17.1.2.2 Event Models, Action Models, Motion Detection for Events, Backgrounds

Allen, J.F.[James F.],
Maintaining Knowledge About Time Temporal Intervals,
CACM(26), 1983, pp. 832-842. BibRef 8300

Allen, J.F.[James F.],
Towards a General Theory of Action and Time,
AI(23), No. 2, July 1984, pp. 123-154.
Elsevier DOI BibRef 8407

Raiha, L.,
Approximate Sequence Comparison: A Study with Histograms,
PR(23), No. 1-2, 1990, pp. 159-169.
Elsevier DOI BibRef 9000

Haering, N.C.[Niels C.], da Vitoria Lobo, N.[Niels],
Visual Event Detection,
KluwerBoston, 2001. ISBN Number 0-7923-7436-3
Springer DOI Extract image descriptions to provide an internal description of the world. Process in a flat hierarchy. Deal with missing information and extra information. Buy this book: Visual Event Detection (The International Series in Video Computing) BibRef 0100

Joo, S.W.[Seong-Wook], Chellappa, R.[Rama],
A Multiple-Hypothesis Approach for Multiobject Visual Tracking,
IP(16), No. 11, November 2007, pp. 2849-2854.
IEEE DOI 0709
BibRef
Earlier:
Recognition of Multi-Object Events Using Attribute Grammars,
ICIP06(2897-2900).
IEEE DOI 0610
BibRef
And:
Attribute Grammar-Based Event Recognition and Anomaly Detection,
SLAM06(107).
IEEE DOI 0609
BibRef

Green, R.,
Spatially and Temporally Segmenting Movement to Recognize Actions,
HumMotBook08(9). 0802
BibRef

Cuntoor, N.P., Yegnanarayana, B., Chellappa, R.,
Activity Modeling Using Event Probability Sequences,
IP(17), No. 4, April 2008, pp. 594-607.
IEEE DOI 0803
BibRef

Cuntoor, N.P.[Naresh P.],
Event detection using multiple event probability sequences,
ICIP09(4321-4324).
IEEE DOI 0911
BibRef

Cuntoor, N.P.[Naresh P.], Chellappa, R.[Rama],
Epitomic Representation of Human Activities,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Abdelkader, M.F.[Mohamed F.], Roy-Chowdhury, A.K.[Amit K.], Chellappa, R.[Rama], Akdemir, U.[Umut],
Activity Representation Using 3D Shape Models,
JIVP(2008), No. 2008, pp. xx-yy.
DOI Link 0804
BibRef

Abdelkader, M.F.[Mohamed F.], Abd-Almageed, W.[Wael], Srivastava, A.[Anuj], Chellappa, R.[Rama],
Silhouette-based gesture and action recognition via modeling trajectories on Riemannian shape manifolds,
CVIU(115), No. 3, March 2011, pp. 439-455.
Elsevier DOI 1103
Gesture recognition; Action recognition; Riemannian manifolds; Shape space; Silhouette-based approaches BibRef

Sankaranarayanan, A.C.[Aswin C.], Patro, R.[Robert], Turaga, P.K.[Pavan K.], Varshney, A.[Amitabh], Chellappa, R.[Rama],
Modeling and Visualization of Human Activities for Multicamera Networks,
JIVP(2009), No. 2009, pp. xx-yy.
DOI Link 0911
BibRef

Bista, S.[Sujal], Leitão da Cunha, Í.L.[Ícaro Lins], Varshney, A.[Amitabh],
Kinetic depth images: flexible generation of depth perception,
VC(33), No. 10, October 2017, pp. 1357-136.
WWW Link. 1709
BibRef

Sankaranarayanan, A.C.[Aswin C.], Turaga, P.K.[Pavan K.], Chellappa, R.[Rama], Baraniuk, R.G.[Richard G.],
Compressive Acquisition of Linear Dynamical Systems,
SIIMS(6), No. 4, 2013, pp. 2109-2133.
DOI Link 1402
BibRef
Earlier: A1, A2, A4, A3:
Compressive Acquisition of Dynamic Scenes,
ECCV10(I: 129-142).
Springer DOI 1009
BibRef

Lohit, S.[Suhas], Wang, Q.[Qiao], Turaga, P.K.[Pavan K.],
Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping,
CVPR19(12418-12427).
IEEE DOI 2002
BibRef

Turaga, P.K.[Pavan K.], Chellappa, R.[Rama],
Locally time-invariant models of human activities using trajectories on the grassmannian,
CVPR09(2435-2441).
IEEE DOI 0906
BibRef

Wang, L.[Liang], Wang, Y.Z.[Yi-Zhou], Gao, W.[Wen],
Mining Layered Grammar Rules for Action Recognition,
IJCV(93), No. 2, June 2011, pp. 162-182.
WWW Link. 1104
BibRef

Wang, L.[Liang], Wang, Y.Z.[Yi-Zhou], Jiang, T.T.[Ting-Ting], Gao, W.[Wen],
Instantly telling what happens in a video sequence using simple features,
CVPR11(3257-3264).
IEEE DOI 1106
Recognize actions from a few frames. Use optical flow and edges. BibRef

Yu, G., Goussies, N.A., Yuan, J.S., Liu, Z.C.,
Fast Action Detection via Discriminative Random Forest Voting and Top-K Subvolume Search,
MultMed(13), No. 3, 2011, pp. 507-517.
IEEE DOI 1106
Find all action instances BibRef

Yu, G.[Gang], Yuan, J.S.[Jun-Song],
Fast action proposals for human action detection and search,
CVPR15(1302-1311)
IEEE DOI 1510
BibRef

Yu, G.[Gang], Yuan, J.S.[Jun-Song], Liu, Z.C.[Zi-Cheng],
Action Search by Example Using Randomized Visual Vocabularies,
IP(22), No. 1, January 2013, pp. 377-390.
IEEE DOI 1301

See also Human Action Recognition with Depth Cameras. BibRef
Earlier:
Unsupervised random forest indexing for fast action search,
CVPR11(865-872).
IEEE DOI 1106
BibRef

Zhang, L., Zeng, Z.[Zhi], Ji, Q.A.[Qi-Ang],
Probabilistic Image Modeling With an Extended Chain Graph for Human Activity Recognition and Image Segmentation,
IP(20), No. 9, September 2011, pp. 2401-2413.
IEEE DOI 1109
BibRef

Wang, X.Y.[Xiao-Yang], Ji, Q.A.[Qi-Ang],
Hierarchical Context Modeling for Video Event Recognition,
PAMI(39), No. 9, September 2017, pp. 1770-1782.
IEEE DOI 1708
BibRef
Earlier:
Video event recognition with deep hierarchical context model,
CVPR15(4418-4427)
IEEE DOI 1510
BibRef
Earlier:
A Hierarchical Context Model for Event Recognition in Surveillance Video,
CVPR14(2561-2568)
IEEE DOI 1409
BibRef
And:
A novel probabilistic approach utilizing clip attribute as hidden knowledge for event recognition,
ICPR12(3382-3385).
WWW Link. 1302
Context, Context modeling, Hidden Markov models, Image recognition, Semantics, Target recognition, Hierarchical context model, event recognition, image context, priming context, semantic, context BibRef

Wang, X.Y.[Xiao-Yang], Ji, Q.A.[Qi-Ang],
Context augmented Dynamic Bayesian Networks for event recognition,
PRL(43), No. 1, 2014, pp. 62-70.
Elsevier DOI 1404
BibRef
Earlier:
Incorporating contextual knowledge to Dynamic Bayesian Networks for event recognition,
ICPR12(3378-3381).
WWW Link. 1302
Award, ICPR. BibRef
And:
Learning dynamic Bayesian network discriminatively for human activity recognition,
ICPR12(3553-3556).
WWW Link. 1302
Context model BibRef

Nie, S.Q.[Si-Qi], Ji, Q.A.[Qi-Ang],
Capturing Global and Local Dynamics for Human Action Recognition,
ICPR14(1946-1951)
IEEE DOI 1412
Computational modeling BibRef

Zeng, Z.[Zhi], Ji, Q.A.[Qi-Ang],
Knowledge Based Activity Recognition with Dynamic Bayesian Network,
ECCV10(VI: 532-546).
Springer DOI 1009
BibRef

Merler, M., Huang, B., Xie, L.X., Hua, G., Natsev, A.P.,
Semantic Model Vectors for Complex Video Event Recognition,
MultMed(14), No. 1, January 2012, pp. 88-101.
IEEE DOI 1201
BibRef

Hospedales, T.M.[Timothy M.], Gong, S.G.[Shao-Gang], Xiang, T.[Tao],
Video Behaviour Mining Using a Dynamic Topic Model,
IJCV(98), No. 3, July 2012, pp. 303-323.
WWW Link. 1202
BibRef
Earlier:
A Markov Clustering Topic Model for Mining Behaviour in Video,
ICCV09(1165-1172).
IEEE DOI 0909
BibRef

Wang, H.R.[Hao-Ran], Yuan, C.F.[Chun-Feng], Hu, W.M.[Wei-Ming], Sun, C.Y.[Chang-Yin],
Supervised class-specific dictionary learning for sparse modeling in action recognition,
PR(45), No. 11, November 2012, pp. 3902-3911.
Elsevier DOI 1206
Compound feature; Motion segment; Sparse model; Supervised dictionary learning; Action recognition BibRef

Wang, H.R.[Hao-Ran], Yuan, C.F.[Chun-Feng], Luo, G.[Guan], Hu, W.M.[Wei-Ming], Sun, C.Y.[Chang-Yin],
Action recognition using linear dynamic systems,
PR(46), No. 6, June 2013, pp. 1710-1718.
Elsevier DOI 1302
Linear dynamic system; Kernel principal angle; Multiclass spectral clustering; Supervised codebook pruning; Action recognition BibRef

Wu, B.X.[Bao-Xin], Yuan, C.F.[Chun-Feng], Hu, W.M.[Wei-Ming],
Human Action Recognition Based on Context-Dependent Graph Kernels,
CVPR14(2609-2616)
IEEE DOI 1409
Human action recognition BibRef

Hu, W.M.[Wei-Ming], Wu, B.X.[Bao-Xin], Wang, P., Yuan, C.F.[Chun-Feng], Li, Y., Maybank, S.J.[Stephen J.],
Context-Dependent Random Walk Graph Kernels and Tree Pattern Graph Matching Kernels With Applications to Action Recognition,
IP(27), No. 10, October 2018, pp. 5060-5075.
IEEE DOI 1808
feature extraction, image matching, learning (artificial intelligence), quadratic programming, tree patterns BibRef

Yuan, C.F.[Chun-Feng], Wu, B.X.[Bao-Xin], Li, X.[Xi], Hu, W.M.[Wei-Ming], Maybank, S.J.[Stephen J.], Wang, F.S.[Fang-Shi],
Fusing R Features and Local Features with Context-Aware Kernels for Action Recognition,
IJCV(118), No. 2, June 2016, pp. 151-171.
Springer DOI 1606
BibRef

Wu, B.X.[Bao-Xin], Yang, S.[Shuang], Yuan, C.F.[Chun-Feng], Hu, W.M.[Wei-Ming], Wang, F.S.[Fang-Shi],
Human Action Recognition Based on Oriented Motion Salient Regions,
Gait14(I: 113-128).
Springer DOI 1504
BibRef

Zhu, P.F.[Peng-Fei], Hu, W.M.[Wei-Ming], Yuan, C.F.[Chun-Feng], Li, L.[Li],
Prototype Learning Using Metric Learning Based Behavior Recognition,
ICPR10(2604-2607).
IEEE DOI 1008
BibRef

Yang, S.[Shuang], Yuan, C.F.[Chun-Feng], Hu, W.M.[Wei-Ming], Ding, X.M.[Xin-Miao],
A Hierarchical Model Based on Latent Dirichlet Allocation for Action Recognition,
ICPR14(2613-2618)
IEEE DOI 1412
Accuracy BibRef

Yuan, C.F.[Chun-Feng], Hu, W.M.[Wei-Ming], Tian, G.D.[Guo-Dong], Yang, S.[Shuang], Wang, H.R.[Hao-Ran],
Multi-task Sparse Learning with Beta Process Prior for Action Recognition,
CVPR13(423-429)
IEEE DOI 1309
BibRef

Yuan, C.F.[Chun-Feng], Li, X.[Xi], Hu, W.M.[Wei-Ming], Wang, H.Z.[Han-Zi],
Human Action Recognition Using Pyramid Vocabulary Tree,
ACCV09(III: 527-537).
Springer DOI 0909
BibRef

Guo, K.[Kai], Ishwar, P.[Prakash], Konrad, J.[Janusz],
Action Recognition From Video Using Feature Covariance Matrices,
IP(22), No. 6, 2013, pp. 2479-2494.
IEEE DOI 1307
BibRef
Earlier:
Action Recognition in Video by Sparse Representation on Covariance Manifolds of Silhouette Tunnels,
ICPR-Contests10(294-305).
Springer DOI 1008
BibRef
And:
Action Recognition Using Sparse Representation on Covariance Manifolds of Optical Flow,
AVSS10(188-195).
IEEE DOI 1009
image recognition; supervised learning methods; Action recognition; nearest-neighbor (NN) classifier; optical flow BibRef

Chen, J.W.[Jia-Wei], Wu, Q.M.J.[Q.M. Jonathan], Konrad, J.[Janusz], Ishwar, P.[Prakash],
Semi-Coupled Two-Stream Fusion ConvNets for Action Recognition at Extremely Low Resolutions,
WACV17(139-147)
IEEE DOI 1609
Context, Fuses, Image resolution, Optical imaging, Testing, Training, Videos BibRef

Goudelis, G.[Georgios], Karpouzis, K.[Konstantinos], Kollias, S.[Stefanos],
Exploring trace transform for robust human action recognition,
PR(46), No. 12, 2013, pp. 3238-3248.
Elsevier DOI 1308
Human action recognition BibRef

Tzouvaras, V., Tsechpenakis, G., Stamou, G., Kollias, S.,
Adaptive rule-based recognition of events in video sequences,
ICIP03(II: 607-610).
IEEE DOI 0312
BibRef

Nguyen, T.P.[Thanh Phuong], Manzanera, A.[Antoine],
Motion Trend Patterns for Action Modelling and Recognition,
CAIP13(360-367).
Springer DOI 1308
trajectory from dense point tracking and Local Binary Patterns. BibRef

Agustí, P.[Pau], Traver, V.J.[V. Javier], Pla, F.[Filiberto],
Bag-of-words with aggregated temporal pair-wise word co-occurrence for human action recognition,
PRL(49), No. 1, 2014, pp. 224-230.
Elsevier DOI 1410
BibRef
Earlier:
Characterizing Actions with Local Descriptors Based on Kinematics and Flow Recurrences,
IbPRIA13(322-329).
Springer DOI 1307
Bag-of-words BibRef

Agustí, P.[Pau], Traver, V.J.[V. Javier], Marin-Jimenez, M.J.[Manuel J.], Pla, F.[Filiberto],
Exploring Alternative Spatial and Temporal Dense Representations for Action Recognition,
CAIP11(II: 364-371).
Springer DOI 1109
BibRef

Bloom, V.[Victoria], Argyriou, V.[Vasileios], Makris, D.[Dimitrios],
Hierarchical transfer learning for online recognition of compound actions,
CVIU(144), No. 1, 2016, pp. 62-72.
Elsevier DOI 1604
Online action recognition BibRef
Earlier: A1, A3, A2:
Clustered Spatio-temporal Manifolds for Online Action Recognition,
ICPR14(3963-3968)
IEEE DOI 1412
Accuracy BibRef

Kotsia, I.[Irene], Argyriou, V.[Vasileios],
Action spotting exploiting the frequency domain,
CVCG11(43-48).
IEEE DOI 1106
BibRef

Rodriguez, M.[Mario], Orrite, C.[Carlos], Medrano, C.[Carlos], Makris, D.[Dimitrios],
A Time Flexible Kernel framework for video-based activity recognition,
IVC(48-49), No. 1, 2016, pp. 26-36.
Elsevier DOI 1604
Activity recognition BibRef

Rodriguez, M.[Mario], Orrite-Urunuela, C.[Carlos], Medrano, C.[Carlos], Makris, D.[Dimitrios],
One-Shot Learning of Human Activity With an MAP Adapted GMM and Simplex-HMM,
Cyber(47), No. 7, July 2017, pp. 1769-1780.
IEEE DOI 1706
BibRef
And:
Fast Simplex-HMM for One-Shot Learning Activity Recognition,
ActionCh17(1259-1266)
IEEE DOI 1709
Activity recognition, Feature extraction, Mathematical model. Adaptation models, Encoding, Feature extraction, Hidden Markov models, Training, Videos, Vocabulary, Activity recognition, hidden Markov model (HMM), maximum a posteriori (MAP) adaptation, soft-assignment, transfer, learning BibRef

Rodriguez, M.[Mario], Orrite, C.[Carlos], Medrano, C.[Carlos],
Space-Time Flexible Kernel for Recognizing Activities from Wearable Cameras,
IbPRIA17(511-518).
Springer DOI 1706
BibRef

Bilen, H.[Hakan], Fernando, B.[Basura], Gavves, E.[Efstratios], Vedaldi, A.[Andrea],
Action Recognition with Dynamic Image Networks,
PAMI(40), No. 12, December 2018, pp. 2799-2813.
IEEE DOI 1811
Convolutional neural networks, Neural networks, Video sequences, Optical imaging, Streaming media, Image classification, convolutional neural networks BibRef

Fernando, B.[Basura], Chet, C.T.Y.[C. T. Yin], Bilen, H.[Hakan],
Weakly Supervised Gaussian Networks for Action Detection,
WACV20(526-535)
IEEE DOI 2006
Videos, Training, Predictive models, Benchmark testing, Task analysis, Neural networks, Image segmentation BibRef

Bilen, H.[Hakan], Fernando, B.[Basura], Gavves, E.[Efstratios], Vedaldi, A.[Andrea], Gould, S.[Stephen],
Dynamic Image Networks for Action Recognition,
CVPR16(3034-3042)
IEEE DOI 1612
BibRef

Shi, Y.[Yuge], Fernando, B.[Basura], Hartley, R.I.[Richard I.],
Action Anticipation with RBF Kernelized Feature Mapping RNN,
ECCV18(X: 305-322).
Springer DOI 1810
BibRef

Fernando, B.[Basura], Shirazi, S., Gould, S.[Stephen],
Unsupervised Human Action Detection by Action Matching,
MotionRep17(1604-1612)
IEEE DOI 1709
Encoding, Feature extraction, Video sequences, Videos BibRef

Guo, D.S.[Da-Shan], Li, W.[Wei], Fang, X.Z.[Xiang-Zhong],
Fully Convolutional Network for Multiscale Temporal Action Proposals,
MultMed(20), No. 12, December 2018, pp. 3428-3438.
IEEE DOI 1812
feature extraction, feedforward neural nets, gesture recognition, image motion analysis, image retrieval, image segmentation, duration regression BibRef

Zhu, Y.S.[Yi-Sheng], Liu, G.C.[Guang-Can],
Fine-grained action recognition using multi-view attentions,
VC(36), No. 9, September 2020, pp. 1771-1781.
Springer DOI 2008
Inflated 3D ConvNet. Add multi-view attention to look for details. BibRef

Wang, X.L.[Xiao-Long], Farhadi, A.[Ali], Gupta, A.[Abhinav],
Actions ~ Transformations,
CVPR16(2658-2667)
IEEE DOI 1612
Action as transformation on high-level feature space. BibRef

Nagel, M.[Markus], Mensink, T.[Thomas], Snoek, C.G.M.[Cees G. M.],
Event Fisher Vectors: Robust Encoding Visual Diversity of Visual Streams,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Tran, T.H.[Thanh-Hai], Nguyen, V.T.[Van-Toi],
How Good Is Kernel Descriptor on Depth Motion Map for Action Recognition,
CVS15(137-146).
Springer DOI 1507
BibRef

Liang, Z.L.[Zhuo-Lin], Inoue, N.[Nakamasa], Shinoda, K.[Koichi],
Event Detection by Velocity Pyramid,
MMMod14(I: 353-364).
Springer DOI 1405
BibRef

Wang, Y.[Yuwang], Wang, B.Y.[Bao-Yuan], Yu, Y.Z.[Yi-Zhou], Dai, Q.H.[Qiong-Hai], Tu, Z.W.[Zhuo-Wen],
Action-Gons: Action Recognition with a Discriminative Dictionary of Structured Elements with Varying Granularity,
ACCV14(V: 259-274).
Springer DOI 1504
BibRef

Zhu, J.[Jun], Wang, B.Y.[Bao-Yuan], Yang, X.K.[Xiao-Kang], Zhang, W.J.[Wen-Jun], Tu, Z.W.[Zhuo-Wen],
Action Recognition with Actons,
ICCV13(3559-3566)
IEEE DOI 1403
BibRef

Vahdat, A.[Arash], Cannons, K.[Kevin], Mori, G.[Greg], Oh, S.[Sangmin], Kim, I.[Ilseo],
Compositional Models for Video Event Detection: A Multiple Kernel Learning Latent Variable Approach,
ICCV13(1185-1192)
IEEE DOI 1403
BibRef

Sakla, W.,
Action classification in polarimetric infrared imagery via diffusion maps,
AIPR12(1-8)
IEEE DOI 1307
data reduction BibRef

Israel, S.A.,
Toward a common lexicon for exploiting activity data,
AIPR12(1-6)
IEEE DOI 1307
pattern recognition BibRef

Natarajan, P.[Pradeep], Wu, S.[Shuang], Vitaladevuni, S.[Shiv], Zhuang, X.D.[Xiao-Dan], Park, U.S.[Un-Sang], Prasad, R.[Rohit], Natarajan, P.[Premkumar],
Multi-channel Shape-Flow Kernel Descriptors for Robust Video Event Detection and Retrieval,
ECCV12(II: 301-314).
Springer DOI 1210
BibRef

Ar, I.[Ilktan], Akgul, Y.S.[Yusuf Sinan],
A Framework for Combined Recognition of Actions and Objects,
ICCVG12(264-271).
Springer DOI 1210
BibRef

Zhou, Q.A.[Qi-Ang], Wang, G.[Gang],
Atomic Action Features: A New Feature for Action Recognition,
VECTaR12(I: 291-300).
Springer DOI 1210
BibRef

Jagadeesh, V.[Vignesh], Manjunath, B.S., Anderson, J.[James], Jones, B.[Bryan], Marc, R.[Robert], Fisher, S.K.[Steven K.],
Online parameter estimation in dynamic Markov Random Fields for image sequence analysis,
ICIP12(301-304).
IEEE DOI 1302
BibRef

Jagadeesh, V.[Vignesh], Karthikeyan, S., Manjunath, B.S.,
Spatio-temporal optical flow statistics (STOFS) for activity classification,
ICCVGIP10(178-182).
DOI Link 1111
BibRef

Wang, Y.[Yang], Wu, L.[Lin], Huang, X.D.[Xiao-Di],
Action recognition using tri-view constraints,
AVSBS11(107-112).
IEEE DOI 1111
BibRef

Bartocci, D.[Daniele], Ferretti, M.[Marco],
Handling Complex Events in Surveillance Tasks,
CIAP11(II: 99-108).
Springer DOI 1109
BibRef

Bourdev, L.[Lubomir], Maji, S.[Subhransu], Malik, J.[Jitendra],
Describing people: A poselet-based approach to attribute classification,
ICCV11(1543-1550).
IEEE DOI 1201
BibRef
Earlier: A2, A1, A3:
Action recognition from a distributed representation of pose and appearance,
CVPR11(3177-3184).
IEEE DOI 1106
BibRef

Le, Q.V.[Quoc V.], Zou, W.Y.[Will Y.], Yeung, S.Y.[Serena Y.], Ng, A.Y.[Andrew Y.],
Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis,
CVPR11(3361-3368).
IEEE DOI 1106
BibRef

Wang, J.[Jiang], Chen, Z.Y.[Zhuo-Yuan], Wu, Y.[Ying],
Action recognition with multiscale spatio-temporal contexts,
CVPR11(3185-3192).
IEEE DOI 1106
BibRef

Kwak, S.[Suha], Han, B.H.[Bo-Hyung], Han, J.H.[Joon Hee],
Scenario-based video event recognition by constraint flow,
CVPR11(3345-3352).
IEEE DOI 1106
BibRef

Brendel, W.[William], Fern, A.[Alan], Todorovic, S.[Sinisa],
Probabilistic event logic for interval-based event recognition,
CVPR11(3329-3336).
IEEE DOI 1106
BibRef

Wang, C.H.[Chun-Hao], Wang, Y.J.[Yong-Jin], Guan, L.[Ling],
Event Detection and Recognition using Histogram of Oriented Gradients and Hidden Markov Models,
ICIAR11(I: 436-445).
Springer DOI 1106
BibRef

Matern, D.[Dierck], Condurache, A.P.[Alexandru Paul], Mertins, A.[Alfred],
Linear Prediction Based Mixture Models for Event Detection in Video Sequences,
IbPRIA11(25-32).
Springer DOI 1106
BibRef

Crispim-Junior, C.F.[Carlos Fernando], Bremond, F.[Francois],
Uncertainty Modeling Framework for Constraint-Based Elementary Scenario Detection in Vision Systems,
CVONT14(269-282).
Springer DOI 1504
BibRef

Romdhane, R.[Rim], Crispim, C.F.[Carlos Fernando], Bremond, F.[Francois], Thonnat, M.[Monique],
Activity recognition and uncertain knowledge in video scenes,
AVSS13(377-382)
IEEE DOI 1311
Bayes methods BibRef

Romdhane, R.[Rim], Boulay, B.[Bernard], Bremond, F.[Francois], Thonnat, M.[Monique],
Probabilistic Recognition of Complex Event,
CVS11(122-131).
Springer DOI 1109
BibRef
Earlier: A1, A3, A4, Only:
A Framework Dealing with Uncertainty for Complex Event Recognition,
AVSS10(392-399).
IEEE DOI 1009
BibRef

Zaidenberg, S.[Sofia], Boulay, B.[Bernard], Bremond, F.[Francois],
A Generic Framework for Video Understanding Applied to Group Behavior Recognition,
AVSS12(136-142).
IEEE DOI 1211
BibRef

Kieran, D., Yan, W.Q.[Wei-Qi],
A Framework for an Event Driven Video Surveillance System,
AVSS10(97-102).
IEEE DOI 1009
BibRef

Matsukawa, T.[Tetsu], Kurita, T.[Takio],
Action Recognition Using Three-Way Cross-Correlations Feature of Local Moton Attributes,
ICPR10(1731-1734).
IEEE DOI 1008
BibRef

Messing, R.[Ross], Pal, C.[Chris], Kautz, H.[Henry],
Activity recognition using the velocity histories of tracked keypoints,
ICCV09(104-111).
IEEE DOI 0909
BibRef

Kovacs, L.[Levente], Utasi, Á.[Ákos], Szlavik, Z.[Zoltán], Havasi, L.[László], Petras, I.[István], Sziranyi, T.[Tamás],
Digital Video Event Detector Framework for Surveillance Applications,
AVSBS09(565-570).
IEEE DOI 0909
BibRef

Mattivi, R.[Riccardo], Shao, L.[Ling],
Human Action Recognition Using LBP-TOP as Sparse Spatio-Temporal Feature Descriptor,
CAIP09(740-747).
Springer DOI 0909
Local Binary Pattern on Three Orthogonal Planes. BibRef

Hatun, K.[Kardelen], Duygulu, P.[Pinar],
Pose sentences: A new representation for action recognition using sequence of pose words,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Patron-Perez, A.[Alonso], Sommerlade, E.[Eric], Reid, I.D.[Ian D.],
Action recognition using shared motion parts,
VS08(xx-yy). 0810

See also Modelling pedestrian trajectory patterns with Gaussian processes. BibRef

Sommerlade, E.[Eric], Reid, I.D.[Ian D.],
Cooperative Surveillance of Multiple Targets using Mutual Information,
M2SFA208(xx-yy). 0810
BibRef

Tran, S.D.[Son D.], Davis, L.S.[Larry S.],
Event Modeling and Recognition Using Markov Logic Networks,
ECCV08(II: 610-623).
Springer DOI 0810
BibRef

Wang, Z.X.[Zheng-Xiang], Hu, Y.Q.[Yi-Qun], Chia, L.T.[Liang-Tien],
Image-to-Class Distance Metric Learning for Image Classification,
ECCV10(I: 706-719).
Springer DOI 1009
BibRef
And:
Multi-label learning by Image-to-Class distance for scene classification and image annotation,
CIVR10(105-112).
DOI Link 1007
BibRef
Earlier:
Learning instance-to-class distance for human action recognition,
ICIP09(3545-3548).
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Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Detecting Anomalies, Abnormal Event, Abnormal Behavior, or Rare Events, Rare Behaviors .