16.7.4.7.1 Depth Based, Human Activity Recognition

Chapter Contents (Back)
Activity Recognition. Event Recognition. RGB-D. 3-D.

Kerola, T.[Tommi], Inoue, N.[Nakamasa], Shinoda, K.[Koichi],
Cross-view human action recognition from depth maps using spectral graph sequences,
CVIU(154), No. 1, 2017, pp. 108-126.
Elsevier DOI 1612
BibRef
And:
Spectral Graph Skeletons for 3D Action Recognition,
ACCV14(IV: 417-432).
Springer DOI 1504
Human action recognition BibRef

Aggarwal, J.K., Xia, L.[Lu],
Human activity recognition from 3D data: A review,
PRL(48), No. 1, 2014, pp. 70-80.
Elsevier DOI 1410
Computer vision BibRef

Xia, L.[Lu], Aggarwal, J.K.,
Spatio-temporal Depth Cuboid Similarity Feature for Activity Recognition Using Depth Camera,
CVPR13(2834-2841)
IEEE DOI 1309
Kinect; Spatio temporal interest point; activity recognition; depth image BibRef

Ke, S.R.[Shian-Ru], Thuc, H.L.U.U.[Hoang Le Uyen Uyen], Hwang, J.N.[Jenq-Neng], Yoo, J.H.[Jang-Hee], Choi, K.H.[Kyoung-Ho],
Human Action Recognition Based on 3D Human Modeling and Cyclic HMMs,
ETRI(26), No. 4, August 2014, pp. 662-672.
DOI Link 1410
BibRef

Mocanu, D.C.[Decebal Constantin], Ammar, H.B.[Haitham Bou], Lowet, D.[Dietwig], Driessens, K.[Kurt], Liotta, A.[Antonio], Weiss, G.[Gerhard], Tuyls, K.[Karl],
Factored four way conditional restricted Boltzmann machines for activity recognition,
PRL(66), No. 1, 2015, pp. 100-108.
Elsevier DOI 1511
Activity recognition BibRef

Mocanu, D.C.[Decebal Constantin], Ammar, H.B.[Haitham Bou], Puig, L.[Luis], Eaton, E.[Eric], Liotta, A.[Antonio],
Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines,
PR(69), No. 1, 2017, pp. 325-335.
Elsevier DOI 1706
Deep, learning BibRef

Wu, Y.X.[Yue-Xin], Jia, Z.[Zhe], Ming, Y.[Yue], Sun, J.J.[Juan-Juan], Cao, L.J.[Liu-Juan],
Human behavior recognition based on 3D features and hidden markov models,
SIViP(10), No. 3, March 2016, pp. 495-502.
Springer DOI 1602
BibRef

Jalal, A.[Ahmad], Kim, Y.H.[Yeon-Ho], Kim, Y.J.[Yong-Joong], Kamal, S.[Shaharyar], Kim, D.J.[Dai-Jin],
Robust human activity recognition from depth video using spatiotemporal multi-fused features,
PR(61), No. 1, 2017, pp. 295-308.
Elsevier DOI 1705
Human activity recognition BibRef

Hu, J.F.[Jian-Fang], Zheng, W.S.[Wei-Shi], Lai, J.H.[Jian-Huang], Zhang, J.G.[Jian-Guo],
Jointly Learning Heterogeneous Features for RGB-D Activity Recognition,
PAMI(39), No. 11, November 2017, pp. 2186-2200.
IEEE DOI 1710
BibRef
Earlier: CVPR15(5344-5352)
IEEE DOI 1510
Feature extraction, Image color analysis, Skeleton, Transforms, Visualization, Heterogeneous features learning, RGB-D activity recognition, action recognition BibRef

Hu, J.F.[Jian-Fang], Zheng, W.S.[Wei-Shi], Pan, J.[Jiahui], Lai, J.H.[Jian-Huang], Zhang, J.G.[Jian-Guo],
Deep Bilinear Learning for RGB-D Action Recognition,
ECCV18(VII: 346-362).
Springer DOI 1810
BibRef

Hu, N., Englebienne, G.[Gwenn], Lou, Z., Kröse, B.J.A.[Ben J.A.],
Learning to Recognize Human Activities Using Soft Labels,
PAMI(39), No. 10, October 2017, pp. 1973-1984.
IEEE DOI 1709
Data models, Labeling, Robots, Support vector machines, Training, Uncertainty, RGB-D perception, human activity recognition, max-margin learning BibRef


Dogan, E.[Emre], Eren, G.[Gonen], Wolf, C.[Christian], Baskurt, A.[Atilla],
Activity recognition with volume motion templates and histograms of 3D gradients,
ICIP15(4421-4425)
IEEE DOI 1512
HoG3D BibRef

Escalera, S.[Sergio],
Human Behavior Analysis from Depth Maps,
AMDO12(282-292).
Springer DOI 1208
BibRef

Hu, G.[Gang], Reilly, D.[Derek], Swinden, B.[Ben], Gao, Q.G.[Qi-Gang],
Human Activity Analysis in a 3D Bird's-eye View,
ICIAR14(II: 365-373).
Springer DOI 1410
BibRef

Liu, Z.C.[Zi-Cheng],
Human Activity Recognition with 2d and 3d Cameras,
CIARP12(37).
Springer DOI 1209
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Models, Inference, Learning Human Activities, Human Behavior .


Last update:May 2, 2021 at 12:04:43