16.7.4.7 Human Activity Recognition, Human Behaviors

Chapter Contents (Back)
Activity Recognition. Event Recognition. Generally more an extended activity rather than a basic action. See also Human Action Detection, Human Action Recognition. See also Models, Inference, Learning Human Activities, Human Behavior.

Stauffer, C.[Chris], Grimson, W.E.L.[W. Eric L.],
Learning Patterns of Activity Using Real-Time Tracking,
PAMI(22), No. 8, August 2000, pp. 747-757.
IEEE DOI 0010
Using the 24 hour data from tracking motion, learn the different patterns, especially to see things that don't fit. Motion segmentation uses adaptive background subtraction with an updated model. Objects are not recognized, but identity is maintained throught the track. BibRef

Stauffer, C.[Chris],
Automated Audio-visual Activity Analysis,
CSAIL-2005-057, September 2005.
WWW Link. BibRef 0509

Gong, S.G.[Shao-Gang], Ng, J.[Jeffrey], Sherrah, J.[Jamie],
On the semantics of visual behaviour, structured events and trajectories of human action,
IVC(20), No. 12, October 2002, pp. 873-888.
WWW Link. 0210
BibRef

Ng, J., Gong, S.G.[Shao-Gang],
On the binding mechanism of synchronised visual events,
Motion02(112-117).
IEEE DOI 0303
BibRef

Robertson, N.M.[Neil M.], Reid, I.D.[Ian D.],
A general method for human activity recognition in video,
CVIU(103), No. 2-3, November-December 2006, pp. 232-248.
WWW Link. 0611
BibRef
Earlier:
Behaviour Understanding in Video: A Combined Method,
ICCV05(I: 808-815).
IEEE DOI 0510
Visual surveillance; Human activity recognition; Video annotation BibRef

Robertson, N.M.[Neil M.], Reid, I.D.[Ian D.],
Automatic Reasoning about Causal Events in Surveillance Video,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1103
BibRef

Hsieh, J.W.[Jun-Wei], Hsu, Y.T.[Yung-Tai],
Boosted string representation and its application to video surveillance,
PR(41), No. 10, October 2008, pp. 3078-3091.
WWW Link. 0808
Behavior analysis; Centroid contexts; String matching; Boosting algorithm BibRef

Lin, W., Sun, M.T., Poovendran, R., Zhang, Z.,
Activity Recognition Using a Combination of Category Components and Local Models for Video Surveillance,
CirSysVideo(18), No. 8, August 2008, pp. 1128-1139.
IEEE DOI 0809
See also Group Event Detection With a Varying Number of Group Members for Video Surveillance. BibRef

Shen, J., Tao, D., Li, X.,
Modality Mixture Projections for Semantic Video Event Detection,
CirSysVideo(18), No. 11, November 2008, pp. 1587-1596.
IEEE DOI 0811
BibRef

Duong, T.V.[Thi V.], Phung, D.Q.[Dinh Q.], Bui, H.H.[Hung H.], Venkatesh, S.[Svetha],
Efficient duration and hierarchical modeling for human activity recognition,
AI(173), No. 7-8, May 2009, pp. 830-856.
Elsevier DOI 0904
Duration modeling; Coxian; Hidden semi-Markov model; Human activity recognition; Smart surveillance BibRef

Kim, Y., Ling, H.,
Human Activity Classification Based on Micro-Doppler Signatures Using a Support Vector Machine,
GeoRS(47), No. 5, May 2009, pp. 1328-1337.
IEEE DOI 0904
BibRef

Gupta, A.[Abhinav], Kembhavi, A.[Aniruddha], Davis, L.S.[Larry S.],
Observing Human-Object Interactions: Using Spatial and Functional Compatibility for Recognition,
PAMI(31), No. 10, October 2009, pp. 1775-1789.
IEEE DOI 0909
Understand events, recognize motions, recognize the objects. Apply constraints to reduce computation. BibRef

Qian, H.M.[Hui-Min], Mao, Y.B.[Yao-Bin], Xiang, W.B.[Wen-Bo], Wang, Z.Q.[Zhi-Quan],
Recognition of human activities using SVM multi-class classifier,
PRL(31), No. 2, 15 January 2010, pp. 100-111.
Elsevier DOI 1001
Human activity recognition; Background subtraction; CCMEI; Support vector machine; Decision tree classifier BibRef

Filipovych, R.[Roman], Ribeiro, E.[Eraldo],
Robust sequence alignment for actor-object interaction recognition: Discovering actor-object states,
CVIU(115), No. 2, February 2011, pp. 177-193.
Elsevier DOI 1102
BibRef
Earlier:
Recognizing primitive interactions by exploring actor-object states,
CVPR08(1-7).
IEEE DOI 0806
Activity analysis; Human-object interaction; Sequence matching; Dynamic programming BibRef

Filipovych, R.[Roman], Ribeiro, E.[Eraldo],
Learning Structural Models in Multiple Projection Spaces,
ICIAR09(616-626).
Springer DOI 0907
BibRef
Earlier:
Learning human motion models from unsegmented videos,
CVPR08(1-7).
IEEE DOI 0806
BibRef
Earlier:
Combining Models of Pose and Dynamics for Human Motion Recognition,
ISVC07(II: 21-32).
Springer DOI 0711
BibRef
And:
Learning Repetitive Patterns for Classifying Non-Rigidly Deforming Texture Surfaces,
CIAP07(49-54).
IEEE DOI 0709
BibRef
And:
Learning Basic Patterns from Repetitive Texture Surfaces Under Non-rigid Deformations,
ICIAR07(81-92).
Springer DOI 0708
BibRef

Filipovych, R.[Roman], Ribeiro, E.[Eraldo],
Adaptive Tuboid Shapes for Action Recognition,
ISVC09(II: 367-376).
Springer DOI 0911
BibRef

Filipovych, R.[Roman], Ribeiro, E.[Eraldo],
Determining the scale of interest regions in videos,
ICIP09(985-988).
IEEE DOI 0911
BibRef

Benabbas, Y.[Yassine], Ihaddadene, N.[Nacim], Djeraba, C.[Chaabane],
Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1103
BibRef

Benabbas, Y.[Yassine], Lablack, A.[Adel], Ihaddadene, N.[Nacim], Djeraba, C.[Chabane],
Action Recognition Using Direction Models of Motion,
ICPR10(4295-4298).
IEEE DOI 1008
BibRef

Siirtola, P.[Pekka], Koskimäki, H.[Heli], Huikari, V.[Ville], Laurinen, P.[Perttu], Röning, J.[Juha],
Improving the classification accuracy of streaming data using SAX similarity features,
PRL(32), No. 13, 1 October 2011, pp. 1659-1668.
Elsevier DOI 1109
Activity recognition; Classification; Symbolic dynamics; SAX BibRef

Hospedales, T.M.[Timothy M.], Li, J.[Jian], Gong, S.G.[Shao-Gang], Xiang, T.[Tao],
Identifying Rare and Subtle Behaviors: A Weakly Supervised Joint Topic Model,
PAMI(33), No. 12, December 2011, pp. 2451-2464.
IEEE DOI 1110
Identify rare event, e.g. dangerous or illegal activities have few prior examples. BibRef

Bregonzio, M.[Matteo], Li, J.[Jian], Gong, S.G.[Shao-Gang], Xiang, T.[Tao],
Discriminative Topics Modelling for Action Feature Selection and Recognition,
BMVC10(xx-yy).
HTML Version. 1009
BibRef

Bregonzio, M.[Matteo], Gong, S.G.[Shao-Gang], Xiang, T.[Tao],
Recognising action as clouds of space-time interest points,
CVPR09(1948-1955).
IEEE DOI 0906
BibRef

Ferrari, L.[Laura], Mamei, M.[Marco],
Discovering City Dynamics through Sports Tracking Applications,
Computer(44), No. 12, December 2011, pp. 63-68.
IEEE DOI 1112
Tracking data from the phone directly. BibRef

Iosifidis, A.[Alexandros], Tefas, A.[Anastasios], Nikolaidis, N.[Nikolaos], Pitas, I.[Ioannis],
Multi-View Human Movement Recognition Based on Fuzzy Distances and Linear Discriminant Analysis,
CVIU(116), No. 3, March 2012, pp. 347-360.
Elsevier DOI 1201
Activity recognition; Multi-view dynemes; Fuzzy vector quantization; Linear discriminant analysis See also Combining Fuzzy Vector Quantization With Linear Discriminant Analysis for Continuous Human Movement Recognition. BibRef

Iosifidis, A.[Alexandros], Tefas, A.[Anastasios], Pitas, I.[Ioannis], Gabbouj, M.[Moncef],
Big Media Data Analysis,
SP:IC(59), No. 1, 2017, pp. 105-108.
Elsevier DOI 1711
Big Media Data. BibRef

Cao, G., Iosifidis, A.[Alexandros], Gabbouj, M.,
Multi-View Nonparametric Discriminant Analysis for Image Retrieval and Recognition,
SPLetters(24), No. 10, October 2017, pp. 1537-1541.
IEEE DOI 1710
Gaussian distribution, image retrieval, nonparametric statistics, optimisation, Gaussian distribution assumption, multiview class structures, optimization criterion, zero-shot recognition, Gaussian distribution, Laplace equations, BibRef

Iosifidis, A.[Alexandros], Tefas, A.[Anastasios], Pitas, I.[Ioannis], Iosifidis, A., Tefas, A., Pitas, I.,
Class-Specific Reference Discriminant Analysis With Application in Human Behavior Analysis,
HMS(45), No. 3, June 2015, pp. 315-326.
IEEE DOI 1506
Face recognition See also Multi-View Human Movement Recognition Based on Fuzzy Distances and Linear Discriminant Analysis. BibRef

Iosifidis, A.[Alexandros], Tefas, A.[Anastastios], Pitas, I.[Ioannis],
Kernel Reference Discriminant Analysis,
PRL(49), No. 1, 2014, pp. 85-91.
Elsevier DOI 1410
Kernel Discriminant Analysis BibRef

Iosifidis, A.[Alexandros], Tefas, A.[Anastasios], Pitas, I.[Ioannis],
Semi-supervised Classification of Human Actions Based on Neural Networks,
ICPR14(1336-1341)
IEEE DOI 1412
Accuracy;Databases;Neurons;Optimization;Training;Training data;Vectors BibRef

Holte, M.B., Moeslund, T.B., Nikolaidis, N., Pitas, I.,
3D Human Action Recognition for Multi-view Camera Systems,
3DIMPVT11(342-349).
IEEE DOI 1109
BibRef

Kapsouras, I.[Ioannis], Nikolaidis, N.[Nikos],
Action recognition on motion capture data using a dynemes and forward differences representation,
JVCIR(25), No. 6, 2014, pp. 1432-1445.
Elsevier DOI 1407
BibRef
And:
Action Recognition in Motion Capture Data Using a Bag of Postures Approach,
ICPR14(2649-2654)
IEEE DOI 1412
Databases Action recognition BibRef

Kapsouras, I.[Ioannis], Nikolaidis, N.[Nikos],
Person identity recognition on motion capture data using multiple actions,
MVA(26), No. 7-8, November 2015, pp. 905-918.
WWW Link. 1511
BibRef

Lu, S.Y.[Shi-Yang], Zhang, J.[Jian], Wang, Z.Y.[Zhi-Yong], Feng, D.D.[David Dagan],
Fast human action classification and VOI localization with enhanced sparse coding,
JVCIR(24), No. 2, February 2013, pp. 127-136.
Elsevier DOI 1302
Human action classification; Localization; Sparse coding; Volume of Interest (VOI) BibRef

Yao, T.T.[Ting-Ting], Wang, Z.Y.[Zhi-Yong], Xie, Z.[Zhao], Gao, J.[Jun], Feng, D.D.[David Dagan],
Learning universal multiview dictionary for human action recognition,
PR(64), No. 1, 2017, pp. 236-244.
Elsevier DOI 1701
Dictionary learning BibRef

Chakraborty, B.[Bhaskar], Gonzŕlez, J.[Jordi], Roca, F.X.[F. Xavier],
Large scale continuous visual event recognition using max-margin Hough transformation framework,
CVIU(117), No. 10, 2013, pp. 1356-1368.
Elsevier DOI 1309
Continuous visual event BibRef

Melfi, R.[Roberto], Kondra, S.[Shripad], Petrosino, A.[Alfredo],
Human activity modeling by spatio temporal textural appearance,
PRL(34), No. 15, 2013, pp. 1990-1994.
Elsevier DOI 1309
Human action modeling BibRef

Jiang, Y.F.[Yi-Fei], Li, D.[Du], Lv, Q.[Qin],
Thinking Fast and Slow: An Approach to Energy-Efficient Human Activity Recognition on Mobile Devices,
AIMag(34), No. 2, Summer 2013, pp. 48-66.
WWW Link. 1309
BibRef

Zhang, Y.M.[Yong-Mian], Zhang, Y.F.[Yi-Fan], Swears, E.[Eran], Larios, N.[Natalia], Wang, Z.H.[Zi-Heng], Ji, Q.A.[Qi-Ang],
Modeling Temporal Interactions with Interval Temporal Bayesian Networks for Complex Activity Recognition,
PAMI(35), No. 10, 2013, pp. 2468-2483.
IEEE DOI 1309
Bayesian methods. Multiple parallel and/or sequential actions from an activity. BibRef

Zhang, Y.F.[Yi-Fan], Ji, Q.A.[Qi-Ang], Lu, H.Q.[Han-Qing],
Event Detection in Complex Scenes Using Interval Temporal Constraints,
ICCV13(3184-3191)
IEEE DOI 1403
BibRef

Kamishima, Y.[Yusuke], Inoue, N.[Nakamasa], Shinoda, K.[Koichi],
Event detection in consumer videos using GMM supervectors and SVMs,
JIVP(2013), No. 1, 2013, pp. 51.
DOI Link 1309
BibRef

Kamishima, Y.[Yusuke], Inoue, N.[Nakamasa], Shinoda, K.[Koichi], Sato, S.[Shunsuke],
Multimedia event detection using GMM supervectors and SVMS,
ICIP12(3089-3092).
IEEE DOI 1302
complex event in consumer video. BibRef

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

Wang, H.[Haoran], Yuan, C.F.[Chun-Feng], Hu, W.M.[Wei-Ming], Ling, H.B.[Hai-Bin], Yang, W.K.[Wan-Kou], Sun, C.Y.[Chang-Yin],
Action Recognition Using Nonnegative Action Component Representation and Sparse Basis Selection,
IP(23), No. 2, February 2014, pp. 570-581.
IEEE DOI 1402
graph theory BibRef

Chen, H.S.[Hsuan-Sheng], Tsai, W.J.[Wen-Jiin],
A framework for video event classification by modeling temporal context of multimodal features using HMM,
JVCIR(25), No. 2, 2014, pp. 285-295.
Elsevier DOI 1402
Multimedia system BibRef

Tong, W.[Wei], Yang, Y.[Yi], Jiang, L.[Lu], Yu, S.I.[Shoou-I], Lan, Z.Z.[Zhen-Zhong], Ma, Z.G.[Zhi-Gang], Sze, W.[Waito], Younessian, E.[Ehsan], Hauptmann, A.G.[Alexander G.],
E-LAMP: integration of innovative ideas for multimedia event detection,
MVA(25), No. 1, January 2014, pp. 5-15.
Springer DOI 1402
BibRef

Wang, S.[Sen], Ma, Z.G.[Zhi-Gang], Yang, Y.[Yi], Li, X.[Xue], Pang, C.Y.[Chao-Yi], Hauptmann, A.G.,
Semi-Supervised Multiple Feature Analysis for Action Recognition,
MultMed(16), No. 2, February 2014, pp. 289-298.
IEEE DOI 1404
feature extraction BibRef

Xu, Z.W.[Zhong-Wen], Tsang, I.W.[Ivor W.], Yang, Y.[Yi], Ma, Z.G.[Zhi-Gang], Hauptmann, A.G.[Alexander G.],
Event Detection Using Multi-level Relevance Labels and Multiple Features,
CVPR14(97-104)
IEEE DOI 1409
BibRef

Yang, Y.[Yi], Ma, Z.G.[Zhi-Gang], Xu, Z.W.[Zhong-Wen], Yan, S.C.[Shui-Cheng], Hauptmann, A.G.[Alexander G.],
How Related Exemplars Help Complex Event Detection in Web Videos?,
ICCV13(2104-2111)
IEEE DOI 1403
BibRef

Ma, Z.G.[Zhi-Gang], Yang, Y.[Yi], Nie, F.P.[Fei-Ping], Sebe, N.[Nicu], Yan, S.C.[Shui-Cheng], Hauptmann, A.G.[Alexander G.],
Harnessing Lab Knowledge for Real-World Action Recognition,
IJCV(109), No. 1-2, August 2014, pp. 60-73.
Springer DOI 1407
human action recognition. Domain transfer from lab videos to real world data. BibRef

Zhu, L.C.[Lin-Chao], Xu, Z.W.[Zhong-Wen], Yang, Y.[Yi], Hauptmann, A.G.[Alexander G.],
Uncovering the Temporal Context for Video Question Answering,
IJCV(124), No. 3, September 2017, pp. 409-421.
Springer DOI 1708
BibRef

Xu, Z.W.[Zhong-Wen], Yang, Y.[Yi], Tsang, I.[Ivor], Sebe, N.[Nicu], Hauptmann, A.G.[Alexander G.],
Feature Weighting via Optimal Thresholding for Video Analysis,
ICCV13(3440-3447)
IEEE DOI 1403
BibRef

Ma, Z.G.[Zhi-Gang], Yang, Y.[Yi], Xu, Z.W.[Zhong-Wen], Yan, S.C.[Shui-Cheng], Sebe, N.[Nicu], Hauptmann, A.G.[Alexander G.],
Complex Event Detection via Multi-source Video Attributes,
CVPR13(2627-2633)
IEEE DOI 1309
BibRef

Lan, Z.Z.[Zhen-Zhong], Bao, L.[Lei], Yu, S.I.[Shoou-I], Liu, W.[Wei], Hauptmann, A.G.[Alexander G.],
Double Fusion for Multimedia Event Detection,
MMMod12(173-185).
Springer DOI 1201
BibRef

Yan, Y., Yang, Y., Meng, D., Liu, G., Tong, W., Hauptmann, A.G.[Alexander G.], Sebe, N.[Nicu],
Event Oriented Dictionary Learning for Complex Event Detection,
IP(24), No. 6, June 2015, pp. 1867-1878.
IEEE DOI 1504
Dictionaries BibRef

Myers, G.K.[Gregory K.], Nallapati, R.[Ramesh], van Hout, J.[Julien], Pancoast, S.[Stephanie], Nevatia, R.[Ramakant], Sun, C.[Chen], Habibian, A.[Amirhossein], Koelma, D.C.[Dennis C.], van de Sande, K.E.A.[Koen E. A.], Smeulders, A.W.M.[Arnold W. M.], Snoek, C.G.M.[Cees G. M.],
Evaluating multimedia features and fusion for example-based event detection,
MVA(25), No. 1, January 2014, pp. 17-32.
Springer DOI 1402
Overview of large project. BibRef

Kovvuri, R.[Rama], Nevatia, R.[Ram], Snoek, C.G.M.[Cees G. M.],
Segment-based models for event detection and recounting,
ICPR16(3868-3873)
IEEE DOI 1705
Computational modeling, Detectors, Dictionaries, Hidden Markov models, Semantics, Testing, Training BibRef

Agharwal, A.[Arnav], Kovvuri, R.[Rama], Nevatia, R.[Ram], Snoek, C.G.M.[Cees G. M.],
Tag-based video retrieval by embedding semantic content in a continuous word space,
WACV16(1-8)
IEEE DOI 1511
event retrieval in unconstrained web videos. Detectors BibRef

Habibian, A.[Amirhossein], Snoek, C.G.M.[Cees G.M.],
Recommendations for recognizing video events by concept vocabularies,
CVIU(124), No. 1, 2014, pp. 110-122.
Elsevier DOI 1406
Event recognition BibRef

Habibian, A.[Amirhossein], Mensink, T., Snoek, C.G.M.[Cees G.M.],
Video2vec Embeddings Recognize Events When Examples Are Scarce,
PAMI(39), No. 10, October 2017, pp. 2089-2103.
IEEE DOI 1709
Correlation, Feature extraction, NIST, Semantics, Training, Vehicles, Visualization, Event recognition, representation learning, semantic, video, representation BibRef

Oh, S.[Sangmin], McCloskey, S.[Scott], Kim, I.[Ilseo], Vahdat, A.[Arash], Cannons, K.J.[Kevin J.], Hajimirsadeghi, H.[Hossein], Mori, G.[Greg], Perera, A.G.A.[A. G. Amitha], Pandey, M.[Megha], Corso, J.J.[Jason J.],
Multimedia event detection with multimodal feature fusion and temporal concept localization,
MVA(25), No. 1, January 2014, pp. 49-69.
Springer DOI 1402
BibRef

Streib, K.[Kevin], Davis, J.W.[James W.],
Summarizing high-level scene behavior,
MVA(25), No. 1, January 2014, pp. 229-244.
Springer DOI 1402
Both optical flow and trajectories to summarize. See also Exploiting Multiple Cameras for Environmental Pathlets. BibRef

O'Malley, M.K., Purkayastha, S.N., Howie, N., Byrne, M.D.,
Identifying Successful Motor Task Completion via Motion-Based Performance Metrics,
HMS(44), No. 1, February 2014, pp. 139-145.
IEEE DOI 1403
control engineering computing BibRef

Lin, W.Y., Chen, Y.Z., Wu, J., Wang, H., Sheng, B., Li, H.X.,
A New Network-Based Algorithm for Human Activity Recognition in Videos,
CirSysVideo(24), No. 5, May 2014, pp. 826-841.
IEEE DOI 1405
Correlation BibRef

Chen, Y.Z.[Yuan-Zhe], Lin, W.Y.[Wei-Yao], Li, H.X.[Hong-Xiang], Luo, H.Z.[Hang-Zai], Tao, Y.[Yisi], Liu, D.H.[Dong-Hua],
A new package-group-transmission-based algorithm for human activity recognition in videos,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Bhattacharya, S., Mehran, R.[Ramin], Sukthankar, R., Shah, M.[Mubarak],
Classification of Cinematographic Shots Using Lie Algebra and its Application to Complex Event Recognition,
MultMed(16), No. 3, April 2014, pp. 686-696.
IEEE DOI 1405
Lie algebras BibRef

Borzeshi, E.Z.[Ehsan Zare], Dehghan, A.[Afshin], Piccardi, M.[Massimo], Shah, M.[Mubarak],
Complex event recognition by latent temporal models of concepts,
ICIP14(2373-2377)
IEEE DOI 1502
Decoding BibRef

Kwak, S.[Suha], Han, B.H.[Bo-Hyung], Han, J.H.[Joon Hee],
On-Line Video Event Detection by Constraint Flow,
PAMI(36), No. 6, June 2014, pp. 1174-1186.
IEEE DOI 1406
BibRef
Earlier:
Multi-agent Event Detection: Localization and Role Assignment,
CVPR13(2682-2689)
IEEE DOI 1309
Event detection. activity detection; video event detection BibRef

Ferrer, G.[Gonzalo], Sanfeliu, A.[Alberto],
Bayesian Human Motion Intentionality Prediction in urban environments,
PRL(44), No. 1, 2014, pp. 134-140.
Elsevier DOI 1407
Human motion prediction 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

Fouhey, D.F.[David F.], Delaitre, V.[Vincent], Gupta, A.[Abhinav], Efros, A.A.[Alexei A.], Laptev, I.[Ivan], Sivic, J.[Josef],
People Watching: Human Actions as a Cue for Single View Geometry,
IJCV(110), No. 1, December 2014, pp. 259-274.
Springer DOI 1411
BibRef
Earlier: ECCV12(V: 732-745).
Springer DOI 1210
BibRef

Delaitre, V.[Vincent], Fouhey, D.F.[David F.], Laptev, I.[Ivan], Sivic, J.[Josef], Gupta, A.[Abhinav], Efros, A.A.[Alexei A.],
Scene Semantics from Long-Term Observation of People,
ECCV12(VI: 284-298).
Springer DOI 1210
BibRef

Yu, G.[Gang], Yuan, J.S.[Jun-Song], Liu, Z.C.[Zi-Cheng],
Propagative Hough Voting for Human Activity Detection and Recognition,
CirSysVideo(25), No. 1, January 2015, pp. 87-98.
IEEE DOI 1502
BibRef
Earlier:
Propagative Hough Voting for Human Activity Recognition,
ECCV12(III: 693-706).
Springer DOI 1210
feature extraction BibRef

Yang, D.Q.[Ding-Qi], Zhang, D.Q.[Da-Qing], Zheng, V.W., Yu, Z.Y.[Zhi-Yong],
Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs,
SMCS(45), No. 1, January 2015, pp. 129-142.
IEEE DOI 1502
mobile computing. Tracking info not image based. BibRef

Baxter, R.H.[Rolf H.], Robertson, N.M.[Neil M.], Lane, D.M.[David M.],
Human behaviour recognition in data-scarce domains,
PR(48), No. 8, 2015, pp. 2377-2393.
Elsevier DOI 1505
Behavior recognition BibRef

Chuang, C.H.[Chi-Hung], Hsieh, J.W.[Jun-Wei], Chiang, H.F.[Hui-Fen], Chiou, Y.D.[Yi-Da],
Human movement analysis around a view circle using time-order similarity distributions,
JVCIR(30), No. 1, 2015, pp. 22-34.
Elsevier DOI 1507
Video surveillance BibRef

Jiang, Y.G., Dai, Q., Mei, T., Rui, Y., Chang, S.F.,
Super Fast Event Recognition in Internet Videos,
MultMed(17), No. 8, August 2015, pp. 1174-1186.
IEEE DOI 1506
Feature extraction 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

Lee, K.[Kyuhwa], Ognibene, D., Chang, H.J.[Hyung Jin], Kim, T.K.[Tae-Kyun], Demiris, Y.,
STARE: Spatio-Temporal Attention Relocation for Multiple Structured Activities Detection,
IP(24), No. 12, December 2015, pp. 5916-5927.
IEEE DOI 1512
computer vision BibRef

Vo, N.N.[Nam N.], Bobick, A.F.[Aaron F.],
Sequential Interval Network for parsing complex structured activity,
CVIU(143), No. 1, 2016, pp. 147-158.
Elsevier DOI 1601
Activity parsing 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

Anirudh, R.[Rushil], Turaga, P.K.[Pavan K.],
Geometry-Based Symbolic Approximation for Fast Sequence Matching on Manifolds,
IJCV(116), No. 2, January 2016, pp. 161-173.
Springer DOI 1602
BibRef

Arai, A.[Ayumi], Fan, Z.[Zipei], Matekenya, D.[Dunstan], Shibasaki, R.[Ryosuke],
Comparative Perspective of Human Behavior Patterns to Uncover Ownership Bias among Mobile Phone Users,
IJGI(5), No. 6, 2016, pp. 85.
DOI Link 1608
BibRef

Barrett, D.P.[Daniel Paul], Barbu, A.[Andrei], Siddharth, N., Siskind, J.M.[Jeffrey Mark],
Saying What You're Looking For: Linguistics Meets Video Search,
PAMI(38), No. 10, October 2016, pp. 2069-2081.
IEEE DOI 1609
BibRef
Earlier: A3, A2, A4, Only:
Seeing What You're Told: Sentence-Guided Activity Recognition in Video,
CVPR14(732-739)
IEEE DOI 1409
Detectors. Text (language) guided analysis. BibRef

Barrett, D.P.[Daniel Paul], Siskind, J.M.[Jeffrey Mark],
Action Recognition by Time Series of Retinotopic Appearance and Motion Features,
CirSysVideo(26), No. 12, December 2016, pp. 2250-2263.
IEEE DOI 1612
Computational modeling BibRef

Guo, Y.[Yanan], Tao, D.P.[Da-Peng], Cheng, J.[Jun], Dougherty, A.[Alan], Li, Y.T.[Yao-Tang], Yue, K.[Kun], Zhang, B.[Bob],
Tensor Manifold Discriminant Projections for Acceleration-Based Human Activity Recognition,
MultMed(18), No. 10, October 2016, pp. 1977-1987.
IEEE DOI 1610
feature extraction 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

Stein, S.[Sebastian], McKenna, S.J.[Stephen J.],
Recognising complex activities with histograms of relative tracklets,
CVIU(154), No. 1, 2017, pp. 82-93.
Elsevier DOI 1612
Activity recognition BibRef

de Souza, F.D.M.[Fillipe D. M.], Sarkar, S.[Sudeep], Srivastava, A.[Anuj], Su, J.Y.[Jing-Yong],
Spatially Coherent Interpretations of Videos Using Pattern Theory,
IJCV(121), No. 1, January 2017, pp. 5-25.
Springer DOI 1702
BibRef
Earlier:
Temporally coherent interpretations for long videos using pattern theory,
CVPR15(1229-1237)
IEEE DOI 1510
BibRef
Earlier:
Pattern Theory-Based Interpretation of Activities,
ICPR14(106-111)
IEEE DOI 1412
BibRef

Azhar, F., Li, C.T.,
Hierarchical Relaxed Partitioning System for Activity Recognition,
Cyber(47), No. 3, March 2017, pp. 784-795.
IEEE DOI 1702
Computational modeling BibRef

Wang, L., Zhao, X., Si, Y., Cao, L., Liu, Y.,
Context-Associative Hierarchical Memory Model for Human Activity Recognition and Prediction,
MultMed(19), No. 3, March 2017, pp. 646-659.
IEEE DOI 1702
Computational modeling BibRef

Wang, B.Y.[Bo-Yue], Hu, Y.L.[Yong-Li], Gao, J.B.[Jun-Bin], Sun, Y.F.[Yan-Feng], Yin, B.C.[Bao-Cai],
Laplacian LRR on Product Grassmann Manifolds for Human Activity Clustering in Multicamera Video Surveillance,
CirSysVideo(27), No. 3, March 2017, pp. 554-566.
IEEE DOI 1703
LRR: Low Rank Representation. Cameras BibRef

Fernando, B.[Basura], Gould, S.[Stephen],
Discriminatively Learned Hierarchical Rank Pooling Networks,
IJCV(124), No. 3, September 2017, pp. 335-355.
Springer DOI 1708
BibRef

Fernando, B.[Basura], Anderson, P.[Peter], Hutter, M.[Marcus], Gould, S.[Stephen],
Discriminative Hierarchical Rank Pooling for Activity Recognition,
CVPR16(1924-1932)
IEEE DOI 1612
BibRef

Barekatain, M., Martí, M., Shih, H.F., Murray, S., Nakayama, K., Matsuo, Y., Prendinger, H.,
Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection,
PETS17(2153-2160)
IEEE DOI 1709
Cameras, Data collection, Mobile communication, Surveillance, Training, Video, sequences 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

Qin, Z.[Zhen], Shelton, C.R.[Christian R.],
Event Detection in Continuous Video: An Inference in Point Process Approach,
IP(26), No. 12, December 2017, pp. 5680-5691.
IEEE DOI 1710
high-level semantic events, Inference algorithms, Semantics, BibRef


Ho, S.B.[Seng-Beng],
The Role of Synchronic Causal Conditions in Visual Knowledge Learning,
Cognition17(9-16)
IEEE DOI 1709
Correlation, Encoding, Problem-solving, Psychology, Visualization, Weapons BibRef

Zunino, A.[Andrea], Cavazza, J.[Jacopo], Koul, A.[Atesh], Cavallo, A.[Andrea], Becchio, C.[Cristina], Murino, V.[Vittorio],
What Will I Do Next? The Intention from Motion Experiment,
Cognition17(1-8)
IEEE DOI 1709
Activity recognition, Computer vision, Ear, Grasping, Kinematics, Three-dimensional displays, Videos BibRef

Lei, J.[Jun], Li, G.H.[Guo-Hui], Zhang, J.[Jun], Li, S.H.[Shuo-Hao], Wang, F.L.[Feng-Lei],
Continuous action recognition with weakly labelling videos,
MVA17(242-245)
DOI Link 1708
Feature extraction, Labeling, Organizations, Supervised learning, Training, Videos, Visualization. Order of action labels, not location. BibRef

Ahsan, U.[Unaiza], Sun, C., Hays, J., Essa, I.A.[Irfan A.],
Complex Event Recognition from Images with Few Training Examples,
WACV17(669-678)
IEEE DOI 1609
Encyclopedias, Feature extraction, Flickr, Image recognition, Image segmentation, Training, Visualization BibRef

Kataoka, H.[Hirokatsu], Iwata, K.[Kenji], Satoh, Y.[Yutaka], Hayashi, M., Aoki, Y.[Yoshimitsu], Ilic, S.[Slobodan],
Dominant Codewords Selection with Topic Model for Action Recognition,
ChaLearn16(770-777)
IEEE DOI 1612
BibRef

Hasan, M.[Mahmudul], Choi, J.H.[Jong-Hyun], Neumann, J.[Jan], Roy-Chowdhury, A.K.[Amit K.], Davis, L.S.[Larry S.],
Learning Temporal Regularity in Video Sequences,
CVPR16(733-742)
IEEE DOI 1612
BibRef

Su, Y.C.[Yu-Chuan], Grauman, K.[Kristen],
Leaving Some Stones Unturned: Dynamic Feature Prioritization for Activity Detection in Streaming Video,
ECCV16(VII: 783-800).
Springer DOI 1611
BibRef

Watagawa, M., Shinoda, T., Hasegawa, K.,
Estimating The Amount Of Ship Recycling Activity Using Remote Sensing Application,
ISPRS16(B8: 1195-1200).
DOI Link 1610
BibRef

Li, W., Fritz, M.,
Recognition of ongoing complex activities by sequence prediction over a hierarchical label space,
WACV16(1-9)
IEEE DOI 1511
Object recognition BibRef

Yan, W.Q.[Wei Qi], Liu, F.[Feng],
Event Analogy Based Privacy Preservation in Visual Surveillance,
VSWS15(357-368).
Springer DOI 1603
BibRef

Timofte, R.[Radu], Rothe, R., Van Gool, L.J.,
Seven Ways to Improve Example-Based Single Image Super Resolution,
CVPR16(1865-1873)
IEEE DOI 1612
BibRef

Rothe, R., Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
DLDR: Deep Linear Discriminative Retrieval for Cultural Event Classification from a Single Image,
ChaLearnDec15(295-302)
IEEE DOI 1602
Agriculture BibRef

Liu, M., Liu, X., Li, Y., Chen, X., Hauptmann, A.G., Shan, S.,
Exploiting Feature Hierarchies with Convolutional Neural Networks for Cultural Event Recognition,
ChaLearnDec15(274-279)
IEEE DOI 1602
Cultural differences BibRef

Wei, X.S., Gao, B.B., Wu, J.,
Deep Spatial Pyramid Ensemble for Cultural Event Recognition,
ChaLearnDec15(280-286)
IEEE DOI 1602
Cultural differences BibRef

Wu, T., Gurram, P., Rao, R.M., Bajwa, W.U.,
Clustering-aware structure-constrained low-rank representation model for learning human action attributes,
IVMSP16(1-5)
IEEE DOI 1608
BibRef
Earlier:
Hierarchical Union-of-Subspaces Model for Human Activity Summarization,
VidSum15(1053-1061)
IEEE DOI 1602
Clustering algorithms BibRef

Gammulle, H., Denman, S.[Simon], Sridharan, S.[Sridha], Fookes, C.[Clinton],
Two Stream LSTM: A Deep Fusion Framework for Human Action Recognition,
WACV17(177-186)
IEEE DOI 1609
Computer vision, Databases, Feature extraction, Neural networks, Support vector machines, Training, Video, sequences See also Hessian-Based Affine Adaptation of Salient Local Image Features. BibRef

Umakanthan, S.[Sabanadesan], Denman, S.[Simon], Fookes, C.[Clinton], Sridharan, S.[Sridha],
Class-specific sparse codes for representing activities,
ICIP15(4902-4906)
IEEE DOI 1512
Activity representation; bag-of-words; sparse codes 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

Batabyal, T.[Tamal], Acton, S.T.[Scott T.], Vaccari, A.[Andrea],
UGrAD: A graph-theoretic framework for classification of activity with complementary graph boundary detection,
ICIP16(1339-1343)
IEEE DOI 1610
Bipartite graph BibRef
Earlier: A1, A3, A2:
LaWeCo: Active region detection in non-uniformly sampled data using Laplacian-weighted covariance,
Southwest16(129-132)
IEEE DOI 1605
BibRef
And: A1, A3, A2:
UGraSP: A unified framework for activity recognition and person identification using graph signal processing,
ICIP15(3270-3274)
IEEE DOI 1512
Covariance matrices. Adjacency Matrix BibRef

Avgerinakis, K.[Konstantinos], Adam, K.[Katerina], Briassouli, A.[Alexia], Kompatsiaris, Y.[Yiannis],
Moving camera human activity localization and recognition with motionplanes and multiple homographies,
ICIP15(2085-2089)
IEEE DOI 1512
activity localization; activity recognition; homography; motionplanes BibRef

Stephens, K., Bors, A.G.,
Human group activity recognition based on modelling moving regions interdependencies,
ICPR16(2115-2120)
IEEE DOI 1705
BibRef
And:
Group activity recognition on outdoor scenes,
AVSS16(59-65)
IEEE DOI 1611
BibRef
And:
Grouping multi-vector streaklines for human activity identification,
IVMSP16(1-5)
IEEE DOI 1608
BibRef
And:
Observing human activities using movement modelling,
AVSS15(1-6)
IEEE DOI 1511
Activity recognition, Cameras, Computational modeling, Estimation, Manuals, Mathematical model, Tracking, Group Activity Identification, Motion Segmentation, Streaklines. Computational modeling. Cameras. Gaussian processes BibRef

Martinel, N.[Niki], Avola, D.[Danilo], Piciarelli, C.[Claudio], Micheloni, C.[Christian], Vernier, M.[Marco], Cinque, L.[Luigi], Foresti, G.L.[Gian Luca],
Selection of Temporal Features for Event Detection in Smart Security,
CIAP15(II:609-619).
Springer DOI 1511
BibRef

Salvador, A.[Amaia], Manchon-Vizuete, D.[Daniel], Calafell, A.[Andrea], Giro-i-Nieto, X.[Xavier], Zeppelzauer, M.[Matthias],
Cultural Event recognition with visual ConvNets and temporal models,
ChaLearn15(36-44)
IEEE DOI 1510
Computational modeling BibRef

Park, S.[Sungheon], Kwak, N.[Nojun],
Cultural event recognition by subregion classification with convolutional neural network,
ChaLearn15(45-50)
IEEE DOI 1510
Accuracy BibRef

Kwon, H.[Heeyoung], Yun, K.[Kiwon], Hoai, M.[Minh], Samaras, D.[Dimitris],
Recognizing cultural events in images: A study of image categorization models,
ChaLearn15(51-57)
IEEE DOI 1510
Cultural differences BibRef

Wu, C.X.[Chen-Xia], Zhang, J.[Jiemi], Savarese, S.[Silvio], Saxena, A.[Ashutosh],
Watch-n-patch: Unsupervised understanding of actions and relations,
CVPR15(4362-4370)
IEEE DOI 1510
BibRef

Heilbron, F.C.[Fabian Caba], Escorcia, V.[Victor], Ghanem, B.[Bernard], Niebles, J.C.[Juan Carlos],
ActivityNet: A large-scale video benchmark for human activity understanding,
CVPR15(961-970)
IEEE DOI 1510
BibRef

Liang, J.W.[Jing-Wei], Fadili, J.[Jalal], Peyré, G.[Gabriel], Luke, R.[Russell],
Activity Identification and Local Linear Convergence of Douglas-Rachford/ADMM under Partial Smoothness,
SSVM15(642-653).
Springer DOI 1506
BibRef

Adeli-Mosabbeb, E.[Ehsan], Cabral, R.S.[Ricardo S.], de la Torre, F.[Fernando], Fathy, M.[Mahmood],
Multi-label Discriminative Weakly-Supervised Human Activity Recognition and Localization,
ACCV14(V: 241-258).
Springer DOI 1504
BibRef

Chakraborty, A.[Anirban], Roy-Chowdhury, A.K.[Amit K.],
Context-Aware Activity Forecasting,
ACCV14(V: 21-36).
Springer DOI 1504
BibRef

Killedar, D., Sasi, S.,
Human activity detection using sparse representation,
AIPR14(1-5)
IEEE DOI 1504
feature extraction BibRef

Lan, T.[Tian], Chen, L.[Lei], Deng, Z.W.[Zhi-Wei], Zhou, G.T.[Guang-Tong], Mori, G.[Greg],
Learning Action Primitives for Multi-level Video Event Understanding,
Re-Id14(95-110).
Springer DOI 1504
BibRef

Singh, B., Han, X., Wu, Z., Morariu, V.I.[Vlad I.], Davis, L.S.[Larry S.],
Selecting Relevant Web Trained Concepts for Automated Event Retrieval,
ICCV15(4561-4569)
IEEE DOI 1602
Calibration BibRef

Lee, H.T.[Hyung-Tae], Morariu, V.I.[Vlad I.], Davis, L.S.[Larry S.],
Clauselets: Leveraging Temporally Related Actions for Video Event Analysis,
WACV15(1161-1168)
IEEE DOI 1503
Sets of concurrent actions and their temporal relationships. BibRef

Khoualed, S.[Samir], Chateau, T.[Thierry], Castellan, U.[Umberto], Samir, C.[Chafik],
An augmented representation of activity in video using semantic-context information,
ICIP14(4171-4175)
IEEE DOI 1502
Accuracy BibRef

Alemdar, H.[Hande], van Kasteren, T.L., Niessen, M.E., Merentitis, A., Ersoy, C.[Cem],
A Unified Model for Human Behavior Modeling Using a Hierarchy with a Variable Number of States,
ICPR14(3804-3809)
IEEE DOI 1412
Bayes methods BibRef

Nguyen, T.[Thuong], Gupta, S.I.[Sun-Il], Venkatesh, S.[Svetha], Phung, D.Q.[Dinh Q.],
A Bayesian Nonparametric Framework for Activity Recognition Using Accelerometer Data,
ICPR14(2017-2022)
IEEE DOI 1412
Accelerometers BibRef

Behera, A.[Ardhendu], Cohn, A.[Anthony], Hogg, D.[David],
Real-time Activity Recognition by Discerning Qualitative Relationships Between Randomly Chosen Visual Features,
BMVC14(xx-yy).
HTML Version. 1410
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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

Wu, S.[Shuang], Bondugula, S.[Sravanthi], Luisier, F.[Florian], Zhuang, X.D.[Xiao-Dan], Natarajan, P.[Pradeep],
Zero-Shot Event Detection Using Multi-modal Fusion of Weakly Supervised Concepts,
CVPR14(2665-2672)
IEEE DOI 1409
Concept Detection BibRef

Hammoud, R.I.[Riad I.], Sahin, C.S.[Cem S.], Blasch, E.P.[Erik P.], Rhodes, B.J.[Bradley J.],
Multi-source Multi-modal Activity Recognition in Aerial Video Surveillance,
PBVS14(237-244)
IEEE DOI 1409
FMV exploitation BibRef

Bhattacharya, S.[Subhabrata], Kalayeh, M.M.[Mahdi M.], Sukthankar, R.[Rahul], Shah, M.[Mubarak],
Recognition of Complex Events: Exploiting Temporal Dynamics between Underlying Concepts,
CVPR14(2243-2250)
IEEE DOI 1409
Complex Event Recognition BibRef

Shankar, S.[Sukrit], Badrinarayanan, V.[Vijay], Cipolla, R.[Roberto],
Part Bricolage: Flow-Assisted Part-Based Graphs for Detecting Activities in Videos,
ECCV14(VI: 586-601).
Springer DOI 1408
BibRef

Clawson, K.M.[Kathy M.], Jing, M.[Min], Scotney, B.W.[Bryan W.], Wang, H.[Hui], Liu, J.[Jun],
Human Action Recognition in Video via Fused Optical Flow and Moment Features: Towards a Hierarchical Approach to Complex Scenario Recognition,
MMMod14(II: 104-115).
Springer DOI 1405
BibRef

Nitta, N.[Naoko], Kumihashi, Y.[Yusuke], Kato, T.[Tomochika], Babaguchi, N.[Noboru],
Real-World Event Detection Using Flickr Images,
MMMod14(II: 307-314).
Springer DOI 1405
BibRef

Hsieh, Y.H.[Yung-Huan], Hidayati, S.C.[Shintami C.], Cheng, W.H.[Wen-Huang], Hu, M.C.[Min-Chun], Hua, K.L.[Kai-Lung],
Who's the Best Charades Player? Mining Iconic Movement of Semantic Concepts,
MMMod14(I: 231-241).
Springer DOI 1405
BibRef

Zafeiriou, L.[Lazaros], Antonakos, E.[Epameinondas], Zafeiriou, S.P.[Stefanos P.], Pantic, M.[Maja],
Joint Unsupervised Deformable Spatio-Temporal Alignment of Sequences,
CVPR16(3382-3390)
IEEE DOI 1612
BibRef
Earlier:
Joint Unsupervised Face Alignment and Behaviour Analysis,
ECCV14(IV: 167-183).
Springer DOI 1408
BibRef

Zafeiriou, L.[Lazaros], Nicolaou, M.A.[Mihalis A.], Zafeiriou, S.P.[Stefanos P.], Nikitidis, S.[Symeon], Pantic, M.[Maja],
Learning Slow Features for Behaviour Analysis,
ICCV13(2840-2847)
IEEE DOI 1403
Component Analysis; Slow Feature Analysis See also Incremental Slow Feature Analysis with Indefinite Kernel for Online Temporal Video Segmentation. BibRef

Tang, K.[Kevin], Yao, B.P.[Bang-Peng], Fei-Fei, L.[Li], Koller, D.[Daphne],
Combining the Right Features for Complex Event Recognition,
ICCV13(2696-2703)
IEEE DOI 1403
Complex Event Recognition; Feature Combination BibRef

Douze, M.[Matthijs], Revaud, J.[Jerome], Schmid, C.[Cordelia], Jegou, H.[Herve],
Stable Hyper-pooling and Query Expansion for Event Detection,
ICCV13(1825-1832)
IEEE DOI 1403
See also Compact Video Description for Copy Detection with Precise Temporal Alignment. BibRef

Fang, X.Y.[Xiao-Yu], Xia, Z.[Ziwei], Su, C.[Chi], Xu, T.[Teng], Tian, Y.H.[Yong-Hong], Wang, Y.W.[Yao-Wei], Huang, T.J.[Tie-Jun],
A system based on sequence learning for event detection in surveillance video,
ICIP13(3587-3591)
IEEE DOI 1402
Event detection;sequence learning;surveillance BibRef

Codella, N.C.E.[Noel C.E.], Hua, G.[Gang], Cao, L.L.[Liang-Liang], Merler, M.[Michele], Gong, L.G.[Lei-Guang], Hill, M.[Matt], Smith, J.R.[John R.],
Large-scale video event classification using dynamic temporal pyramid matching of visual semantics,
ICIP13(2877-2881)
IEEE DOI 1402
event; pyramid; semantics; temporal; video BibRef

Gopalan, R.[Raghuraman],
Joint Sparsity-Based Representation and Analysis of Unconstrained Activities,
CVPR13(2738-2745)
IEEE DOI 1309
BibRef

Sun, C.[Chen], Nevatia, R.[Ram],
DISCOVER: Discovering Important Segments for Classification of Video Events and Recounting,
CVPR14(2569-2576)
IEEE DOI 1409
BibRef
Earlier:
Semantic Aware Video Transcription Using Random Forest Classifiers,
ECCV14(I: 772-786).
Springer DOI 1408
BibRef
Earlier:
ACTIVE: Activity Concept Transitions in Video Event Classification,
ICCV13(913-920)
IEEE DOI 1403
BibRef
And:
Large-scale web video event classification by use of Fisher Vectors,
WACV13(15-22).
IEEE DOI 1303
event classification; event recounting; latent svm BibRef

Tao, S.[Shuai], Kudo, M.[Mineichi], Nonaka, H.[Hidetoshi], Toyama, J.[Jun],
Camera view usage of binary infrared sensors for activity recognition,
ICPR12(1759-1762).
WWW Link. 1302
BibRef

Li, K.[Kang], Fu, Y.[Yun],
ARMA-HMM: A new approach for early recognition of human activity,
ICPR12(1779-1782).
WWW Link. 1302
BibRef

Tu, P.[Peter], Gao, D.[Dashan], Yu, T.[Ting], Yao, Y.[Yi],
Action based video summarization for convenience stores,
ICIP12(45-48).
IEEE DOI 1302
BibRef

Cullen, D.[Daniel], Konrad, J.[Janusz], Little, T.D.C.,
Detection and Summarization of Salient Events in Coastal Environments,
AVSS12(7-12).
IEEE DOI 1211
BibRef

Walker, J.[Jacob], Gupta, A.[Abhinav], Hebert, M.[Martial],
Patch to the Future: Unsupervised Visual Prediction,
CVPR14(3302-3309)
IEEE DOI 1409
Activity Forecasting; Prediction mid-level visual elements and temporal modeling. BibRef

Yang, Y.[Yang], Shah, M.[Mubarak],
Complex Events Detection Using Data-Driven Concepts,
ECCV12(III: 722-735).
Springer DOI 1210
Video:
WWW Link. BibRef

Odobez, J.M.[Jean-Marc], Carincotte, C.[Cyril], Emonet, R.[Rémi], Jouneau, E.[Erwan], Zaidenberg, S.[Sofia], Ravera, B.[Bertrand], Bremond, F.[Francois], Grifoni, A.[Andrea],
Unsupervised Activity Analysis and Monitoring Algorithms for Effective Surveillance Systems,
ECCVDemos12(III: 675-678).
Springer DOI 1210
BibRef

Cheng, Z.W.[Zhong-Wei], Qin, L.[Lei], Ye, Y.[Yituo], Huang, Q.M.[Qing-Ming], Tian, Q.[Qi],
Human Daily Action Analysis with Multi-view and Color-Depth Data,
CDC4CV12(II: 52-61).
Springer DOI 1210
BibRef

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

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

Stottinger, J.[Julian], Uijlings, J.R.R.[Jasper R. R.], Pandey, A.K.[Anand K.], Sebe, N.[Nicu], Giunchiglia, F.[Fausto],
(Unseen) event recognition via semantic compositionality,
CVPR12(3061-3068).
IEEE DOI 1208
High level events built from image level events BibRef

Lan, T.[Tian], Sigal, L.[Leonid], Mori, G.[Greg],
Social roles in hierarchical models for human activity recognition,
CVPR12(1354-1361).
IEEE DOI 1208
BibRef

Hassan, E.[Ehtesham], Chaudhury, S.[Santanu], Gopal, M, Garg, V.[Vikram],
A hybrid framework for event detection using multi-modal features,
VECTaR11(1510-1515).
IEEE DOI 1201
See also Annotating Dance Posture Images Using Multi Kernel Feature Combination. BibRef

Wang, J.[Jing], Xu, Z.J.[Zhi-Jie],
Video event detection based on over-segmented STV regions,
VECTaR11(1464-1471).
IEEE DOI 1201
BibRef

Al Ghamdi, M.[Manal], Zhang, L.[Lei], Gotoh, Y.[Yoshihiko],
Spatio-temporal SIFT and Its Application to Human Action Classification,
VECTaR12(I: 301-310).
Springer DOI 1210
BibRef

Khan, M.U.G.[Muhammad Usman Ghani], Zhang, L.[Lei], Gotoh, Y.[Yoshihiko],
Human Focused Video Description,
VECTaR11(1480-1487).
IEEE DOI 1201
BibRef

Zhang, J.G.[Jian-Gen], Hu, W.Z.[Wen-Ze], Yao, B.[Benjamin], Wang, Y.T.[Yong-Tian], Zhu, S.C.[Song-Chun],
Inferring social roles in long timespan video sequence,
VECTaR11(1456-1463).
IEEE DOI 1201
BibRef

Mitarai, Y.[Yusuke], Matsugu, M.[Masakazu],
Visual Code-Sentences: A New Video Representation Based on Image Descriptor Sequences,
VECTaR12(I: 321-331).
Springer DOI 1210
BibRef

Matsugu, M.[Masakazu], Yamanaka, M.[Masao], Sugiyama, M.[Masashi],
Detection of activities and events without explicit categorization,
VECTaR11(1532-1539).
IEEE DOI 1201
BibRef

Kaloskampis, I.[Ioannis], Hicks, Y.A.[Yulia A.], Marshall, D.[David],
Automatic analysis of composite activities in video sequences using Key Action Discovery and hierarchical graphical models,
ARTEMIS11(890-897).
IEEE DOI 1201
BibRef

Malgireddy, M.R.[Manavender R.], Nwogu, I.[Ifeoma], Govindaraju, V.[Venu],
A temporal Bayesian model for classifying, detecting and localizing activities in video sequences,
Gesture12(43-48).
IEEE DOI 1207
BibRef
Earlier:
A generative framework to investigate the underlying patterns in human activities,
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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:Nov 11, 2017 at 13:31:57