16.7.4.6.7 Human Action Recognition and Detection Using Depth, RGB-D, Kinect

Chapter Contents (Back)
Action Recognition. 3-D Recognition. Depth. Kinect. RGB-D.

Darby, J.[John], Li, B.H.[Bai-Hua], Costen, N.P.[Nicholas P.],
Tracking human pose with multiple activity models,
PR(43), No. 9, September 2010, pp. 3042-3058.
Elsevier DOI 1006
BibRef
Earlier:
Behaviour based particle filtering for human articulated motion tracking,
ICPR08(1-4).
IEEE DOI 0812
BibRef
Earlier:
Tracking a walking person using activity-guided annealed particle filtering,
FG08(1-6).
IEEE DOI 0809
BibRef
And:
Human Activity Tracking from Moving Camera Stereo Data,
BMVC08(xx-yy).
PDF File. 0809
Human motion analysis; 3D human tracking; Generative model; Particle filter; Annealing BibRef

Leightley, D.[Daniel], Li, B.H.[Bai-Hua], McPhee, J.S.[Jamie S.], Yap, M.H.[Moi Hoon], Darby, J.[John],
Exemplar-Based Human Action Recognition with Template Matching from a Stream of Motion Capture,
ICIAR14(II: 12-20).
Springer DOI 1410
BibRef

Darby, J.[John], Li, B.H.[Bai-Hua], Costen, N.P.[Nicholas P.], Fleet, D.J.[David J.], Lawrence, N.D.[Neil D.],
Backing Off: Hierarchical Decomposition of Activity for 3d Novel Pose Recovery,
BMVC09(xx-yy).
PDF File. 0909
BibRef

Yan, S.C.[Shui-Cheng], Zhang, Z.Q.[Zhen-Qiu], Fu, Y.[Yun], Hu, Y.X.[Yu-Xiao], Tu, J.L.[Ji-Lin], Huang, T.S.[Thomas S.],
Learning a Person-Independent Representation for Precise 3D Pose Estimation,
MTPH07(xx-yy).
Springer DOI 0705
BibRef

Ni, B.B.[Bing-Bing], Pei, Y.[Yong], Moulin, P.[Pierre], Yan, S.,
Multilevel Depth and Image Fusion for Human Activity Detection,
Cyber(43), No. 5, 2013, pp. 1383-1394.
IEEE DOI 1309
Accuracy BibRef

Ni, B.B.[Bing-Bing], Paramathayalan, V.R.[Vignesh R.], Li, T.[Teng], Moulin, P.[Pierre],
Multiple Granularity Modeling: A Coarse-to-Fine Framework for Fine-grained Action Analysis,
IJCV(120), No. 1, October 2016, pp. 28-43.
Springer DOI 1609
BibRef
Earlier: A1, A2, A4, Only:
Multiple Granularity Analysis for Fine-Grained Action Detection,
CVPR14(756-763)
IEEE DOI 1409
action detection; interaction tracking; multiple granularity BibRef

Pei, Y.[Yong], Ni, B.B.[Bing-Bing], Atmosukarto, I.[Indriyati],
Mixture of Heterogeneous Attribute Analyzers for Human Action Detection,
ChaLearn14(528-540).
Springer DOI 1504
BibRef

Zhou, Y.[Yang], Ni, B.B.[Bing-Bing], Yan, S.C.[Shui-Cheng], Moulin, P.[Pierre], Tian, Q.[Qi],
Pipelining Localized Semantic Features for Fine-Grained Action Recognition,
ECCV14(IV: 481-496).
Springer DOI 1408
BibRef

Ni, B.B.[Bing-Bing], Pei, Y.[Yong], Liang, Z.J.[Zhu-Jin], Lin, L.[Liang], Moulin, P.[Pierre],
Integrating multi-stage depth-induced contextual information for human action recognition and localization,
FG13(1-8)
IEEE DOI 1309
computer vision. With depth sensor. BibRef

Liu, L.[Li], Shao, L.[Ling], Zheng, F.[Feng], Li, X.L.[Xue-Long],
Realistic action recognition via sparsely-constructed Gaussian processes,
PR(47), No. 12, 2014, pp. 3819-3827.
Elsevier DOI 1410
Action recognition BibRef

Shao, L.[Ling], Liu, L.[Li], Yu, M.Y.[Meng-Yang],
Kernelized Multiview Projection for Robust Action Recognition,
IJCV(118), No. 2, June 2016, pp. 115-129.
Springer DOI 1606
See also Learning Short Binary Codes for Large-scale Image Retrieval. BibRef

Yu, M.Y.[Meng-Yang], Liu, L.[Li], Shao, L.[Ling],
Structure-Preserving Binary Representations for RGB-D Action Recognition,
PAMI(38), No. 8, August 2016, pp. 1651-1664.
IEEE DOI 1608
BibRef
Earlier: A2, A1, A3:
Local Feature Binary Coding for Approximate Nearest Neighbor Search,
BMVC15(xx-yy).
DOI Link 1601
binary codes See also Multiview Alignment Hashing for Efficient Image Search. BibRef

Vieira, A.W.[Antonio W.], Nascimento, E.R.[Erickson R.], Oliveira, G.L.[Gabriel L.], Liu, Z.C.[Zi-Cheng], Campos, M.F.M.[Mario F.M.],
On the improvement of human action recognition from depth map sequences using Space-Time Occupancy Patterns,
PRL(36), No. 1, 2014, pp. 221-227.
Elsevier DOI 1312
BibRef
Earlier:
Stop: Space-time Occupancy Patterns for 3d Action Recognition from Depth Map Sequences,
CIARP12(252-259).
Springer DOI 1209
Pattern recognition BibRef

Oliveira, G.L., Nascimento, E.R., Vieira, A.W., Campos, M.F.M.,
Sparse Spatial Coding: A Novel Approach to Visual Recognition,
IP(23), No. 6, June 2014, pp. 2719-2731.
IEEE DOI 1406
Accuracy BibRef

Vasconcelos, L.O.[Levi O.], Nascimento, E.R.[Erickson R.], Campos, M.F.M.[Mario F.M.],
KVD: Scale invariant keypoints by combining visual and depth data,
PRL(86), No. 1, 2017, pp. 83-89.
Elsevier DOI 1702
Keypoint detector BibRef

Nascimento, E.R.[Erickson R.], Schwartz, W.R.[William Robson], Campos, M.F.M.[Mario F.M.],
EDVD: Enhanced descriptor for visual and depth data,
ICPR12(2776-2779).
WWW Link. 1302
BibRef

Yuan, C.F.[Chun-Feng], Li, X.[Xi], Hu, W.M.[Wei-Ming], Ling, H.B.[Hai-Bin], Maybank, S.J.[Stephen J.],
Modeling Geometric-Temporal Context With Directional Pyramid Co-Occurrence for Action Recognition,
IP(23), No. 2, February 2014, pp. 658-672.
IEEE DOI 1402
BibRef
Earlier:
3D-R Transform on Spatio-temporal Interest Points for Action Recognition,
CVPR13(724-730)
IEEE DOI 1309
geometry BibRef

Yuan, C.F.[Chun-Feng], Hu, W.M.[Wei-Ming], Li, X.[Xi], Maybank, S.J.[Stephen J.], Luo, G.[Guan],
Human Action Recognition under Log-Euclidean Riemannian Metric,
ACCV09(I: 343-353).
Springer DOI 0909
BibRef

Cao, X.C.[Xiao-Chun], Zhang, H.[Hua], Deng, C.[Chao], Liu, Q.[Qiguang], Liu, H.[Hanyu],
Action recognition using 3D DAISY descriptor,
MVA(25), No. 1, January 2014, pp. 159-171.
Springer DOI 1402
BibRef

Deng, C.[Chao], Cao, X.C.[Xiao-Chun], Liu, H.[Hanyu], Chen, J.[Jian],
A Global Spatio-Temporal Representation for Action Recognition,
ICPR10(1816-1819).
IEEE DOI 1008
BibRef

Wang, J.[Jiang], Liu, Z.C.[Zi-Cheng], Wu, Y.[Ying],
Human Action Recognition with Depth Cameras,

Springer2014. ISBN 978-3-319-04560-3.
WWW Link. 1404
See also Action Search by Example Using Randomized Visual Vocabularies. BibRef

Wang, J.[Jiang], Liu, Z.C.[Zi-Cheng], Wu, Y.[Ying], Yuan, J.S.[Jun-Song],
Learning Actionlet Ensemble for 3D Human Action Recognition,
PAMI(36), No. 5, May 2014, pp. 914-927.
IEEE DOI 1405
BibRef
Earlier:
Mining actionlet ensemble for action recognition with depth cameras,
CVPR12(1290-1297).
IEEE DOI 1208
Feature extraction See also Abnormal Event Detection in Crowded Scenes Using Sparse Representation. BibRef

Song, Y., Tang, J.H., Liu, F., Yan, S.,
Body Surface Context: A New Robust Feature for Action Recognition From Depth Videos,
CirSysVideo(24), No. 6, June 2014, pp. 952-964.
IEEE DOI 1407
Context BibRef

Song, Y.[Yan], Liu, S.[Shi], Tang, J.H.[Jin-Hui],
Describing Trajectory of Surface Patch for Human Action Recognition on RGB and Depth Videos,
SPLetters(22), No. 4, April 2015, pp. 426-429.
IEEE DOI 1411
feature extraction BibRef

Luo, J.J.[Jia-Jia], Wang, W.[Wei], Qi, H.R.[Hai-Rong],
Spatio-temporal feature extraction and representation for RGB-D human action recognition,
PRL(50), No. 1, 2014, pp. 139-148.
Elsevier DOI 1410
Human action recognition BibRef

Chen, L.[Lulu], Wei, H.[Hong], Ferryman, J.M.[James M.],
ReadingAct RGB-D action dataset and human action recognition from local features,
PRL(50), No. 1, 2014, pp. 159-169.
Elsevier DOI 1410
Human action recognition BibRef

Peng, X.J.[Xiao-Jiang], Qiao, Y.[Yu], Peng, Q.A.[Qi-Ang], Wang, Q.,
Large Margin Dimensionality Reduction for Action Similarity Labeling,
SPLetters(21), No. 8, August 2014, pp. 1022-1025.
IEEE DOI 1406
BibRef

Peng, X.J.[Xiao-Jiang], Qiao, Y.[Yu], Peng, Q.A.[Qi-Ang],
Motion boundary based sampling and 3D co-occurrence descriptors for action recognition,
IVC(32), No. 9, 2014, pp. 616-628.
Elsevier DOI 1408
Dense trajectory BibRef

Peng, X.J.[Xiao-Jiang], Zou, C.Q.[Chang-Qing], Qiao, Y.[Yu], Peng, Q.A.[Qi-Ang],
Action Recognition with Stacked Fisher Vectors,
ECCV14(V: 581-595).
Springer DOI 1408
BibRef

Peng, X.J.[Xiao-Jiang], Qiao, Y.[Yu], Peng, Q.A.[Qi-Ang], Qi, X.B.[Xian-Biao],
Exploring Motion Boundary based Sampling and Spatial-Temporal Context Descriptors for Action Recognition,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Wang, L.M.[Li-Min], Wang, Z., Guo, S., Qiao, Y.[Yu],
Better Exploiting OS-CNNs for Better Event Recognition in Images,
ChaLearnDec15(287-294)
IEEE DOI 1602
Computer vision BibRef

Wang, L.M.[Li-Min], Wang, Z.[Zhe], Du, W.B.[Wen-Bin], Qiao, Y.[Yu],
Object-Scene Convolutional Neural Networks for event recognition in images,
ChaLearn15(30-35)
IEEE DOI 1510
Computer architecture BibRef

Slama, R.[Rim], Wannous, H.[Hazem], Daoudi, M.[Mohamed], Srivastava, A.[Anuj],
Accurate 3D action recognition using learning on the Grassmann manifold,
PR(48), No. 2, 2015, pp. 556-567.
Elsevier DOI 1411
Human action recognition See also 3D human motion analysis framework for shape similarity and retrieval. BibRef

Chen, C.[Chen], Jafari, R.[Roozbeh], Kehtarnavaz, N.[Nasser],
Improving Human Action Recognition Using Fusion of Depth Camera and Inertial Sensors,
HMS(45), No. 1, February 2015, pp. 51-61.
IEEE DOI 1502
BibRef
And:
Action Recognition from Depth Sequences Using Depth Motion Maps-Based Local Binary Patterns,
WACV15(1092-1099)
IEEE DOI 1503
Feature extraction BibRef

Chen, C.[Chen], Liu, K.[Kui], Kehtarnavaz, N.[Nasser],
Real-time human action recognition based on depth motion maps,
RealTimeIP(12), No. 1, June 2016, pp. 155-163.
WWW Link. 1606
BibRef

Hu, M., Chen, C., Cheng, W., Chang, C., Lai, J., Wu, J.,
Real-Time Human Movement Retrieval and Assessment With Kinect Sensor,
Cyber(45), No. 4, April 2015, pp. 742-753.
IEEE DOI 1503
Cameras BibRef

Stückler, J.[Jörg], Behnke, S.[Sven],
Efficient Dense Rigid-Body Motion Segmentation and Estimation in RGB-D Video,
IJCV(113), No. 3, July 2015, pp. 233-245.
Springer DOI 1506
BibRef
Earlier:
Efficient Dense 3D Rigid-Body Motion Segmentation in RGB-D Video,
BMVC13(xx-yy).
DOI Link 1402
BibRef

Cosar, S.[Serhan], Çetin, M.[Müjdat],
Sparsity-Driven Bandwidth-Efficient Decentralized Tracking in Visual Sensor Networks,
CVIU(139), No. 1, 2015, pp. 40-58.
Elsevier DOI 1509
BibRef
Earlier:
A group sparsity-driven approach to 3-D action recognition,
VS11(1904-1911).
IEEE DOI 1201
Camera networks See also Sparsity-Driven Approach to Multi-Camera Tracking in Visual Sensor Networks, A. BibRef

Koppula, H.S.[Hema S.], Saxena, A.[Ashutosh],
Anticipating Human Activities Using Object Affordances for Reactive Robotic Response,
PAMI(38), No. 1, January 2016, pp. 14-29.
IEEE DOI 1601
BibRef
Earlier:
Physically Grounded Spatio-temporal Object Affordances,
ECCV14(III: 831-847).
Springer DOI 1408
Context. The associated objects. BibRef

Jiang, Y.[Yun], Koppula, H.S.[Hema S.], Saxena, A.[Ashutosh],
Modeling 3D Environments through Hidden Human Context,
PAMI(38), No. 10, October 2016, pp. 2040-2053.
IEEE DOI 1609
BibRef
Earlier:
Hallucinated Humans as the Hidden Context for Labeling 3D Scenes,
CVPR13(2993-3000)
IEEE DOI 1309
Computational modeling. hallucinated humans; scene labeling in context of human use. (e.g. spatial relation of keyboard and monitor) BibRef

Zhang, H.[Hao], Parker, L.E.[Lynne E.],
CoDe4D: Color-Depth Local Spatio-Temporal Features for Human Activity Recognition From RGB-D Videos,
CirSysVideo(26), No. 3, March 2016, pp. 541-555.
IEEE DOI 1603
Cameras BibRef

Zhang, H.[Hao], Zhou, W.J.[Wen-Jun], Reardon, C.[Christopher], Parker, L.E.[Lynne E.],
Simplex-Based 3D Spatio-temporal Feature Description for Action Recognition,
CVPR14(2067-2074)
IEEE DOI 1409
Feature description BibRef

Rahmani, H.[Hossein], Huynh, D.Q.[Du Q.], Mahmood, A.[Arif], Mian, A.[Ajmal],
Discriminative human action classification using locality-constrained linear coding,
PRL(72), No. 1, 2016, pp. 62-71.
Elsevier DOI 1604
BibRef
Earlier: A1, A3, A2, A4:
Action Classification with Locality-Constrained Linear Coding,
ICPR14(3511-3516)
IEEE DOI 1412
BibRef
Earlier: A1, A3, A2, A4:
HOPC: Histogram of Oriented Principal Components of 3D Pointclouds for Action Recognition,
ECCV14(II: 742-757).
Springer DOI 1408
Human action classification BibRef

Rahmani, H.[Hossein], Mahmood, A.[Arif], Huynh, D.Q.[Du Q.], Mian, A.[Ajmal],
Histogram of Oriented Principal Components for Cross-View Action Recognition,
PAMI(38), No. 12, December 2016, pp. 2430-2443.
IEEE DOI 1609
Detectors BibRef

Rahmani, H.[Hossein], Mian, A.[Ajmal],
3D Action Recognition from Novel Viewpoints,
CVPR16(1506-1515)
IEEE DOI 1612
BibRef

Brun, L.[Luc], Percannella, G.[Gennaro], Saggese, A.[Alessia], Vento, M.[Mario],
Action recognition by using kernels on aclets sequences,
CVIU(144), No. 1, 2016, pp. 3-13.
Elsevier DOI 1604
BibRef
Earlier:
HAck: A system for the recognition of human actions by kernels of visual strings,
AVSS14(142-147)
IEEE DOI 1411
Human action recognition. Computer hacking BibRef

Foggia, P.[Pasquale], Saggese, A.[Alessia], Strisciuglio, N.[Nicola], Vento, M.[Mario],
Exploiting the deep learning paradigm for recognizing human actions,
AVSS14(93-98)
IEEE DOI 1411
Computer architecture BibRef

Carletti, V.[Vincenzo], Foggia, P.[Pasquale], Percannella, G.[Gennaro], Saggese, A.[Alessia], Vento, M.[Mario],
Recognition of Human Actions from RGB-D Videos Using a Reject Option,
SBA13(436-445).
Springer DOI 1309
BibRef

Lin, L.[Liang], Wang, K.[Keze], Zuo, W.M.[Wang-Meng], Wang, M.[Meng], Luo, J.B.[Jie-Bo], Zhang, L.[Lei],
A Deep Structured Model with Radius-Margin Bound for 3D Human Activity Recognition,
IJCV(118), No. 2, June 2016, pp. 256-273.
Springer DOI 1606
BibRef

Le, C.Q.[Chien-Quang], Phan, S.[Sang], Ngo, T.D.[Thanh Duc], Le, D.D.[Duy-Dinh], Satoh, S.[Shin'ichi], Duong, D.A.[Duc Anh],
Human Action Recognition from Depth Videos Using Pool of Multiple Projections with Greedy Selection,
IEICE(E99-D), No. 8, August 2016, pp. 2161-2171.
WWW Link. 1608
BibRef

Liang, C., Chen, E., Qi, L., Guan, L.,
Improving Action Recognition Using Collaborative Representation of Local Depth Map Feature,
SPLetters(23), No. 9, September 2016, pp. 1241-1245.
IEEE DOI 1609
gesture recognition BibRef

El Din El Madany, N., He, Y., Guan, L.,
Human action recognition via multiview discriminative analysis of canonical correlations,
ICIP16(4170-4174)
IEEE DOI 1610
Accelerometers BibRef

Shahroudy, A.[Amir], Ng, T.T.[Tian-Tsong], Yang, Q.X.[Qing-Xiong], Wang, G.[Gang],
Multimodal Multipart Learning for Action Recognition in Depth Videos,
PAMI(38), No. 10, October 2016, pp. 2123-2129.
IEEE DOI 1609
Feature extraction BibRef

Hsu, Y.P.[Yen-Pin], Liu, C.[Chengyin], Chen, T.Y.[Tzu-Yang], Fu, L.C.[Li-Chen],
Online view-invariant human action recognition using RGB-D spatio-temporal matrix,
PR(60), No. 1, 2016, pp. 215-226.
Elsevier DOI 1609
Action recognition BibRef

Zhang, J.[Jing], Li, W.Q.[Wan-Qing], Ogunbona, P.O.[Philip O.], Wang, P.[Pichao], Tang, C.[Chang],
RGB-D-based action recognition datasets: A survey,
PR(60), No. 1, 2016, pp. 86-105.
Elsevier DOI 1609
Dataset, Action Recognition. Action recognition BibRef

Zhou, L.J.[Li-Juan], Li, W.Q.[Wan-Qing], Ogunbona, P.O.[Philip O.], Zhang, Z.Y.[Zheng-You],
Semantic action recognition by learning a pose lexicon,
PR(72), No. 1, 2017, pp. 548-562.
Elsevier DOI 1708
Lexicon BibRef

Jia, C., Fu, Y.,
Low-Rank Tensor Subspace Learning for RGB-D Action Recognition,
IP(25), No. 10, October 2016, pp. 4641-4652.
IEEE DOI 1610
gesture recognition BibRef

Jia, C., Shao, M., Fu, Y.,
Sparse Canonical Temporal Alignment With Deep Tensor Decomposition for Action Recognition,
IP(26), No. 2, February 2017, pp. 738-750.
IEEE DOI 1702
decomposition BibRef

Vemulapalli, R.[Raviteja], Arrate, F.[Felipe], Chellappa, R.[Rama],
R3DG features: Relative 3D geometry-based skeletal representations for human action recognition,
CVIU(152), No. 1, 2016, pp. 155-166.
Elsevier DOI 1609
BibRef
Earlier:
Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group,
CVPR14(588-595)
IEEE DOI 1409
Action Recognition;Lie Groups;Special Euclidean Group Action recognition BibRef

Vemulapalli, R.[Raviteja], Chellappa, R.[Rama],
Rolling Rotations for Recognizing Human Actions from 3D Skeletal Data,
CVPR16(4471-4479)
IEEE DOI 1612
BibRef

Salih, A.A.A.[Al Alwani Adnan], Youssef, C.[Chahir],
Spatiotemporal representation of 3D skeleton joints-based action recognition using modified spherical harmonics,
PRL(83, Part 1), No. 1, 2016, pp. 32-41.
Elsevier DOI 1609
Spherical harmonics BibRef

Wang, W.[Wei], Yan, Y.[Yan], Zhang, L.M.[Lu-Ming], Hong, R., Sebe, N.[Nicu],
Collaborative Sparse Coding for Multiview Action Recognition,
MultMedMag(23), No. 4, October 2016, pp. 80-87.
IEEE DOI 1612
Collaboration BibRef

Wang, W.[Wei], Yan, Y.[Yan], Nie, L.Q.[Li-Qiang], Zhang, L.M.[Lu-Ming], Winkler, S.[Stefan], Sebe, N.[Nicu],
Sparse Code Filtering for Action Pattern Mining,
ACCV16(II: 3-18).
Springer DOI 1704
BibRef

Liu, Z.[Zhi], Zhang, C.Y.[Chen-Yang], Tian, Y.[Yingli],
3D-based Deep Convolutional Neural Network for action recognition with depth sequences,
IVC(55, Part 2), No. 1, 2016, pp. 93-100.
Elsevier DOI 1612
Action recognition BibRef

Perez, A.[Alexandre], Tabia, H.[Hedi], Declercq, D.[David], Zanotti, A.[Alain],
Using the conflict in Dempster-Shafer evidence theory as a rejection criterion in classifier output combination for 3D human action recognition,
IVC(55, Part 2), No. 1, 2016, pp. 149-157.
Elsevier DOI 1612
Human action recognition BibRef

Perez, A.[Alexandre], Tabia, H.[Hedi], Declercq, D.[David], Zanotti, A.[Alain],
Feature covariance for human action recognition,
IPTA16(1-5)
IEEE DOI 1703
covariance matrices BibRef

Lillo, I.[Ivan], Niebles, J.C.[Juan Carlos], Soto, A.[Alvaro],
Sparse composition of body poses and atomic actions for human activity recognition in RGB-D videos,
IVC(59), No. 1, 2017, pp. 63-75.
Elsevier DOI 1704
Activity recognition BibRef

Guo, Y.[Yanan], Tao, D.P.[Da-Peng], Liu, W., Cheng, J.[Jun],
Multiview Cauchy Estimator Feature Embedding for Depth and Inertial Sensor-Based Human Action Recognition,
SMCS(47), No. 4, April 2017, pp. 617-627.
IEEE DOI 1704
Cameras BibRef

Huang, M.[Min], Su, S.Z.[Song-Zhi], Cai, G.R.[Guo-Rong], Zhang, H.B.[Hong-Bo], Cao, D.[Donglin], Li, S.Z.[Shao-Zi],
Meta-action descriptor for action recognition in RGBD video,
IET-CV(11), No. 4, June 2017, pp. 301-308.
DOI Link 1705
BibRef

Gao, Z., Li, S.H., Zhu, Y.J., Wang, C., Zhang, H.,
Collaborative sparse representation leaning model for RGBD action recognition,
JVCIR(48), No. 1, 2017, pp. 442-452.
Elsevier DOI 1708
RGBD, action, recognition BibRef

Hao, T.[Tong], Wu, D.[Dan], Wang, Q.[Qian], Sun, J.S.[Jin-Sheng],
Multi-view representation learning for multi-view action recognition,
JVCIR(48), No. 1, 2017, pp. 453-460.
Elsevier DOI 1708
Multi-view, learning BibRef


Liu, M.Y.[Meng-Yuan], Liu, H.[Hong], Chen, C.[Chen], Najafian, M.[Maryam],
Energy-Based Global Ternary Image for Action Recognition Using Sole Depth Sequences,
3DV16(47-55)
IEEE DOI 1701
Encoding. Changes in depth pixels. BibRef

Awwad, S., Piccardi, M.[Massimo],
Local depth patterns for fine-grained activity recognition in depth videos,
ICVNZ16(1-6)
IEEE DOI 1701
Activity recognition BibRef

Li, J., Chen, J., Sun, L.,
Joint Motion Similarity (JMS)-Based Human Action Recognition Using Kinect,
DICTA16(1-8)
IEEE DOI 1701
Feature extraction BibRef

Wang, Q.[Qian], Jin, W.[Wei], Wang, G.[Gang],
Gathering Event Detection by Stereo Vision,
ISVC16(II: 431-442).
Springer DOI 1701
BibRef

Ling, J.[Jiaxu], Tian, L.H.[Li-Hua], Li, C.[Chen],
3D Human Activity Recognition Using Skeletal Data from RGBD Sensors,
ISVC16(II: 133-142).
Springer DOI 1701
BibRef

Gupta, K., Bhavsar, A.,
Scale Invariant Human Action Detection from Depth Cameras Using Class Templates,
PBVS16(304-311)
IEEE DOI 1612
BibRef

Shahroudy, A., Liu, J., Ng, T.T., Wang, G.,
NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis,
CVPR16(1010-1019)
IEEE DOI 1612
Dataset, Human Activity. BibRef

Lan, Z., Zhu, Y.[Yi], Hauptmann, A.G., Newsam, S.[Shawn],
Deep Local Video Feature for Action Recognition,
ActionCh17(1219-1225)
IEEE DOI 1709
Feature extraction, Neural networks, Noise measurement, Pattern recognition, Streaming media, Training BibRef

Zhu, Y.[Yi], Newsam, S.[Shawn],
Efficient Action Detection in Untrimmed Videos via Multi-task Learning,
WACV17(197-206)
IEEE DOI 1609
BibRef
Earlier:
Depth2Action: Exploring Embedded Depth for Large-Scale Action Recognition,
WebScale16(I: 668-684).
Springer DOI 1611
Computational modeling, Proposals, Three-dimensional displays, Training, Training data, Videos BibRef

Hu, J.F.[Jian-Fang], Zheng, W.S.[Wei-Shi], Ma, L.[Lianyang], Wang, G.[Gang], Lai, J.H.[Jian-Huang],
Real-Time RGB-D Activity Prediction by Soft Regression,
ECCV16(I: 280-296).
Springer DOI 1611
BibRef

Cippitelli, E.[Enea], Gambi, E.[Ennio], Spinsante, S.[Susanna], Florez-Revuelta, F.[Francisco],
Human Action Recognition Based on Temporal Pyramid of Key Poses Using RGB-D Sensors,
ACIVS16(510-521).
Springer DOI 1611
BibRef

Nguyen, X.S.[Xuan Son], Nguyen, T.P.[Thanh Phuong], Charpillet, F.,
Effective surface normals based action recognition in depth images,
ICPR16(817-822)
IEEE DOI 1705
BibRef
And:
Improving surface normals based action recognition in depth images,
AVSS16(109-114)
IEEE DOI 1611
Computational modeling, Encoding, Feature extraction, Histograms, Image recognition, Shape, Three-dimensional, displays BibRef

Miao, J., Jia, X., Mathew, R., Xu, X., Taubman, D., Qing, C.,
Efficient action recognition from compressed depth maps,
ICIP16(16-20)
IEEE DOI 1610
Decision support systems BibRef

Khan, M.H., Helsper, J., Boukhers, Z., Grzegorzek, M.,
Automatic recognition of movement patterns in the vojta-therapy using RGB-D data,
ICIP16(1235-1239)
IEEE DOI 1610
Cameras BibRef

Antunes, M., Aouada, D., Ottersten, B.,
A revisit to human action recognition from depth sequences: Guided SVM-sampling for joint selection,
WACV16(1-8)
IEEE DOI 1606
Cameras BibRef

Liu, Z.[Zhi], Feng, X.[Xin], Tian, Y.L.[Ying-Li],
An effective view and time-invariant action recognition method based on depth videos,
VCIP15(1-4)
IEEE DOI 1605
Cameras BibRef

Liang, B., Zheng, L.,
A Survey on Human Action Recognition Using Depth Sensors,
DICTA15(1-8)
IEEE DOI 1603
feature extraction BibRef

Li, W.B.[Wen-Bo], Wen, L.Y.[Long-Yin], Chuah, M.C.[Mooi Choo], Lyu, S.[Siwei],
Category-Blind Human Action Recognition: A Practical Recognition System,
ICCV15(4444-4452)
IEEE DOI 1602
Feature extraction BibRef

Tachos, S.[Stavros], Avgerinakis, K.[Konstantinos], Briasouli, A.[Alexia], Kompatsiaris, I.[Ioannis],
Appearance and Depth for Rapid Human Activity Recognition in Real Applications,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Chen, C.[Chen], Hou, Z.J.[Zhen-Jie], Zhang, B.C.[Bao-Chang], Jiang, J.J.[Jun-Jun], Yang, Y.[Yun],
Gradient Local Auto-Correlations and Extreme Learning Machine for Depth-Based Activity Recognition,
ISVC15(I: 613-623).
Springer DOI 1601
BibRef

Liu, H.[Hong], Tian, L.[Lu], Liu, M.Y.[Meng-Yuan], Tang, H.[Hao],
SDM-BSM: A fusing depth scheme for human action recognition,
ICIP15(4674-4678)
IEEE DOI 1512
Bag of Words BibRef

Chen, C.[Chen], Jafari, R.[Roozbeh], Kehtarnavaz, N.[Nasser],
UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor,
ICIP15(168-172)
IEEE DOI 1512
Multimodal human action dataset BibRef

Yang, R.[Rui], Yang, R.[Ruoyu],
DMM-Pyramid Based Deep Architectures for Action Recognition with Depth Cameras,
ACCV14(V: 37-49).
Springer DOI 1504
BibRef

Papadopoulos, G.T.[Georgios Th.], Daras, P.[Petros],
Local descriptions for human action recognition from 3D reconstruction data,
ICIP14(2814-2818)
IEEE DOI 1502
Computer vision BibRef

Lee, A.R.[A-Reum], Suk, H.I.[Heung-Il], Lee, S.W.[Seong-Whan],
View-Invariant 3D Action Recognition Using Spatiotemporal Self-Similarities from Depth Camera,
ICPR14(501-505)
IEEE DOI 1412
Computer vision BibRef

Keceli, A.S.[Ali Seydi], Can, A.B.[Ahmet Burak],
A Multimodal Approach for Recognizing Human Actions Using Depth Information,
ICPR14(421-426)
IEEE DOI 1412
Accuracy BibRef

Lin, Y.Y.[Yen-Yu], Hua, J.H.[Ju-Hsuan], Tang, N.C.[Nick C.], Chen, M.H.[Min-Hung], Liao, H.Y.M.[Hong-Yuan Mark],
Depth and Skeleton Associated Action Recognition without Online Accessible RGB-D Cameras,
CVPR14(2617-2624)
IEEE DOI 1409
BibRef

Lu, C.[Cewu], Jia, J.Y.[Jia-Ya], Tang, C.K.[Chi-Keung],
Range-Sample Depth Feature for Action Recognition,
CVPR14(772-779)
IEEE DOI 1409
Action Recognition;Binary Feature;Depth;Sampling BibRef

Hadfield, S.[Simon], Lebeda, K.[Karel], Bowden, R.[Richard],
Natural Action Recognition Using Invariant 3D Motion Encoding,
ECCV14(II: 758-771).
Springer DOI 1408
BibRef

Rahmani, H.[Hossein], Mian, A.[Ajmal],
Learning a non-linear knowledge transfer model for cross-view action recognition,
CVPR15(2458-2466)
IEEE DOI 1510
BibRef

Rahmani, H.[Hossein], Mahmood, A.[Arif], Huynh, D.Q.[Du Q.], Mian, A.[Ajmal],
Real time action recognition using histograms of depth gradients and random decision forests,
WACV14(626-633)
IEEE DOI 1406
Feature extraction BibRef

Zanfir, M.[Mihai], Leordeanu, M.[Marius], Sminchisescu, C.[Cristian],
The Moving Pose: An Efficient 3D Kinematics Descriptor for Low-Latency Action Recognition and Detection,
ICCV13(2752-2759)
IEEE DOI 1403
RGB-D cameras BibRef

Luo, J.J.[Jia-Jia], Wang, W.[Wei], Qi, H.R.[Hai-Rong],
Group Sparsity and Geometry Constrained Dictionary Learning for Action Recognition from Depth Maps,
ICCV13(1809-1816)
IEEE DOI 1403
BibRef

Körner, M.[Marco], Denzler, J.[Joachim],
JAR-Aibo: A Multi-view Dataset for Evaluation of Model-Free Action Recognition Systems,
SBA13(527-535).
Springer DOI 1309
BibRef
And:
Temporal Self-Similarity for Appearance-Based Action Recognition in Multi-View Setups,
CAIP13(163-171).
Springer DOI 1308
BibRef
Earlier:
Analyzing the Subspaces Obtained by Dimensionality Reduction for Human Action Recognition from 3d Data,
AVSS12(130-135).
IEEE DOI 1211
BibRef

Wang, H.J.[Hao-Jen], Lin, Y.L.[Yen-Liang], Huang, C.Y.[Cheng-Yu], Hou, Y.L.[Yu-Lin], Hsu, W.[Winston],
Full body human attribute detection in indoor surveillance environment using color-depth information,
AVSS13(383-388)
IEEE DOI 1311
Color BibRef

Negin, F.[Farhood], Özdemir, F.[Flrat], Akgül, C.B.[Ceyhun Burak], Yüksel, K.A.[Kamer Ali], Erçil, A.[Aytül],
A Decision Forest Based Feature Selection Framework for Action Recognition from RGB-Depth Cameras,
ICIAR13(648-657).
Springer DOI 1307
BibRef

Oreifej, O.[Omar], Liu, Z.C.[Zi-Cheng],
HON4D: Histogram of Oriented 4D Normals for Activity Recognition from Depth Sequences,
CVPR13(716-723)
IEEE DOI 1309
3D BibRef

Seidenari, L.[Lorenzo], Varano, V.[Vincenzo], Berretti, S.[Stefano], del Bimbo, A.[Alberto], Pala, P.[Pietro],
Weakly Aligned Multi-part Bag-of-Poses for Action Recognition from Depth Cameras,
SBA13(446-455).
Springer DOI 1309
BibRef
And:
Recognizing Actions from Depth Cameras as Weakly Aligned Multi-part Bag-of-Poses,
HAU3D13(479-485)
IEEE DOI 1309
RGB-D;action recognition;depth cameras BibRef

Azary, S.[Sherif], Savakis, A.E.[Andreas E.],
Grassmannian Spectral Regression for Action Recognition,
ISVC13(II:189-198).
Springer DOI 1311
BibRef
And:
Grassmannian Sparse Representations and Motion Depth Surfaces for 3D Action Recognition,
HAU3D13(492-499)
IEEE DOI 1309
BibRef

Yumiba, R.[Ryo], Agata, Y.[Yoshiki], Fujiyoshi, H.[Hironobu],
A Compensation Method of Motion Features with Regression for Deficient Depth Image,
HAU3D13(558-565)
IEEE DOI 1309
Action Recognition; Depth Image BibRef

Avola, D.[Danilo], Cinque, L.[Luigi], Levialdi, S.[Stefano], Placidi, G.[Giuseppe],
Human Body Language Analysis: A Preliminary Study Based on Kinect Skeleton Tracking,
SBA13(465-473).
Springer DOI 1309
BibRef

Wang, J.[Jiang], Liu, Z.C.[Zi-Cheng], Chorowski, J.[Jan], Chen, Z.Y.[Zhuo-Yuan], Wu, Y.[Ying],
Robust 3D Action Recognition with Random Occupancy Patterns,
ECCV12(II: 872-885).
Springer DOI 1210
BibRef

Chen, L.J.[Lu-Jun], Yao, H.X.[Hong-Xun], Sun, X.S.[Xiao-Shuai],
Action retrieval based on generalized dynamic depth data matching,
VCIP12(1-4).
IEEE DOI 1302
BibRef

Li, W.Q.[Wan-Qing], Zhang, Z.Y.[Zheng-You], Liu, Z.C.[Zi-Cheng],
Action recognition based on a bag of 3D points,
CVPR4HB10(9-14).
IEEE DOI 1006
BibRef

Minhas, R.[Rashid], Baradarani, A.[Aryaz], Seifzadeh, S.[Sepideh], Wu, Q.M.J.[Q. M. Jonathan],
Human Action Recognition Using Non-separable Oriented 3D Dual-Tree Complex Wavelets,
ACCV09(III: 226-235).
Springer DOI 0909
BibRef

Hahn, M.[Markus], Krüger, L.[Lars], Wöhler, C.[Christian],
3D Action Recognition and Long-Term Prediction of Human Motion,
CVS08(xx-yy).
Springer DOI 0805
BibRef

Grundmann, M.[Matthias], Meier, F.[Franziska], Essa, I.A.[Irfan A.],
3D Shape Context and Distance Transform for action recognition,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Klaeser, A., Marszalek, M., Schmid, C.,
A Spatio-Temporal Descriptor Based on 3D-Gradients,
BMVC08(xx-yy).
PDF File. 0809
BibRef

Marszalek, M.[Marcin], Laptev, I.[Ivan], Schmid, C.[Cordelia],
Actions in context,
CVPR09(2929-2936).
IEEE DOI 0906
See: See also Hollywood2 Human Actions and Scenes Dataset. BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Viewpoint invariant, View Invariant, Human Action Detection, Human Action Recognition .


Last update:Sep 18, 2017 at 11:34:11