17.1.3.6.9 Incremental Learning for Human Action Recognition

Chapter Contents (Back)
Action Recognition. Human Actions. Learning. Neural Networks. Incremental Learning. CNN.
See also Neural Networks and Learning for Human Action Recognition and Detection.
See also Human Action Detection, Human Action Recognition.

Wu, X.X.[Xin-Xiao], Jia, Y.D.[Yun-De], Liang, W.[Wei],
Incremental discriminant-analysis of canonical correlations for action recognition,
PR(43), No. 12, December 2010, pp. 4190-4197.
Elsevier DOI 1003
BibRef
Earlier: A1, A3, A2:
Incremental discriminative-analysis of canonical correlations for action recognition,
ICCV09(2035-2041).
IEEE DOI 0909
Human action recognition; Incremental discriminant-analysis; Computer vision BibRef

Zhang, L.[Lei], Zhen, X.T.[Xian-Tong], Shao, L.[Ling],
Learning Object-to-Class Kernels for Scene Classification,
IP(23), No. 8, August 2014, pp. 3241-3253.
IEEE DOI 1408
BibRef
And:
High order co-occurrence of visualwords for action recognition,
ICIP12(757-760).
IEEE DOI 1302
image classification BibRef

Zhang, L.[Lei], Shum, H.P.H.[H. P. H.], Shao, L.[Ling],
Manifold Regularized Experimental Design for Active Learning,
IP(26), No. 2, February 2017, pp. 969-981.
IEEE DOI 1702
design of experiments BibRef

Zhang, L.[Lei], Xie, S.Z.[Shou-Zhi], Zhen, X.T.[Xian-Tong],
Discriminative high-level representations for scene classification,
ICIP13(4345-4348)
IEEE DOI 1402
High-level representation BibRef

Tang, J.[Jun], Shao, L.[Ling], Zhen, X.T.[Xian-Tong],
Human Action Retrieval via efficient feature matching,
AVSS13(306-311)
IEEE DOI 1311
content-based retrieval. Finding videos of the same actions. BibRef

Chen, C.Y.[Chao-Yeh], Grauman, K.[Kristen],
Efficient Activity Detection in Untrimmed Video with Max-Subgraph Search,
PAMI(39), No. 5, May 2017, pp. 908-921.
IEEE DOI 1704
BibRef
Earlier:
Watching Unlabeled Video Helps Learn New Human Actions from Very Few Labeled Snapshots,
CVPR13(572-579)
IEEE DOI 1309
BibRef
And:
Efficient activity detection with max-subgraph search,
CVPR12(1274-1281).
IEEE DOI 1208
Detectors. BibRef

Bandla, S.I.[Sun-Il], Grauman, K.[Kristen],
Active Learning of an Action Detector from Untrimmed Videos,
ICCV13(1833-1840)
IEEE DOI 1403
action detection BibRef

Ali, S.[Samr], Bouguila, N.[Nizar],
Multimodal action recognition using variational-based Beta-Liouville hidden Markov models,
IET-IPR(14), No. 17, 24 December 2020, pp. 4785-4794.
DOI Link 2104
BibRef
Earlier:
Online Learning for Beta-Liouville Hidden Markov Models: Incremental Variational Learning for Video Surveillance and Action Recognition,
ICIP20(3249-3253)
IEEE DOI 2011
Hidden Markov models, Surveillance, Mathematical model, Data models, Training, Adaptation models, Hidden Markov Models, Variational Learning BibRef

Najar, F.[Fatma], Bouguila, N.[Nizar],
Image Categorization Using Agglomerative Clustering Based Smoothed Dirichlet Mixtures,
ISVC20(II:27-38).
Springer DOI 2103
BibRef

Najar, F.[Fatma], Bourouis, S.[Sami], Zaguia, A.[Atef], Bouguila, N.[Nizar], Belghith, S.[Safya],
Unsupervised Human Action Categorization Using a Riemannian Averaged Fixed-Point Learning of Multivariate GGMM,
ICIAR18(408-415).
Springer DOI 1807
BibRef

Gutoski, M.[Matheus], Lazzaretti, A.E.[André Eugenio], Lopes, H.S.[Heitor Silvério],
Incremental human action recognition with dual memory,
IVC(116), 2021, pp. 104313.
Elsevier DOI 2112
Incremental learning, Human Action Recognition, Metric Learning, Triplet Networks, Dual-memory Extreme Value Machine BibRef


Park, J.[Jaeyoo], Kang, M.S.[Min-Soo], Han, B.H.[Bo-Hyung],
Class-Incremental Learning for Action Recognition in Videos,
ICCV21(13678-13687)
IEEE DOI 2203
Learning systems, Image recognition, Benchmark testing, Linear programming, Task analysis, Standards, Video analysis and understanding BibRef

Ma, J.W.[Jia-Wei], Tao, X.Y.[Xiao-Yu], Ma, J.X.[Jian-Xing], Hong, X.P.[Xiao-Peng], Gong, Y.H.[Yi-Hong],
Class Incremental Learning for Video Action Classification,
ICIP21(504-508)
IEEE DOI 2201
Manifolds, Neurons, Machine learning, Feature extraction, Object recognition, Task analysis, Class Incremental Learning, Grow When Required network BibRef

Khoshrou, S.[Samaneh], Cardoso, J.S.[Jaime S.], Granger, E.[Eric], Teixeira, L.F.[Luís F.],
Spatio-Temporal Fusion for Learning of Regions of Interests Over Multiple Video Streams,
ISVC15(II: 509-520).
Springer DOI 1601
BibRef
Earlier: A1, A2, A4, Only:
Active Learning from Video Streams in a Multi-camera Scenario,
ICPR14(1248-1253)
IEEE DOI 1412
Accuracy BibRef

Liu, X.H.[Xiang-Hang], Zhang, J.[Jian],
Active learning for human action recognition with Gaussian Processes,
ICIP11(3253-3256).
IEEE DOI 1201
BibRef

Xu, J.[Jie], Ye, G.[Getian], Wang, Y.[Yang], Wang, W.[Wei], Yang, J.[Jun],
Online Learning for PLSA-Based Visual Recognition,
ACCV10(II: 95-108).
Springer DOI 1011
BibRef

Xu, J.[Jie], Ye, G.[Getian], Wang, Y.[Yang], Herman, G.[Gunawan], Zhang, B.[Bang], Yang, J.[Jun],
Incremental EM for Probabilistic Latent Semantic Analysis on Human Action Recognition,
AVSBS09(55-60).
IEEE DOI 0909
BibRef

Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Convolutional Neural Networks for Human Action Recognition and Detection .


Last update:Apr 27, 2024 at 11:46:35