21.4 Gesture and Pose Analysis

Chapter Contents (Back)
Surveillance.

21.4.1 Human Posture, or Human Pose, Human Body Pose

Chapter Contents (Back)
Human Pose. Human Posture. Body Pose. Posture. Pose. See also Multi-Person Human Pose Desicriptions. See also Articulated Human Pose Desicriptions. See also Human Pose from Silhouettes. See also Human Posture, Upper Body Posture, Arms. See also Human Motion Capture, Joint Information, Special Activities. See also Human Action Recognition and Detection Using Human Pose. See also Human Detection, People Detection, Pedestrians, Using Body Parts, Body Shape.

Lee, H.J., Chen, Z.,
Determination of 3D Human Body Postures from a Single View,
CVGIP(30), No. 2, May 1985, pp. 148-168.
Elsevier DOI BibRef 8505

Barrón, C.[Carlos], Kakadiaris, I.A.[Ioannis A.],
On the Improvement of Anthropometry and Pose Estimation from a Single Uncalibrated Image,
MVA(14), No. 4, September 2003, pp. 229-236.
Springer DOI 0309
BibRef
Earlier:
The Improvement of Anthropomery and Pose Estimation from a Single Uncalibrated Image,
HUMO00(53-60).
IEEE Top Reference. 0010
See also Model-Based Estimation of 3D Human Motion. BibRef

Barrón, C.[Carlos], Kakadiaris, I.A.[Ioannis A.],
Estimating Anthropometry and Pose from a Single Uncalibrated Image,
CVIU(81), No. 3, March 2001, pp. 269-284.
DOI Link 0001
BibRef
Earlier:
Estimating Anthropometry and Pose from a Single Image,
CVPR00(I: 669-676).
IEEE DOI 0005
See also Model-Based Estimation of 3D Human Motion. BibRef

Bruckstein, A.M.[Alfred M.], Holt, R.J.[Robert J.], Jean, Y.D.[Yves D.], Netravali, A.N.[Arun N.],
On the use of shadows in stance recovery,
IJIST(11), No. 5, 2000, pp. 315-330.
WWW Link. 0110
BibRef

Mori, G.[Greg], and Malik, J.[Jitendra],
Recovering 3D Human Body Configurations Using Shape Contexts,
PAMI(28), No. 7, July 2006, pp. 1052-1062.
IEEE DOI 0606
BibRef
Earlier:
Estimating Human Body Configurations Using Shape Context Matching,
ECCV02(III: 666 ff.).
Springer DOI Or:
PDF File. 0205
From a single image, locate body parts, estimate joint positions, then get 3-D pose. See also Efficient Shape Matching Using Shape Contexts. BibRef

Mori, G., Ren, X.F.[Xiao-Feng], Efros, A.A., Malik, J.,
Recovering Human Body Configurations: Combining Segmentation and Recognition,
CVPR04(II: 326-333).
IEEE DOI 0408
BibRef

Wang, Y.[Yang], Mori, G.[Greg],
Multiple Tree Models for Occlusion and Spatial Constraints in Human Pose Estimation,
ECCV08(III: 710-724).
Springer DOI 0810
BibRef
Earlier:
Boosted Multiple Deformable Trees for Parsing Human Poses,
HUMO07(16-27).
Springer DOI 0710
BibRef

Chen, B.[Bo], Nguyen, N.[Nhan], Mori, G.[Greg],
Human Pose Estimation with Rotated Geometric Blur,
WACV08(1-6).
IEEE DOI 0801
BibRef

Fathi, A.[Alireza], Mori, G.[Greg],
Human Pose Estimation using Motion Exemplars,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Ren, X.F.[Xiao-Feng], Berg, A.C.[Alexander C.], Malik, J.[Jitendra],
Recovering Human Body Configurations Using Pairwise Constraints between Parts,
ICCV05(I: 824-831).
IEEE DOI 0510
BibRef

Dimitrijevic, M., Lepetit, V., Fua, P.,
Human body pose detection using Bayesian spatio-temporal templates,
CVIU(103), No. 2-3, November-December 2006, pp. 127-139.
Elsevier DOI 0611
Keywords: Body pose detection; Spatio-temporal templates; Template matching; Chamfer matching BibRef

Wang, J.M.[Jack M.], Fleet, D.J.[David J.], Hertzmann, A.[Aaron],
Gaussian Process Dynamical Models for Human Motion,
PAMI(30), No. 2, February 2008, pp. 283-298.
IEEE DOI 0712
BibRef
And: Correction: PAMI(30), No. 6, June 2008, pp. 1118-1118.
IEEE DOI 0804
Models of pose from motion capture data. BibRef

Cao, Y.S.[Yan-Shuai], Brubaker, M.A., Fleet, D.J.[David J.], Hertzmann, A.[Aaron],
Efficient Optimization for Sparse Gaussian Process Regression,
PAMI(37), No. 12, December 2015, pp. 2415-2427.
IEEE DOI 1512
Gaussian processes BibRef

Kohli, P.[Pushmeet], Rihan, J.[Jonathan], Bray, M.[Matthieu], Torr, P.H.S.[Philip H. S.],
Simultaneous Segmentation and Pose Estimation of Humans Using Dynamic Graph Cuts,
IJCV(79), No. 3, September 2008, pp. xx-yy.
Springer DOI 0806
BibRef
Earlier: A3, A1, A4, Only:
PoseCut: Simultaneous Segmentation and 3D Pose Estimation of Humans Using Dynamic Graph-Cuts,
ECCV06(II: 642-655).
Springer DOI 0608
BibRef

Rahman, M.M.[M. Masudur], Ishikawa, S.[Seiji],
Human Posture Recognition: Eigenspace Tuning By A Mean Eigenspace,
IJIG(5), No. 4, October 2005, pp. 825-837. 0510
BibRef

Scherff, P.C.[Phillip-Christoph], Baciu, G.[George], Hu, J.L.[Jin-Lian],
Intuitive Parameterized Input Interface For Proportional Reshaping Of Human Bodies,
IJIG(8), No. 2, April 2008, pp. 299-325. 0804
BibRef

Hsieh, J.W.[Jun-Wei], Chuang, C.H., Chen, S.Y., Chen, C.C.A.[Chih-Chi-Ang], Fan, K.C.,
Segmentation of Human Body Parts Using Deformable Triangulation,
SMC-A(40), No. 3, May 2010, pp. 596-610.
IEEE DOI 1003
BibRef

Chen, C.C.A.[Chih-Chi-Ang], Hsieh, J.W.[Jun-Wei], Hsu, Y.T.[Yung-Tai], Huang, C.Y.[Chuan-Yu],
Segmentation of Human Body Parts Using Deformable Triangulation 2,
ICPR06(I: 355-358).
IEEE DOI 0609
BibRef

Yan, J., Shen, S., Li, Y., Liu, Y.,
An Optimization Based Framework for Human Pose Estimation,
SPLetters(17), No. 8, August 2010, pp. 766-769.
IEEE DOI 1007
BibRef

Wachs, J.P.[Juan P.], Kölsch, M.[Mathias], Goshorn, D.[Deborah],
Human posture recognition for intelligent vehicles,
RealTimeIP(5), No. 4, December 2010, pp. 231-244.
WWW Link. 1101
BibRef
Earlier: A3, A1, A2:
The Multi-level Learning and Classification of Multi-class Parts-Based Representations of U.S. Marine Postures,
CIARP09(505-512).
Springer DOI 0911
BibRef

Kuo, P.[Paul], Makris, D.[Dimitrios], Nebel, J.C.[Jean-Christophe],
Integration of bottom-up/top-down approaches for 2D pose estimation using probabilistic Gaussian modelling,
CVIU(115), No. 2, February 2011, pp. 242-255.
Elsevier DOI 1102
Human body pose estimation; Stochastic clustering; Gaussian mixture modelling; Pattern classification; Object recognition; Confidence measure; Ground truth BibRef

Lewandowski, M.[Michal], Makris, D.[Dimitrios], Nebel, J.C.[Jean-Christophe],
Automatic configuration of spectral dimensionality reduction methods for 3D human pose estimation,
VS09(1314-1321).
IEEE DOI 0910
BibRef

Kuo, P.[Paul], Makris, D.[Dimitrios], Megherbi, N.[Najla], Nebel, J.C.[Jean-Christophe],
Integration of Local Image Cues for Probabilistic 2D Pose Recovery,
ISVC08(II: 214-223).
Springer DOI 0812
Fit 2-D human body model. BibRef

Liu, Q.A.[Qi-Ang], Li, H.L.[Hong-Liang], Ngan, K.N.[King Ngi],
Automatic body segmentation with graph cut and self-adaptive initialization level set (SAILS),
JVCIR(22), No. 5, July 2011, pp. 367-377.
Elsevier DOI 1106
Face detection; Motion estimation and compensation; Body segmentation; Object segmentation; Graph cut; Level set; Background contrast removal; Object detection See also FaceSeg: Automatic Face Segmentation for Real-Time Video. BibRef

Xie, F., Xu, G., Cheng, Y., Tian, Y.,
Human body and posture recognition system based on an improved thinning algorithm,
IET-IPR(5), No. 5, 2011, pp. 420-428.
DOI Link 1108
BibRef

Chen, S.S.[Shou-Shun], Akselrod, P.[Polina], Zhao, B.[Bo], Perez-Carrasco, J.A.[Jose Antonio], Linares-Barranco, B.[Bernabe], Culurciello, E.[Eugenio],
Efficient Feedforward Categorization of Objects and Human Postures with Address-Event Image Sensors,
PAMI(34), No. 2, February 2012, pp. 302-314.
IEEE DOI 1112
Line feature models. See also NeuFlow: A runtime reconfigurable dataflow processor for vision. BibRef

Sigal, L.[Leonid], Isard, M.[Michael], Haussecker, H.W.[Horst W.], Black, M.J.[Michael J.],
Loose-limbed People: Estimating 3D Human Pose and Motion Using Non-parametric Belief Propagation,
IJCV(98), No. 1, May 2012, pp. 15-48.
WWW Link. 1204
BibRef

Balan, A.O.[Alexandru O.], Black, M.J.[Michael J.], Haussecker, H.W.[Horst W.], Sigal, L.[Leonid],
Shining a Light on Human Pose: On Shadows, Shading and the Estimation of Pose and Shape,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Brubaker, M.A.[Marcus A.], Sigal, L.[Leonid], Fleet, D.J.[David J.],
Estimating Contact Dynamics,
ICCV09(2389-2396).
IEEE DOI
PDF File. 0909
Body pose. BibRef

Pourdamghani, N.[Nima], Rabiee, H.R.[Hamid R.], Faghri, F.[Fartash], Rohban, M.H.[Mohammad Hossein],
Graph based semi-supervised human pose estimation: When the output space comes to help,
PRL(33), No. 12, 1 September 2012, pp. 1529-1535.
Elsevier DOI 1208
Human pose estimation; Graph based; Semi-supervised; Manifold regularization BibRef

Pourdamghani, N.[Nima], Rabiee, H.R.[Hamid R.], Zolfaghari, M.[Mohammadreza],
Metric learning for graph based semi-supervised human pose estimation,
ICPR12(3386-3389).
WWW Link. 1302
BibRef

Li, S.F.[Shi-Feng], Lu, H.C.[Hu-Chuan], Ruan, X.[Xiang], Chen, Y.W.[Yen-Wei],
Human body segmentation based on independent component analysis with reference at two-scale superpixel,
IET-IPR(6), No. 6, 2012, pp. 770-777.
DOI Link 1210
BibRef
Earlier:
Pose estimation and body segmentation based on hierarchical searching tree,
ICIP11(1289-1292).
IEEE DOI 1201
BibRef

Li, S.F.[Shi-Feng], Yao, M.[Meng], Lu, H.C.[Hu-Chuan],
Human Body Segmentation in a Static Image with On-Line Adaboost at Multiscale Superpixels,
IJIG(12), No. 3, July 2012, pp. 1250018.
DOI Link 1210
BibRef

Tian, Y.[Yan], Sigal, L.[Leonid], de la Torre, F.[Fernando], Jia, Y.H.[Yong-Hua],
Canonical locality preserving Latent Variable Model for discriminative pose inference,
IVC(31), No. 3, March 2013, pp. 223-230.
Elsevier DOI 1303
Human pose estimation; Gaussian Mixture Regression; Latent Variable Model; Discriminative Model BibRef

Tian, Y.[Yan], Jia, Y.H.[Yong-Hua], Shi, Y.[Yuan], Liu, Y.[Yong], Ji, H.[Hao], Sigal, L.[Leonid],
Inferring 3D body pose using variational semi-parametric regression,
ICIP11(29-32).
IEEE DOI 1201
BibRef

Yang, Y.[Yang], Saleemi, I., Shah, M.,
Discovering Motion Primitives for Unsupervised Grouping and One-Shot Learning of Human Actions, Gestures, and Expressions,
PAMI(35), No. 7, 2013, pp. 1635-1648.
IEEE DOI
PDF File. gesture recognition; hidden Markov models; human actions; optical flow; facial expressions BibRef 1300

Lu, H., Shao, X., Xiao, Y.,
Pose Estimation With Segmentation Consistency,
IP(22), No. 10, 2013, pp. 4040-4048.
IEEE DOI 1309
Human Segmentation BibRef

Fergie, M.[Martin], Galata, A.[Aphrodite],
Mixtures of Gaussian process models for human pose estimation,
IVC(31), No. 12, 2013, pp. 949-957.
Elsevier DOI 1312
BibRef
Earlier:
Dynamical Pose Filtering for Mixtures of Gaussian Processes,
BMVC12(7).
DOI Link 1301
BibRef
Earlier:
Local Gaussian Processes for Pose Recognition from Noisy Inputs,
BMVC10(xx-yy).
HTML Version. 1009
Computer vision BibRef

Yamada, M.[Makoto], Sigal, L.[Leonid], Raptis, M.[Michalis],
Covariate Shift Adaptation for Discriminative 3D Pose Estimation,
PAMI(36), No. 2, February 2014, pp. 235-247.
IEEE DOI 1402
BibRef
Earlier:
No Bias Left behind: Covariate Shift Adaptation for Discriminative 3D Pose Estimation,
ECCV12(IV: 674-687).
Springer DOI 1210
Gaussian processes BibRef

Babagholami-Mohamadabadi, B., Jourabloo, A., Zarghami, A., Kasaei, S.,
A Bayesian Framework for Sparse Representation-Based 3-D Human Pose Estimation,
SPLetters(21), No. 3, March 2014, pp. 297-300.
IEEE DOI 1403
Bayes methods BibRef

Ionescu, C.[Catalin], Papava, D., Olaru, V., Sminchisescu, C.[Cristian],
Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments,
PAMI(36), No. 7, July 2014, pp. 1325-1339.
IEEE DOI 1407
Cameras BibRef

Ionescu, C.[Catalin], Li, F.X.[Fu-Xin], Sminchisescu, C.[Cristian],
Latent structured models for human pose estimation,
ICCV11(2220-2227).
IEEE DOI 1201
See also Structural SVM for visual localization and continuous state estimation. BibRef

Cho, E.[Eunji], Kim, D.J.[Dai-Jin],
Accurate Human Pose Estimation by Aggregating Multiple Pose Hypotheses Using Modified Kernel Density Approximation,
SPLetters(22), No. 4, April 2015, pp. 445-449.
IEEE DOI 1411
pose estimation BibRef

Li, S.F.[Shi-Feng], Lu, H.C.[Hu-Chuan], Shao, X.Q.[Xing-Qing],
Human Body Segmentation via Data-Driven Graph Cut,
Cyber(44), No. 11, November 2014, pp. 2099-2108.
IEEE DOI 1411
computer vision BibRef

Chen, M.[Ming], Tan, X.Y.[Xiao-Yang],
Part-based pose estimation with local and non-local contextual information,
IET-CV(8), No. 6, 2014, pp. 475-486.
DOI Link 1502
optimisation. part-based human pose estimation. improve the accuracies for leaf parts locations. BibRef

Li, S.J.[Si-Jin], Liu, Z.Q.[Zhi-Qiang], Chan, A.B.[Antoni B.],
Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network,
IJCV(113), No. 1, May 2015, pp. 19-36.
Springer DOI 1506
BibRef
Earlier: DeepLearn14(488-495)
IEEE DOI 1409
BibRef
And: A1, A3, Only:
3D Human Pose Estimation from Monocular Images with Deep Convolutional Neural Network,
ACCV14(II: 332-347).
Springer DOI 1504
deep learning; human pose estimation; multi-task learning BibRef

Pons-Moll, G.[Gerard], Taylor, J.[Jonathan], Shotton, J.D.J.[Jamie D.J.], Hertzmann, A.[Aaron], Fitzgibbon, A.[Andrew],
Metric Regression Forests for Correspondence Estimation,
IJCV(113), No. 3, July 2015, pp. 163-175.
Springer DOI 1506
BibRef
Earlier:
Metric Regression Forests for Human Pose Estimation,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Taylor, J.[Jonathan], Shotton, J.D.J.[Jamie D.J.], Sharp, T.[Toby], Fitzgibbon, A.[Andrew],
The Vitruvian manifold: Inferring dense correspondences for one-shot human pose estimation,
CVPR12(103-110).
IEEE DOI 1208
BibRef

Xiao, Y., Lu, H., Sun, C.,
Pose Estimation Based on Pose Cluster and Candidates Recombination,
CirSysVideo(25), No. 6, June 2015, pp. 935-943.
IEEE DOI 1506
Biological system modeling pose clustering and body-part candidates. BibRef

Shen, M.[Minmin], Li, C.[Chen], Huang, W.[Wei], Szyszka, P.[Paul], Shirahama, K.[Kimiaki], Grzegorzek, M.[Marcin], Merhof, D.[Dorit], Deussen, O.[Oliver],
Interactive tracking of insect posture,
PR(48), No. 11, 2015, pp. 3560-3571.
Elsevier DOI 1506
Multiple object tracking BibRef

Gonzalez-Sosa, E.[Ester], Vera-Rodriguez, R.[Ruben], Fierrez, J.[Julian], Moreno-Moreno, M.[Miriam], Ortega-Garcia, J.[Javier],
Feature exploration for biometric recognition using millimetre wave body images,
JIVP(2015), No. 1, 2015, pp. 30.
DOI Link 1509
BibRef
Earlier: A1, A2, A3, A5, Only:
Comparison of Body Shape Descriptors for Biometric Recognition Using MMW Images,
ICPR14(124-129)
IEEE DOI 1412
Biomedical imaging BibRef

Vera-Rodriguez, R.[Ruben], Gonzalez-Sosa, E.[Ester], Hernandez-Ortega, J.[Javier], Fierrez, J.[Julian],
Body Shape-Based Biometric Person Recognition from mmW Images,
IbPRIA17(453-461).
Springer DOI 1706
BibRef

Liu, Z.[Zhao], Zhu, J.[Jianke], Bu, J.J.[Jia-Jun], Chen, C.[Chun],
A survey of human pose estimation: The body parts parsing based methods,
JVCIR(32), No. 1, 2015, pp. 10-19.
Elsevier DOI 1511
Human pose estimation BibRef

Hong, C.Q.[Chao-Qun], Yu, J.[Jun], Wan, J.[Jian], Tao, D.C.[Da-Cheng], Wang, M.[Meng],
Multimodal Deep Autoencoder for Human Pose Recovery,
IP(24), No. 12, December 2015, pp. 5659-5670.
IEEE DOI 1512
backpropagation BibRef

Dong, J.[Jian], Chen, Q.A.[Qi-Ang], Huang, Z., Yang, J.C.[Jian-Chao], Yan, S.C.[Shui-Cheng],
Parsing Based on Parselets: A Unified Deformable Mixture Model for Human Parsing,
PAMI(38), No. 1, January 2016, pp. 88-101.
IEEE DOI 1601
Deformable models BibRef

Dong, J.[Jian], Chen, Q.A.[Qi-Ang], Shen, X.H.[Xiao-Hui], Yang, J.C.[Jian-Chao], Yan, S.C.[Shui-Cheng],
Towards Unified Human Parsing and Pose Estimation,
CVPR14(843-850)
IEEE DOI 1409
Human Parsing; Human Pose Estimation BibRef

Tashiro, K.[Kazuhiro], Kawamura, T.[Takahiro], Sei, Y.[Yuichi], Nakagawa, H.[Hiroyuki], Tahara, Y.[Yasuyuki], Ohsuga, A.[Akihiko],
Iterative Improvement of Human Pose Classification Using Guide Ontology,
IEICE(E99-D), No. 1, January 2016, pp. 236-247.
WWW Link. 1601
BibRef

Hernández-Vela, A.[Antonio], Sclaroff, S.[Stan], Escalera, S.[Sergio],
Poselet-Based Contextual Rescoring for Human Pose Estimation via Pictorial Structures,
IJCV(118), No. 1, June 2016, pp. 49-64.
Springer DOI 1605
BibRef
Earlier: A1, A3, A2:
Contextual Rescoring for Human Pose Estimation,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Kang, X.[Xin], Yau, W.P.[Wai-Pan], Taylor, R.H.[Russell H.],
Simultaneous pose estimation and patient-specific model reconstruction from single image using maximum penalized likelihood estimation (MPLE),
PR(57), No. 1, 2016, pp. 61-69.
Elsevier DOI 1605
Pose estimation BibRef

Unzueta, L., Aranjuelo, N., Goenetxea, J., Rodriguez, M., Linaza, M.T.,
Contextualised learning-free three-dimensional body pose estimation from two-dimensional body features in monocular images,
IET-CV(10), No. 4, 2016, pp. 299-306.
DOI Link 1608
cameras BibRef

Liu, H.L.[Hong-Lin], Kong, D.H.[De-Hui], Wang, S.F.[Shao-Fan], Yin, B.C.[Bao-Cai],
Sparse Pose Regression via Componentwise Clustering Feature Point Representation,
MultMed(18), No. 7, July 2016, pp. 1233-1244.
IEEE DOI 1608
feature extraction. 2D pose of human body from range image. BibRef

Belagiannis, V.[Vasileios], Amin, S.[Sikandar], Andriluka, M.[Mykhaylo], Schiele, B.[Bernt], Navab, N.[Nassir], Ilic, S.[Slobodan],
3D Pictorial Structures Revisited: Multiple Human Pose Estimation,
PAMI(38), No. 10, October 2016, pp. 1929-1942.
IEEE DOI 1609
BibRef
Earlier:
3D Pictorial Structures for Multiple Human Pose Estimation,
CVPR14(1669-1676)
IEEE DOI 1409
Biological system modeling 3D pose estimation;human pose estimation;pictorial structures See also Discriminative Appearance Models for Pictorial Structures. BibRef

Belagiannis, V.[Vasileios], Wang, X.C.[Xin-Chao], Schiele, B.[Bernt], Fua, P.[Pascal], Ilic, S.[Slobodan], Navab, N.[Nassir],
Multiple Human Pose Estimation with Temporally Consistent 3D Pictorial Structures,
ChaLearn14(742-754).
Springer DOI 1504
BibRef

Amin, S.[Sikandar], Andriluka, M.[Mykhaylo], Rohrbach, M.[Marcus], Schiele, B.[Bernt],
Multi-view Pictorial Structures for 3D Human Pose Estimation,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Pishchulin, L.[Leonid], Andriluka, M.[Mykhaylo], Gehler, P.[Peter], Schiele, B.[Bernt],
Poselet Conditioned Pictorial Structures,
CVPR13(588-595)
IEEE DOI 1309
articulated pose estimation BibRef

Pishchulin, L.[Leonid], Wuhrer, S.[Stefanie], Helten, T.[Thomas], Theobalt, C.[Christian], Schiele, B.[Bernt],
Building statistical shape spaces for 3D human modeling,
PR(67), No. 1, 2017, pp. 276-286.
Elsevier DOI 1704
Statistical human body model BibRef

Sarafianos, N.[Nikolaos], Boteanu, B.[Bogdan], Ionescu, B.[Bogdan], Kakadiaris, I.A.[Ioannis A.],
3D Human pose estimation: A review of the literature and analysis of covariates,
CVIU(152), No. 1, 2016, pp. 1-20.
Elsevier DOI 1609
Survey, Human Pose. 3D Human pose estimation BibRef

Wu, Y., Lu, T., Yuan, Z., Wang, H.,
FreeScup: A Novel Platform for Assisting Sculpture Pose Design,
MultMed(19), No. 1, January 2017, pp. 183-195.
IEEE DOI 1612
Image reconstruction BibRef

Cho, J.C.[Jung-Chan], Lee, M.[Minsik], Oh, S.H.[Song-Hwai],
Single image 3D human pose estimation using a procrustean normal distribution mixture model and model transformation,
CVIU(155), No. 1, 2017, pp. 150-161.
Elsevier DOI 1702
Human pose estimation BibRef

Hara, K.[Kota], Chellappa, R.[Rama],
Growing Regression Tree Forests by Classification for Continuous Object Pose Estimation,
IJCV(122), No. 2, April 2017, pp. 292-312.
Springer DOI 1704
BibRef
Earlier:
Growing Regression Forests by Classification: Applications to Object Pose Estimation,
ECCV14(II: 552-567).
Springer DOI 1408
BibRef
Earlier:
Computationally Efficient Regression on a Dependency Graph for Human Pose Estimation,
CVPR13(3390-3397)
IEEE DOI 1309
Human Pose Estimation; Regression BibRef

Jammalamadaka, N.[Nataraj], Zisserman, A.[Andrew], Jawahar, C.V.,
Human pose search using deep networks,
IVC(59), No. 1, 2017, pp. 31-43.
Elsevier DOI 1704
BibRef
Earlier:
Human pose search using deep poselets,
FG15(1-8)
IEEE DOI 1508
Pose retrieval. image representation BibRef

Zhu, H.[Hao], Liu, Y.B.[Ye-Bin], Fan, J.T.[Jing-Tao], Dai, Q.H.[Qiong-Hai], Cao, X.[Xun],
Video-Based Outdoor Human Reconstruction,
CirSysVideo(27), No. 4, April 2017, pp. 760-770.
IEEE DOI 1704
Cameras BibRef

Han, F.[Fei], Reily, B.[Brian], Hoff, W.[William], Zhang, H.[Hao],
Space-time representation of people based on 3D skeletal data: A review,
CVIU(158), No. 1, 2017, pp. 85-105.
Elsevier DOI 1704
Human representation BibRef

Nishi, K., Miura, J.,
Generation of human depth images with body part labels for complex human pose recognition,
PR(71), No. 1, 2017, pp. 402-413.
Elsevier DOI 1707
Human, depth, image BibRef

Atrevi, D.F.[Dieudonné Fabrice], Vivet, D.[Damien], Duculty, F.[Florent], Emile, B.[Bruno],
A very simple framework for 3D human poses estimation using a single 2D image: Comparison of geometric moments descriptors,
PR(71), No. 1, 2017, pp. 389-401.
Elsevier DOI 1707
3D, Pose, estimation BibRef

Safi, K.[Khaled], Mohammed, S.[Samer], Albertsen, I.M.[Inke Marie], Delechelle, E.[Eric], Amirat, Y.[Yacine], Khalil, M.[Mohamad], Gracies, J.M.[Jean-Michel], Hutin, E.[Emilie],
Automatic analysis of human posture equilibrium using empirical mode decomposition,
SIViP(11), No. 6, September 2017, pp. 1081-1088.
Springer DOI 1708
BibRef

Gouiaa, R.[Rafik], Meunier, J.[Jean],
Learning cast shadow appearance for human posture recognition,
PRL(97), No. 1, 2017, pp. 54-60.
Elsevier DOI 1709
Cast shadows BibRef

Zhang, S., McCullagh, P., Zheng, H., Nugent, C.,
Situation Awareness Inferred From Posture Transition and Location: Derived From Smartphone and Smart home Sensors,
HMS(47), No. 6, December 2017, pp. 814-821.
IEEE DOI 1712
Accelerometers, Assisted living, Body sensor networks, Context awareness, Radiofrequency identification, Smart homes, wearable computers BibRef

Azrour, S.[Samir], Piérard, S.[Sébastien], Geurts, P.[Pierre], Van Droogenbroeck, M.[Marc],
A Two-Step Methodology for Human Pose Estimation Increasing the Accuracy and Reducing the Amount of Learning Samples Dramatically,
ACIVS17(3-14).
Springer DOI 1712
BibRef

Guo, Y.[Yao], Li, Y.F.[You-Fu], Shao, Z.P.[Zhan-Peng],
RRV: A Spatiotemporal Descriptor for Rigid Body Motion Recognition,
Cyber(48), No. 5, May 2018, pp. 1513-1525.
IEEE DOI 1804
Benchmark testing, Biological system modeling, Matrix decomposition, Quaternions, Skeleton, translational and rotational invariants BibRef

Ning, G., Zhang, Z., He, Z.,
Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation,
MultMed(20), No. 5, May 2018, pp. 1246-1259.
IEEE DOI 1805
Biological system modeling, Fractals, Knowledge engineering, Neural networks, Pose estimation, Training, Human pose estimation, knowledge-guided learning BibRef

Park, S.[Seyoung], Nie, B.X.[Bruce Xiaohan], Zhu, S.C.[Song-Chun],
Attribute And-Or Grammar for Joint Parsing of Human Pose, Parts and Attributes,
PAMI(40), No. 7, July 2018, pp. 1555-1569.
IEEE DOI 1806
Geometry, Glass, Grammar, Head, Magnetic heads, Pose estimation, Predictive models, And-Or grammar, Attribute grammar, pose estimation BibRef

Nie, B.X., Wei, P., Zhu, S.C.,
Monocular 3D Human Pose Estimation by Predicting Depth on Joints,
ICCV17(3467-3475)
IEEE DOI 1802
image motion analysis, pose estimation, recurrent neural nets, 2D human joint locations, HHOI dataset, Human3.6M dataset, BibRef

Liang, G.Q.[Guo-Qiang], Lan, X.G.[Xu-Guang], Wang, J.[Jiang], Wang, J.J.[Jian-Ji], Zheng, N.N.[Nan-Ning],
A Limb-Based Graphical Model for Human Pose Estimation,
SMCS(48), No. 7, July 2018, pp. 1080-1092.
IEEE DOI 1806
BibRef
Earlier: A1, A2, A3, A5, Only:
Human pose estimation based on human limbs,
ICPR16(913-918)
IEEE DOI 1705
Elbow, Feature extraction, Graphical models, Joining processes, Pose estimation, Shape, Visual systems, limbs detection. Adaptation models, Heating systems, ConvNet, Graphical model. BibRef

Petrov, I.[Ilia], Shakhuro, V.[Vlad], Konushin, A.[Anton],
Deep probabilistic human pose estimation,
IET-CV(12), No. 5, August 2018, pp. 578-585.
DOI Link 1807
BibRef

Rogez, G.[Grégory], Schmid, C.[Cordelia],
Image-Based Synthesis for Deep 3D Human Pose Estimation,
IJCV(126), No. 9, September 2018, pp. 993-1008.
Springer DOI 1809
BibRef

Rogez, G., Weinzaepfel, P., Schmid, C.,
LCR-Net: Localization-Classification-Regression for Human Pose,
CVPR17(1216-1224)
IEEE DOI 1711
Computer architecture, Pose estimation, Proposals, Standards, Training, BibRef

Lim, J.[Jongin], Yoo, Y.J.[Young-Joon], Heo, B.[Byeongho], Choi, J.Y.[Jin Young],
Pose transforming network: Learning to disentangle human posture in variational auto-encoded latent space,
PRL(112), 2018, pp. 91-97.
Elsevier DOI 1809
Human pose transform, Disentangle hidden factors in latent space, Generative model, Variational auto-encoder BibRef

Dong, L., Chen, X., Wang, R., Zhang, Q., Izquierdo, E.[Ebroul],
ADORE: An Adaptive Holons Representation Framework for Human Pose Estimation,
CirSysVideo(28), No. 10, October 2018, pp. 2803-2813.
IEEE DOI 1811
Pose estimation, Detectors, Adaptation models, Training, Computational modeling, Image color analysis, Pose estimation, adaptivity BibRef

Nie, X., Feng, J., Xing, J., Xiao, S., Yan, S.,
Hierarchical Contextual Refinement Networks for Human Pose Estimation,
IP(28), No. 2, February 2019, pp. 924-936.
IEEE DOI 1811
Pose estimation, Complexity theory, Heating systems, Biological system modeling, Predictive models, Iterative methods, hierarchical contextual refinement network BibRef

Iqbal, U.[Umar], Doering, A.[Andreas], Yasin, H.[Hashim], Krüger, B.[Björn], Weber, A.[Andreas], Gall, J.[Juergen],
A dual-source approach for 3D human pose estimation from single images,
CVIU(172), 2018, pp. 37-49.
Elsevier DOI 1812
BibRef
Earlier: A2, A1, A4, A5, A6, Only:
A Dual-Source Approach for 3D Pose Estimation from a Single Image,
CVPR16(4948-4956)
IEEE DOI 1612
3D human pose estimation, Motion capture, 3D reconstruction, Articulated pose estimation BibRef

Liang, S.[Shuang], Sun, X.[Xiao], Wei, Y.C.[Yi-Chen],
Compositional Human Pose Regression,
CVIU(176-177), 2018, pp. 1-8.
Elsevier DOI 1812
BibRef

Sun, X.[Xiao], Xiao, B.[Bin], Wei, F.Y.[Fang-Yin], Liang, S.[Shuang], Wei, Y.C.[Yi-Chen],
Integral Human Pose Regression,
ECCV18(VI: 536-553).
Springer DOI 1810
BibRef

Heydari, M.J.[Muhamad Javad], Ghidary, S.S.[Saeed Shiry],
Cross-modal motion regeneration using Multimodal Deep Belief Network,
JVCIR(58), 2019, pp. 245-260.
Elsevier DOI 1901
Multimodal Deep Belief Network. Learn generative 2D and 3D skeletal model. Multimodal deep learning, Multimodal Deep Belief Network, 2D/3D recovery, Cross-modal motion regeneration, Visual correspondence BibRef

Wang, S., Xin, Y., Kong, D., Yin, B.,
Unsupervised Learning of Human Pose Distance Metric via Sparsity Locality Preserving Projections,
MultMed(21), No. 2, February 2019, pp. 314-327.
IEEE DOI 1902
Measurement, Robots, Resource management, Image recognition, Databases, Learning systems, Skeleton, Pose similarity, locality preserving projection BibRef

Wang, D.[Dan], Sheng, Y.[Yun], Zhang, G.[Gui_Xu],
A New Female Body Segmentation and Feature Localisation Method for Image-Based Anthropometry,
MMMod19(I:567-577).
Springer DOI 1901
BibRef

Zhu, H.[Hao], Su, H.[Hao], Wang, P.[Peng], Cao, X.[Xun], Yang, R.G.[Rui-Gang],
View Extrapolation of Human Body from a Single Image,
CVPR18(4450-4459)
IEEE DOI 1812
Shape, Solid modeling, Image generation, Geometry, Estimation BibRef

Kanazawa, A.[Angjoo], Black, M.J., Jacobs, D.W., Malik, J.,
End-to-End Recovery of Human Shape and Pose,
CVPR18(7122-7131)
IEEE DOI 1812
Shape, Solid modeling, Joints, Biological system modeling, Estimation BibRef

Luo, Y.[Yue], Ren, J.[Jimmy], Wang, Z.X.[Zhou-Xia], Sun, W.X.[Wen-Xiu], Pan, J.S.[Jin-Shan], Pang, J.H.[Jia-Hao], Lin, L.[Liang],
LSTM Pose Machines,
CVPR18(5207-5215)
IEEE DOI 1812
Videos, Pose estimation, Computational modeling, Recurrent neural networks, Computer architecture, Benchmark testing BibRef

Nie, X., Feng, J., Zuo, Y., Yan, S.,
Human Pose Estimation with Parsing Induced Learner,
CVPR18(2100-2108)
IEEE DOI 1812
Pose estimation, Adaptation models, Feature extraction, Predictive models, Semantics, Task analysis, Benchmark testing BibRef

Peng, X., Tang, Z., Yang, F., Feris, R.S., Metaxas, D.,
Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation,
CVPR18(2226-2234)
IEEE DOI 1812
Training, Pose estimation, Generators, Neural networks, Task analysis, Data models BibRef

Fang, H., Lu, G., Fang, X., Xie, J., Tai, Y., Lu, C.,
Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer,
CVPR18(70-78)
IEEE DOI 1812
Transforms, Computer vision, Pattern recognition, Knowledge transfer, Image segmentation BibRef

Pavlakos, G., Zhu, L., Zhou, X., Daniilidis, K.,
Learning to Estimate 3D Human Pose and Shape from a Single Color Image,
CVPR18(459-468)
IEEE DOI 1812
Shape, Training, Color, Estimation, Predictive models BibRef

Mehta, D., Sotnychenko, O., Mueller, F., Xu, W., Sridhar, S., Pons-Moll, G., Theobalt, C.,
Single-Shot Multi-person 3D Pose Estimation from Monocular RGB,
3DV18(120-130)
IEEE DOI 1812
cameras, image colour analysis, inference mechanisms, learning (artificial intelligence), pose estimation, bottom up BibRef

Omran, M., Lassner, C., Pons-Moll, G., Gehler, P., Schiele, B.,
Neural Body Fitting: Unifying Deep Learning and Model Based Human Pose and Shape Estimation,
3DV18(484-494)
IEEE DOI 1812
feedforward neural nets, image representation, image segmentation, learning (artificial intelligence), model-based and learning-based human pose and shape estimation BibRef

Saint, A., Ahmed, E., Shabayek, A.E.R., Cherenkova, K., Gusev, G., Aouada, D., Ottersten, B.,
3DBodyTex: Textured 3D Body Dataset,
3DV18(495-504)
IEEE DOI 1812
computer vision, image resolution, image texture, solid modelling, textured 3D body dataset, static 3D body scans, 3D body scans BibRef

Fieraru, M., Khoreva, A., Pishchulin, L., Schiele, B.,
Learning to Refine Human Pose Estimation,
Crowd18(318-31809)
IEEE DOI 1812
Pose estimation, Task analysis, Predictive models, Videos, Training, Data models, Benchmark testing BibRef

Andriluka, M., Iqbal, U., Insafutdinov, E., Pishchulin, L., Milan, A., Gall, J., Schiele, B.,
PoseTrack: A Benchmark for Human Pose Estimation and Tracking,
CVPR18(5167-5176)
IEEE DOI 1812
Pose estimation, Benchmark testing, Task analysis, Tracking, Training, Video sequences, Sports BibRef

Yang, W., Ouyang, W., Wang, X., Ren, J., Li, H., Wang, X.,
3D Human Pose Estimation in the Wild by Adversarial Learning,
CVPR18(5255-5264)
IEEE DOI 1812
Pose estimation, Generators, Heating systems, Joints, Task analysis BibRef

Güler, R.A., Neverova, N., Kokkinos, I.,
DensePose: Dense Human Pose Estimation in the Wild,
CVPR18(7297-7306)
IEEE DOI 1812
Pose estimation, Task analysis, Solid modeling, Training, Pipelines, Deformable models BibRef

Pavlakos, G., Zhou, X., Daniilidis, K.,
Ordinal Depth Supervision for 3D Human Pose Estimation,
CVPR18(7307-7316)
IEEE DOI 1812
Training, Image reconstruction, Pose estimation, Hip, Benchmark testing BibRef

Nie, X.C.[Xue-Cheng], Feng, J.[Jiashi], Yan, S.C.[Shui-Cheng],
Mutual Learning to Adapt for Joint Human Parsing and Pose Estimation,
ECCV18(VI: 519-534).
Springer DOI 1810
BibRef

Chen, Y.T.[Yu-Ting], Chang, W.Y.[Wen-Yen], Lu, H.L.[Hai-Lun], Wu, T.F.[Ting-Fan], Sun, M.[Min],
Leveraging Motion Priors in Videos for Improving Human Segmentation,
ECCV18(VII: 228-244).
Springer DOI 1810
BibRef

Varol, G.[Gül], Ceylan, D.[Duygu], Russell, B.[Bryan], Yang, J.[Jimei], Yumer, E.[Ersin], Laptev, I.[Ivan], Schmid, C.[Cordelia],
BodyNet: Volumetric Inference of 3D Human Body Shapes,
ECCV18(VII: 20-38).
Springer DOI 1810
BibRef

Tang, W.[Wei], Yu, P.[Pei], Wu, Y.[Ying],
Deeply Learned Compositional Models for Human Pose Estimation,
ECCV18(III: 197-214).
Springer DOI 1810
BibRef

Chen, Q., Zhang, C., Liu, W., Wang, D.,
SHPD: Surveillance Human Pose Dataset and Performance Evaluation for Coarse-Grained Pose Estimation,
ICIP18(4088-4092)
IEEE DOI 1809
Surveillance, Pose estimation, Cameras, Lighting, Benchmark testing, Task analysis, Performance evaluation, pose estimation, global-pose BibRef

Hu, H.M.[Hui-Min], Bai, Y.H.[Ya-Hui], Li, Y.X.[Yin-Xia], Wu, H.M.[Hai-Mei], Luo, L.[Ling], Wang, R.[Rui], Hong, P.[Pu],
Research on Ergonomics Design of the Height and Operation Force for Furniture Lockset,
DHM18(64-74).
Springer DOI 1807
BibRef

Friemert, D.[Daniel], Saala, F.[Florian], Hartmann, U.[Ulrich], Ellegast, R.[Rolf],
Similarities and Differences in Posture During Simulated Order Picking in Real Life and Virtual Reality,
DHM18(41-53).
Springer DOI 1807
BibRef

McLaughlin, N.[Niall], Martinez del Rincon, J.[Jesus],
Refining the Pose: Training and Use of Deep Recurrent Autoencoders for Improving Human Pose Estimation,
AMDO18(11-23).
Springer DOI 1807
BibRef

Rafi, U.[Umer], Leibe, B.[Bastian], Gall, J.[Juergen], Kostrikov, I.[Ilya],
An Efficient Convolutional Network for Human Pose Estimation,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Shabayek, A.E.[A. El_Rahman], Aouada, D., Saint, A., Ottersten, B.,
Deformation transfer of 3D human shapes and poses on manifolds,
ICIP17(220-224)
IEEE DOI 1803
Computational modeling, Deformable models, Indexes, Manifolds, Shape, Strain, Deformation transfer, shape modeling BibRef

Yang, Z., Luo, J.,
Personalized pose estimation for body language understanding,
ICIP17(126-130)
IEEE DOI 1803
Heating systems, Pose estimation, Reliability, Task analysis, Videos, Visualization, Wrist, Body Parts Tracking, Pose Estimation BibRef

Tekin, B., Sinha, S.N., Fua, P.,
Real-Time Seamless Single Shot 6D Object Pose Prediction,
CVPR18(292-301)
IEEE DOI 1812
Pose estimation, Solid modeling, Task analysis, Computer architecture BibRef

Tekin, B., Márquez-Neila, P., Salzmann, M., Fua, P.,
Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation,
ICCV17(3961-3970)
IEEE DOI 1802
image fusion, learning (artificial intelligence), motion estimation, pose estimation, 2D joint locations, BibRef

Ronchi, M.R.[Matteo Ruggero], Perona, P.[Pietro],
Benchmarking and Error Diagnosis in Multi-instance Pose Estimation,
ICCV17(369-378)
IEEE DOI 1802
computer vision, estimation theory, learning (artificial intelligence), pose estimation, Wrist BibRef

Wang, H., Liang, W., Yu, L.F.,
Transferring Objects: Joint Inference of Container and Human Pose,
ICCV17(2952-2960)
IEEE DOI 1802
computer vision, inference mechanisms, learning (artificial intelligence), pose estimation, BibRef

Liu, B., Ferrari, V.,
Active Learning for Human Pose Estimation,
ICCV17(4373-4382)
IEEE DOI 1802
learning (artificial intelligence), pose estimation, active learning framework, active learning process, Uncertainty BibRef

Sun, K., Lan, C., Xing, J., Zeng, W., Liu, D., Wang, J.,
Human Pose Estimation Using Global and Local Normalization,
ICCV17(5600-5608)
IEEE DOI 1802
convolution, learning (artificial intelligence), neural nets, pose estimation, articulated pose estimation, Wrist BibRef