Marcin], Bogdan, M.[Mariusz],
Fusion of Static and Dynamic Parameters at Decision Level in Human Gait Recognition,
PReMI15(515-524).
Springer DOI 1511
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Improved Human Gait Recognition,
CIAP15(II:119-129).
Springer DOI 1511
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Makihara, Y., Mansur, A., Muramatsu, D., Uddin, Z., Yagi, Y.,
Multi-view discriminant analysis with tensor representation and its application to cross-view gait recognition,
FG15(1-8)
IEEE DOI 1508
gait analysis BibRef

Kondo, T., Kato, K., Yamamoto, K.,
A proposal of ambient light estimation methods for skin region detection,
FCV15(1-6)
IEEE DOI 1506
gait analysis BibRef

Pu, R.[Rui], Wang, Y.H.[Yun-Hong],
2-D Structure-Based Gait Recognition in Video Using Incremental GMM-HMM,
Gait14(I: 58-70).
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Derbel, A., Chetouani, A., Treuillet, S., Emile, B., Mansouri, N., Ben Jemaa, Y.[Yousra],
Interest lower body point's detection for markerless gait analysis,
IPTA14(1-6)
IEEE DOI 1503
computer vision BibRef

Tafazzoli, F.[Faezeh], Bebis, G.N.[George N.], Louis, S.[Sushil], Hussain, M.[Muhammad],
Improving Human Gait Recognition Using Feature Selection,
ISVC14(II: 830-840).
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ICPR14(1794-1799)
IEEE DOI 1412
Clustering algorithms BibRef

Deng, X.M.[Xiao-Ming], Xia, S.H.[Shi-Hong], Wang, W.Z.[Wen-Zhong], Wang, Z.Q.[Zhao-Qi], Chang, L.[Liang], Wang, H.A.[Hong-An],
Automatic Gait Motion Capture with Missing-Marker Fillings,
ICPR14(2507-2512)
IEEE DOI 1412
Cameras BibRef

Yang, Y.Z.[Ya-Zhou], Tu, D.[Dan], Li, G.H.[Guo-Hui],
Gait Recognition Using Flow Histogram Energy Image,
ICPR14(444-449)
IEEE DOI 1412
Computer vision BibRef

Okada, T., Yamazoe, H., Mitsugami, I., Yagi, Y.,
Preliminary Analysis of Gait Changes That Correspond to Gaze Directions,
ACPR13(788-792)
IEEE DOI 1408
gait analysis BibRef

Sengupta, S., Halder, U., Panda, R., Chowdhury, A.S.,
A frequency domain approach to silhouette based gait recognition,
NCVPRIPG13(1-4)
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Fourier transforms BibRef

Deepak, N.A., Hariharan, R., Sinha, U.N.,
Analysing gait sequences using Latent Dirichlet Allocation for certain human actions,
NCVPRIPG13(1-4)
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gait analysis BibRef

Nakazawa, M., Mitsugami, I., Yamazoe, H., Yagi, Y.,
Distinguishing Pedestrians Facing to the Front and the Side by Gait Observation,
ACPR13(486-490)
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gait analysis BibRef

Lombardi, S.[Stephen], Nishino, K.[Ko], Makihara, Y.S.[Yasu-Shi], Yagi, Y.S.[Yasu-Shi],
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ICCV13(1041-1048)
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Gait Recognition BibRef

Jeevan, M., Jain, N.[Neha], Hanmandlu, M., Chetty, G.[Girija],
Gait recognition based on gait pal and pal entropy image,
ICIP13(4195-4199)
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Gait Pal and Pal Entropy Image (GPPE);Gait Recognition BibRef

Yang, C.[Cheng], Ugbolue, U.[Ukadike], Carse, B.[Bruce], Stankovic, V.[Vladimir], Stankovic, L.[Lina], Rowe, P.[Philip],
Multiple marker tracking in a single-camera system for gait analysis,
ICIP13(3128-3131)
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Gait analysis; Marker tracking; bStructural-Similarity BibRef

Derbel, A.[Ahmed], Mansouri, N.[Nabila], Ben Jemaa, Y.[Yousra], Emile, B.[Bruno], Treuillet, S.[Sylvie],
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IPTA12(313-318)
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cameras BibRef

Chaubey, H., Hanmandlu, M., Vasikarla, S.,
Enhanced view invariant gait recognition using feature level fusion,
AIPR14(1-5)
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gait analysis BibRef

Kochhar, A., Gupta, D., Hanmandlu, M., Vasikarla, S.,
Novel features for silhouette based gait recognition systems,
AIPR12(1-6)
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feature extraction BibRef

Lorenzo, J.O.[Javier Ortells], Martín-Félez, R.[Raúl], Cárdenas, R.A.M.[Ramón A. Mollineda],
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Semi-supervised Gait Recognition Based on Self-Training,
AVSS12(288-293).
IEEE DOI 1211
BibRef

Kolawole, A.[Akintola], Tavakkoli, A.[Alireza],
A Novel Gait Recognition System Based on Hidden Markov Models,
ISVC12(II: 125-134).
Springer DOI 1209
BibRef

Lin, H.W.[Hung-Wei], Hu, M.C.[Min-Chun], Wu, J.L.[Ja-Ling],
Gait-Based Action Recognition via Accelerated Minimum Incremental Coding Length Classifier,
MMMod12(266-276).
Springer DOI 1201
BibRef

Harle, R.[Robert], Cameron, J.[Jonathan], Lasenby, J.[Joan],
Foot Contact Detection for Sprint Training,
VECTaR10(297-306).
Springer DOI 1109
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Zhang, Z.[Zheng], Seah, H.S.[Hock Soon],
Real-time tracking of unconstrained full-body motion using Niching Swarm Filtering combined with local optimization,
HAU3D11(23-28).
IEEE DOI 1106
BibRef

Ishikawa, E.[Eri], Karungaru, S.[Stephen], Terada, K.[Kenji],
Gait features extraction method using image processing,
FCV11(1-6).
IEEE DOI 1102
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Watanabe, Y.[Yoshihiro], Hatanaka, T.[Tetsuo], Komuro, T.[Takashi], Ishikawa, M.[Masatoshi],
Human gait estimation using a wearable camera,
WACV11(276-281).
IEEE DOI 1101
BibRef

Kotsia, I.[Irene], Patras, I.[Ioannis],
Exploring the Similarities of Neighboring Spatiotemporal Points for Action Pair Matching,
ACCV12(III:624-635).
Springer DOI 1304
BibRef
And:
Support tensor action spotting,
ICIP12(1397-1400).
IEEE DOI 1302
BibRef
Earlier:
Relative Margin Support Tensor Machines for gait and action recognition,
CIVR10(446-453).
DOI Link 1007

See also Support tucker machines.
See also Higher rank Support Tensor Machines for visual recognition. BibRef

Olivier, A.H.[Anne-Hélène], Kulpa, R.[Richard], Pettré, J.[Julien], Crétual, A.[Armel],
A Velocity-Curvature Space Approach for Walking Motions Analysis,
MIG09(104-115).
Springer DOI 0911
BibRef

Zhang, Y.Y.[Yuan-Yuan], Yang, N.[Niqing], Li, W.[Wei], Wu, X.J.[Xiao-Juan], Ruan, Q.Q.[Qiu-Qi],
Gait Recognition Using Procrustes Shape Analysis and Shape Context,
ACCV09(III: 256-265).
Springer DOI 0909
BibRef

Tahmoush, D., Silvious, J.,
Remote detection of humans and animals,
AIPR09(1-8).
IEEE DOI 0910
BibRef

Ng, H.[Hu], Tan, W.H.[Wooi-Haw], Tong, H.L.[Hau-Lee], Abdullah, J.[Junaidi], Komiya, R.[Ryoichi],
Extraction and Classification of Human Gait Features,
IVIC09(596-606).
Springer DOI 0911
BibRef

Dadashi, F., Araabi, B.N., Soltanian-Zadeh, H.,
Gait Recognition Using Wavelet Packet Silhouette Representation and Transductive Support Vector Machines,
CISP09(1-5).
IEEE DOI 0910
BibRef

Lawson, W.[Wallace], Duric, Z.[Zoran],
Analyzing Human Gait Using Patterns of Translation and Rotation,
ICIAR09(408-417).
Springer DOI 0907
BibRef

Lawson, W.[Wallace], Duric, Z.[Zoran], Wechsler, H.[Harry],
Gait Analysis using Independent Components of image motion,
FG08(1-6).
IEEE DOI 0809
BibRef

Tanaka, H., Wu, X., Arai, H., Koike, H.,
Modeling timing structures in gait image sequences using bottom-up clustering,
IVCNZ08(1-6).
IEEE DOI 0811
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Lee, T.K.M.[Tracey K. M.], Belkhatir, M., Lee, P.A., Sanei, S.,
Fronto-normal gait incorporating accurate practical looming compensation,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Wu, C.C.[Chun-Chih], Medina, J.[Jose], Zordan, V.B.[Victor B.],
Simple Steps for Simply Stepping,
ISVC08(I: 97-106).
Springer DOI 0812
Animating stepping motion. BibRef

Lawson, W.[Wallace], Wechsler, H.[Harry],
Comparative Assessment of ICA Architectures for Gait Recognition,
BTAS07(1-5).
IEEE DOI 0709
BibRef

Romero-Moreno, M., Martínez-Trinidad, J.F.[J. Francisco], Carrasco-Ochoa, J.A.,
Gait Recognition Based on Silhouette, Contour and Classifier Ensembles,
CIARP08(527-534).
Springer DOI 0809
BibRef

Ding, T.[Tao],
A robust identification approach to gait recognition,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Srivastava, S.[Shruti], Sural, S.[Shamik],
Human Gait Recognition Using Temporal Slices,
PReMI07(592-599).
Springer DOI 0712
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Memisoglu, A.[Aydemir], Gudukbay, U.[Ugur], Ozguc, B.[Bulent],
Motion Control for Realistic Walking Behavior using Inverse Kinematics,
3DTV07(1-4).
IEEE DOI 0705
BibRef

Lee, S.K.[Seung-Kyu], Liu, Y.X.[Yan-Xi], Collins, R.T.[Robert T.],
Shape Variation-Based Frieze Pattern for Robust Gait Recognition,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Suk, H.I.[Heung-Il], Sin, B.K.[Bong-Kee],
HMM-Based Gait Recognition with Human Profiles,
SSPR06(596-603).
Springer DOI 0608
BibRef

Emoto, M., Hayashi, A., Suematsu, N., Iwata, K.,
View Independent Gait Identification Using a Particle Filter,
AVSBS06(74-74).
IEEE DOI 0611
BibRef

Ran, Y.[Yang], Chellappa, R.[Rama], Zheng, Q.F.[Qin-Fen],
Finding Gait in Space and Time,
ICPR06(IV: 586-589).
IEEE DOI 0609
BibRef

Chai, Y.M.[Yan-Mei], Wang, Q.[Qing], Jia, J.P.[Jing-Ping], Zhao, R.C.[Rong-Chun],
A Novel Gait Recognition Method Via Fusing Shape and Kinematics Features,
ISVC06(I: 80-89).
Springer DOI 0611
BibRef
Earlier:
A Novel Human Gait Recognition Method by Segmenting and Extracting the Region Variance Feature,
ICPR06(IV: 425-428).
IEEE DOI 0609
BibRef

Hu, S., Buxton, B.F.,
Using Temporal Coherence for Gait Pose Estimation From a Monocular Camera View,
BMVC05(xx-yy).
HTML Version. 0509
BibRef

Fusco, N.[Nicolas], Nicolas, G.[Guillaume], Multon, F.[Franck], Crétual, A.[Armel],
Simulation of Hemiplegic Subjects' Locomotion,
GW05(236-247).
Springer DOI 0505
BibRef

Das, S.R., Wilson, R.C., Lazarewicz, M.T., Finkel, L.H.,
Gait Recognition by Two-Stage Principal Component Analysis,
FGR06(579-584).
IEEE DOI 0604
BibRef

Zhao, G.Y.[Guo-Ying], Cui, L.[Li], Li, H.[Hua],
Combining Wavelet Velocity Moments and Reflective Symmetry for Gait Recognition,
IWBRS05(205).
Springer DOI 0601
BibRef

Zhao, G.Y.[Guo-Ying], Chen, R.[Rui], Liu, G.Y.[Guo-Yi], Li, H.[Hua],
Amplitude spectrum-based gait recognition,
AFGR04(23-28).
IEEE DOI 0411
BibRef

Chai, Y.M.[Yan-Mei], Ren, J.C.[Jin-Chang], Zhao, R.C.[Rong-Chun], Jia, J.P.[Jing-Ping],
Automatic Gait Recognition using Dynamic Variance Features,
FGR06(475-480).
IEEE DOI 0604
BibRef

Yang, H.D.[Hee-Deok], Sin, B.K.[Bong-Kee], Lee, S.W.[Seong-Whan],
Automatic Pedestrian Detection and Tracking for Real-Time Video Surveillance,
AVBPA03(242-250).
Springer DOI 0310
BibRef

Ye, B.[Bo], Wen, Y.[Yumei],
A New Gait Recognition Method Based on Body Contour,
ICARCV06(1-6).
IEEE DOI 0612
BibRef

Lie, A.S.[Agus Santoso], Shimomoto, R.[Ryo], Sakaguchi, S.[Shohei], Ishimura, T.[Toshiyuki], Enokida, S.[Shuichi], Wada, T.[Tomohito], Ejima, T.[Toshiaki],
Gait Recognition Using Spectral Features of Foot Motion,
AVBPA05(767).
Springer DOI 0509
BibRef

Lie, A.S.[Agus Santoso], Enokida, S.[Shuichi], Wada, T.[Tomohito], Ejima, T.[Toshiaki],
Magnitude and Phase Spectra of Foot Motion for Gait Recognition,
CAIP05(390).
Springer DOI 0509
BibRef

Fei, H., Reid, I.D.[Ian D.],
Dynamic Classifier for Non-rigid Human motion analysis,
BMVC04(xx-yy).
HTML Version. 0508
BibRef

Roy Chowdhury, A.K.[Amit K.],
A Measure of Deformability of Shapes, with Applications to Human Motion Analysis,
CVPR05(I: 398-404).
IEEE DOI 0507
BibRef

Cabo, J.M., Salgado, L., Cabrera, J.,
Adaptive segmentation for gymnastic exercises based on change detection over multiresolution combined differences,
ICIP04(I: 337-340).
IEEE DOI 0505
BibRef

Buades, J.M., Perales, F.J., Gonzalez, M., Aguiló, A., Martinez, P.,
Human Body Analysis with Biomechanics Criteria,
AMDO04(239-248).
Springer DOI 0505
BibRef

Tanawongsuwan, R.[Rawesak], Bobick, A.[Aaron],
Performance Analysis of Time-Distance Gait Parameters under Different Speeds,
AVBPA03(715-724).
Springer DOI 0310
BibRef

Calow, R.[Roman], Michaelis, B.[Bernd], Al-Hamadi, A.[Ayoub],
Solutions for Model-Based Analysis of Human Gait,
DAGM03(540-547).
Springer DOI 0310

See also New Multi-camera Based Facial Expression Analysis Concept, A. BibRef

Davis, J.W.[James W.],
Visual Categorization of Children and Adult Walking Styles,
AVBPA01(295).
Springer DOI 0310
BibRef

Davis, J.W., Taylor, S.R.,
Analysis and recognition of walking movements,
ICPR02(I: 315-318).
IEEE DOI 0211
BibRef

Tassone, E., West, G.A.W., Venkatesh, S.,
Temporal PDMs for gait classification,
ICPR02(II: 1065-1068).
IEEE DOI 0211
BibRef

Meyer, D., Posl, J., Niemann, H.,
Gait Classification with HMMS for Trajectories of Body Parts Extracted by Mixture Densities,
BMVC98(459-468).
PS File. BibRef 9800

Denzler, J.[Joachim], Niemann, H.[Heinrich],
Real-time pedestrian tracking in natural scenes,
CAIP97(42-49).
Springer DOI 9709
BibRef

Meyer, D., Denzler, J.[Joachim], Niemann, H.[Heinrich],
Model Based Extraction of Articulated Objects in Image Sequences for Gait Analysis,
ICIP97(III: 78-81).
IEEE DOI
PS File. BibRef 9700

Cheng, J.C., and Moura, J.,
Tracking Human Walking in Dynamic Scenes,
ICIP97(I: 137-140).
IEEE DOI BibRef 9700

Geiger, D., Liu, T.L.[Tyng-Luh],
Recognizing articulated objects with information theoretic methods,
AFGR96(45-50).
IEEE DOI 9610
BibRef

Qian, R.J., and Huang, T.S.,
Motion Analysis of Articulated Objects with Applications to Human Ambulatory Patterns,
DARPA92(549-553). BibRef 9200
And:
Motion Analysis of Human Ambulatory Patterns,
ICPR92(I:220-223).
IEEE DOI Motion, Walking. BibRef

Niyogi, S.A.,
Spatiotemporal junction analysis for motion boundary detection,
ICIP95(III: 468-471).
IEEE DOI 9510
BibRef

Niyogi, S.A., Adelson, E.H.,
Analyzing and Recognizing Walking Figures in XYT,
CVPR94(469-474).
IEEE DOI BibRef 9400
And: Vismod-223, 1993.
PS File. BibRef
And:
Analyzing Gait with Spatiotemporal Surfaces,
Vismod-290, 1994.
PS File. Walking Motion. BibRef

Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Walking, Gait Recognition, Neural Networks, CNN, Learning .


Last update:Mar 16, 2024 at 20:36:19