Bibliography

Major publications by the team in recent years

1A. Avanzi, F. Brémond, C. Tornieri, M. Thonnat.

Design and Assessment of an Intelligent Activity Monitoring Platform, in: EURASIP Journal on Applied Signal Processing, Special Issue on “Advances in Intelligent Vision Systems: Methods and Applications”, August 2005, vol. 2005:14, pp. 2359-2374.
2H. Benhadda, J. Patino, E. Corvee, F. Bremond, M. Thonnat.

Data Mining on Large Video Recordings, in: 5eme Colloque Veille Stratégique Scientifique et Technologique VSST 2007, Marrakech, Marrocco, 21st - 25th October 2007.
3B. Boulay, F. Bremond, M. Thonnat.

Applying 3D Human Model in a Posture Recognition System, in: Pattern Recognition Letter, 2006, vol. 27, n^o 15, pp. 1785-1796.
4F. Brémond, M. Thonnat.

Issues of Representing Context Illustrated by Video-surveillance Applications, in: International Journal of Human-Computer Studies, Special Issue on Context, 1998, vol. 48, pp. 375-391.
5G. Charpiat.

Learning Shape Metrics based on Deformations and Transport, in: Proceedings of ICCV 2009 and its Workshops, Second Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment (NORDIA), Kyoto, Japan, September 2009.
6N. Chleq, F. Brémond, M. Thonnat.

Advanced Video-based Surveillance Systems, Kluwer A.P. , Hangham, MA, USA, November 1998, pp. 108-118.
7F. Cupillard, F. Brémond, M. Thonnat.

Tracking Group of People for Video Surveillance, Video-Based Surveillance Systems, Kluwer Academic Publishers, 2002, vol. The Kluwer International Series in Computer Vision and Distributed Processing, pp. 89-100.
8F. Fusier, V. Valentin, F. Bremond, M. Thonnat, M. Borg, D. Thirde, J. Ferryman.

Video Understanding for Complex Activity Recognition, in: Machine Vision and Applications Journal, 2007, vol. 18, pp. 167-188.
9B. Georis, F. Bremond, M. Thonnat.

Real-Time Control of Video Surveillance Systems with Program Supervision Techniques, in: Machine Vision and Applications Journal, 2007, vol. 18, pp. 189-205.
10C. Liu, P. Chung, Y. Chung, M. Thonnat.

Understanding of Human Behaviors from Videos in Nursing Care Monitoring Systems, in: Journal of High Speed Networks, 2007, vol. 16, pp. 91-103.
11N. Maillot, M. Thonnat, A. Boucher.

Towards Ontology Based Cognitive Vision, in: Machine Vision and Applications (MVA), December 2004, vol. 16, n^o 1, pp. 33-40.
12V. Martin, J.-M. Travere, F. Bremond, V. Moncada, G. Dunand.

Thermal Event Recognition Applied to Protection of Tokamak Plasma-Facing Components, in: IEEE Transactions on Instrumentation and Measurement, Apr 2010, vol. 59, n^o 5, pp. 1182-1191.
13S. Moisan.

Knowledge Representation for Program Reuse, in: European Conference on Artificial Intelligence (ECAI), Lyon, France, July 2002, pp. 240-244.
14S. Moisan.

Une plate-forme pour une programmation par composants de systèmes à base de connaissances, Université de Nice-Sophia Antipolis, April 1998, Habilitation à diriger les recherches.
15S. Moisan, A. Ressouche, J.-P. Rigault.

Blocks, a Component Framework with Checking Facilities for Knowledge-Based Systems, in: Informatica, Special Issue on Component Based Software Development, November 2001, vol. 25, n^o 4, pp. 501-507.
16J. Patino, H. Benhadda, E. Corvee, F. Bremond, M. Thonnat.

Video-Data Modelling and Discovery, in: 4th IET International Conference on Visual Information Engineering VIE 2007, London, UK, 25th - 27th July 2007.
17J. Patino, E. Corvee, F. Bremond, M. Thonnat.

Management of Large Video Recordings, in: 2nd International Conference on Ambient Intelligence Developments AmI.d 2007, Sophia Antipolis, France, 17th - 19th September 2007.
18A. Ressouche, D. Gaffé, V. Roy.

Modular Compilation of a Synchronous Language, in: Software Engineering Research, Management and Applications, R. Lee (editor), Studies in Computational Intelligence, Springer, 2008, vol. 150, pp. 157-171, selected as one of the 17 best papers of SERA'08 conference.
19A. Ressouche, D. Gaffé.

Compilation Modulaire d'un Langage Synchrone, in: Revue des sciences et technologies de l'information, série Théorie et Science Informat ique, June 2011, vol. 4, n^o 30, pp. 441-471.

http://hal.inria.fr/inria-00524499/en
20M. Thonnat, S. Moisan.

What Can Program Supervision Do for Software Re-use?, in: IEE Proceedings - Software Special Issue on Knowledge Modelling for Software Components Reuse, 2000, vol. 147, n^o 5.
21M. Thonnat.

Vers une vision cognitive: mise en oeuvre de connaissances et de raisonnements pour l'analyse et l'interprétation d'images, Université de Nice-Sophia Antipolis, October 2003, Habilitation à diriger les recherches.
22M. Thonnat.

Special issue on Intelligent Vision Systems, in: Computer Vision and Image Understanding, May 2010, vol. 114, n^o 5, pp. 501-502.
23A. Toshev, F. Brémond, M. Thonnat.

An A priori-based Method for Frequent Composite Event Discovery in Videos, in: Proceedings of 2006 IEEE International Conference on Computer Vision Systems, New York USA, January 2006.
24V. Vu, F. Brémond, M. Thonnat.

Temporal Constraints for Video Interpretation, in: Proc of the 15th European Conference on Artificial Intelligence, Lyon, France, 2002.
25V. Vu, F. Brémond, M. Thonnat.

Automatic Video Interpretation: A Novel Algorithm based for Temporal Scenario Recognition, in: The Eighteenth International Joint Conference on Artificial Intelligence (IJCAI'03), 9-15 September 2003.
26N. Zouba, F. Bremond, A. Anfosso, M. Thonnat, E. Pascual, O. Guerin.

Monitoring elderly activities at home, in: Gerontechnology, May 2010, vol. 9, n^o 2.

Publications of the year

Articles in International Peer-Reviewed Journals

27C. F. Crispim-Junior, V. Buso, K. Avgerinakis, G. Meditskos, A. Briassouli, J. Benois-Pineau, Y. KOMPATSIARIS, F. Bremond.

Semantic Event Fusion of Different Visual Modality Concepts for Activity Recognition, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016, vol. 38, pp. 1598 - 1611. [ DOI : 10.1109/TPAMI.2016.2537323 ]

https://hal.inria.fr/hal-01399025
28A. Dantcheva, F. Brémond.

Gender estimation based on smile-dynamics, in: IEEE Transactions on Information Forensics and Security, 2016, 11 p. [ DOI : 10.1109/TIFS.2016.2632070 ]

https://hal.archives-ouvertes.fr/hal-01412408

Invited Conferences

29S. Chen, F. Bremond, H. Nguyen, H. Thomas.

Exploring Depth Information for Head Detection with Depth Images, in: AVSS 2016 - 13th International Conference on Advanced Video and Signal-Based Surveillance, Colorado Springs, United States, August 2016.

https://hal.inria.fr/hal-01414757
30F. F. Negin, S. Cosar, M. F. Koperski, C. F. Crispim-Junior, K. Avgerinakis, F. F. Bremond.

A hybrid framework for online recognition of activities of daily living in real-world settings, in: 13th IEEE International Conference on Advanced Video and Signal Based Surveillance - AVSS 2016, Colorado springs, United States, IEEE, August 2016. [ DOI : 10.1109/AVSS.2016.7738021 ]

https://hal.inria.fr/hal-01384710

International Conferences with Proceedings

31C. F. Crispim-Junior, M. Koperski, S. Cosar, F. Bremond.

Semi-supervised understanding of complex activities from temporal concepts, in: 13th International Conference on Advanced Video and Signal-Based Surveillance, Colorado Springs, United States, August 2016.

https://hal.inria.fr/hal-01398958
32E. De Maria, A. Muzy, D. Gaffé, A. Ressouche, F. Grammont.

Verification of Temporal Properties of Neuronal Archetypes Modeled as Synchronous Reactive Systems, in: HSB 2016 - 5th International Workshop Hybrid Systems Biology, Grenoble, France, Lecture Notes in Bioinformatics series, October 2016, 15 p. [ DOI : 10.1007/978-3-319-47151-8_7 ]

https://hal.inria.fr/hal-01377288
33F. M. Khan, F. Bremond.

Unsupervised data association for metric learning in the context of multi-shot person re-identification, in: Advance Video and Signal based Surveillance, Colorado Springs, United States, August 2016. [ DOI : 10.1109/AVSS.2016.7738058 ]

https://hal.inria.fr/hal-01400147
34F. Negin, J. Bourgeois, E. Chapoulie, P. Robert, F. Bremond.

Praxis and Gesture Recognition, in: The 10th World Conference of Gerontechnology (ISG 2016), Nice, France, September 2016.

https://hal.inria.fr/hal-01416372

Conferences without Proceedings

35P. Bilinski, A. Dantcheva, F. Brémond.

Can a smile reveal your gender?, in: 15th International Conference of the Biometrics Special Interest Group (BIOSIG 2016), Darmstadt, Germany, September 2016.

https://hal.archives-ouvertes.fr/hal-01387134
36E. Gonzalez-Sosa, A. Dantcheva, R. Vera-Rodriguez, J.-L. Dugelay, F. Brémond, J. Fierrez.

Image-based Gender Estimation from Body and Face across Distances, in: 23rd International Conference on Pattern Recognition (ICPR 2016): "Image analysis and machine learning for scene understanding", Cancun, Mexico, December 2016.

https://hal.archives-ouvertes.fr/hal-01384324
37M. Koperski, F. Bremond.

Modeling Spatial Layout of Features for Real World Scenario RGB-D Action Recognition, in: AVSS 2016, Colorado Springs, United States, August 2016, pp. 44 - 50. [ DOI : 10.1109/AVSS.2016.7738023 ]

https://hal.inria.fr/hal-01399037
38M. K. Phan Tran, P. Robert, F. Bremond.

A Virtual Agent for enhancing performance and engagement of older people with dementia in Serious Games, in: Workshop Artificial Compagnon-Affect-Interaction 2016, Brest, France, June 2016.

https://hal.archives-ouvertes.fr/hal-01369878
39N. Thi Lan Anh, F. Bremond, J. Trojanova.

Multi-Object Tracking of Pedestrian Driven by Context, in: Advance Video and Signal-based Surveillance, Colorado Springs, United States, IEEE, August 2016.

https://hal.inria.fr/hal-01383186

Internal Reports

40E. De Maria, A. Muzy, D. Gaffé, A. Ressouche, F. Grammont.

Verification of Temporal Properties of Neuronal Archetypes Using Synchronous Models, UCA, Inria ; UCA, I3S ; UCA, LEAT ; UCA, LJAD, July 2016, n^o RR-8937, 21 p.

https://hal.inria.fr/hal-01349019
41S. Moisan, J.-P. Rigault.

Dynamic Reconfiguration of Feature Models: an Algorithm and its Evaluation, Inria Sophia Antipolis, November 2016, n^o RR-8972, 16 p.

https://hal.inria.fr/hal-01392796

Other Publications

42C. F. Crispim-Junior, A. Konig, R. David, P. Robert, F. Bremond.

Automatic prediction of autonomy in activities of daily living of older adults, November 2016, 74s p, Short-paper.

https://hal.inria.fr/hal-01399259
43F. M. Khan, F. M. Brémond.

Person Re-identification for Real-world Surveillance Systems, November 2016, working paper or preprint.

https://hal.inria.fr/hal-01399939

References in notes

44M. Acher, P. Collet, F. Fleurey, P. Lahire, S. Moisan, J.-P. Rigault.

Modeling Context and Dynamic Adaptations with Feature Models, in: Models@run.time Workshop, Denver, CO, USA, October 2009.

http://hal.inria.fr/hal-00419990/en
45M. Acher, P. Lahire, S. Moisan, J.-P. Rigault.

Tackling High Variability in Video Surveillance Systems through a Model Transformation Approach, in: ICSE'2009 - MISE Workshop, Vancouver, Canada, May 2009.

http://hal.inria.fr/hal-00415770/en
46A. Alahi, L. Jacques, Y. Boursier, P. Vandergheynst.

Sparsity-driven people localization algorithm: Evaluation in crowded scenes environments, in: PETS workshop, 2009.
47A. Andriyenko, K. Schindler.

Multi-target tracking by continuous energy minimization, in: Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, June 2011, pp. 1265-1272. [ DOI : 10.1109/CVPR.2011.5995311 ]
48D. Arsic, A. Lyutskanov, G. Rigoll, B. Kwolek.

Multi-camera person tracking applying a graph-cuts based foreground segmentation in a homography framework, in: PETS workshop, 2009.
49K. Avgerinakis, A. Briassouli, I. Kompatsiaris.

Activity detection using sequential statistical boundary detection (ssbd), in: to appear in Computer Vision and Image Understanding, CVIU, 2015.
50S.-H. Bae, K.-J. Yoon.

Robust Online Multi-Object Tracking based on Tracklet Confidence and Online Discriminative Appearance Learning, in: CVPR, Columbus, IEEE, June 2014.
51A. Bar-Hillel, D. Levi, E. Krupka, C. Goldberg.

Part-based feature synthesis for human detection, in: ECCV, 2010.
52H. Ben Shitrit, J. Berclaz, F. Fleuret, P. Fua.

Tracking multiple people under global appearance constraints, in: IEEE International Conference on Computer Vision (ICCV), 2011, pp. 137-144.
53R. Benenson, M. Mathias, R. Timofte, L. V. Gool.

Pedestrian detection at 100 frames per second, in: CVPR, 2013.
54B. Berkin, B. K. Horn, I. Masaki.

Fast Human Detection With Cascaded Ensembles On The GPU, in: IEEE Intelligent Vehicles Symposium, 2010.
55M. D. Breitenstein, F. Reichlin, B. Leibe, E. Koller-Meier, L. van Gool.

Markovian tracking-by-detection from a single, uncalibrated camera, in: PETS workshop, 2009, pp. 71-78.
56D. P. Chau, J. Badie, F. Bremond, M. Thonnat.

Online Tracking Parameter Adaptation based on Evaluation, in: IEEE International Conference on Advanced Video and Signal-based Surveillance, Krakow, Poland, August 2013.

https://hal.inria.fr/hal-00846920
57D. P. Chau, F. Bremond, M. Thonnat.

Online evaluation of tracking algorithm performance, in: The 3rd International Conference on Imaging for Crime Detection and Prevention (ICDP), London,UK, , December 2009.

https://hal.inria.fr/inria-00486479
58D. P. Chau, M. Thonnat, F. Bremond, E. Corvee.

Online Parameter Tuning for Object Tracking Algorithms, in: Image and Vision Computing, February 2014, vol. 32, n^o 4, pp. 287-302.

https://hal.inria.fr/hal-00976594
59D. Conte, P. Foggia, G. Percannella, M. Vento.

Performance evaluation of a people tracking system on the pets video database, in: PETS workshop, 2009.
60A. D. Costea, S. Nedevschi.

Word Channel Based Multiscale Pedestrian Detection without Image Resizing and Using Only One Classifier, in: CVPR, 2014.
61N. Dalal, B. Triggs.

Histograms of oriented gradients for human detection, in: Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, IEEE, 2005, vol. 1, pp. 886–893.
62N. Dalal, B. Triggs, C. Schmid.

Human detection using oriented histograms of flow and appearance, in: European conference on computer vision, Springer, 2006, pp. 428–441.
63R. David, E. Mulin, P. Mallea, P. Robert.

Measurement of Neuropsychiatric Symptoms in Clinical Trials Targeting Alzheimer's Disease and Related Disorders, in: Pharmaceuticals, 2010, vol. 3, pp. 2387-2397.
64P. Dollar, S. Belongie, P. Perona.

The Fastest Pedestrian Detector in the West, in: BMVC, 2010.
65P. Dollar, Z. Tu, P. Perona, S. Belongie.

Integral channel features, in: BMVC, 2009.
66S. Elloumi, S. Cosar, G. Pusiol, F. Bremond, M. Thonnat.

Unsupervised discovery of human activities from long-time videos, in: IET Computer Vision, March 2015, 1 p.

https://hal.inria.fr/hal-01123895
67P. Felzenszwalb, R. Girshick, D. McAllester, D. Ramanan.

Object Detection with Discriminatively Trained Part-Based Models, in: PAMI, 2009, vol. 32, n^o 9, pp. 1627–1645.
68P. Felzenszwalb, D. McAllester, D. Ramanan.

A discriminatively trained, multiscale, deformable part model, in: CVPR, 2008.
69J. Ferryman, A. Shahrokni.

An overview of the pets2009 challenge, in: PETS, 2009.
70Q. Gao, S. Sun.

Trajectory-based human activity recognition with hierarchical Dirichlet process hidden Markov models, in: Proceedings of the 1st IEEE China Summit and International Conference on Signal and Information Processing, 2013.
71W. Hu, X. Xiao, Z. Fu, D. Xie, T. Tan, S. Maybank.

A system for learning statistical motion patterns, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, vol. 28, n^o 9, pp. 1450–1464.
72J.-F. Hu, W.-S. Zheng, J. Lai, J. Zhang.

Jointly learning heterogeneous features for RGB-D activity recognition, in: CVPR, 2015. [ DOI : 10.1109/CVPR.2015.7299172 ]
73A. Karakostas, A. Briassouli, K. Avgerinakis, I. Kompatsiaris, M. Tsolaki.

The Dem@Care Experiments and Datasets: a Technical Report, 2014.
74Y. Kong, Y. Fu.

Bilinear heterogeneous information machine for RGB-D action recognition, in: CVPR, 2015.
75H. S. Koppula, R. Gupta, A. Saxena.

Learning Human Activities and Object Affordances from RGB-D Videos, in: Int. J. Rob. Res., July 2013, vol. 32, n^o 8, pp. 951–970.

http://dx.doi.org/10.1177/0278364913478446
76H. Koppula, A. Saxena.

Learning spatio-temporal structure from rgb-d videos for human activity detection and anticipation, in: ICML, 2013.
77C. Kästner, S. Apel, S. Trujillo, M. Kuhlemann, D. Batory.

Guaranteeing Syntactic Correctness for All Product Line Variants: A Language-Independent Approach, in: TOOLS (47), 2009, pp. 175-194.
78W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed.

SSD: Single Shot MultiBox Detector, in: arXiv preprint, 2015, pp. 1–15. [ DOI : 10.1016/j.nima.2015.05.028 ]

http://arxiv.org/abs/1512.02325
79L. Liu, L. Shao.

Learning Discriminative Representations from RGB-D Video Data, in: IJCAI, 2013.
80C. Lu, J. Jia, C.-K. Tang.

Range-Sample Depth Feature for Action Recognition, in: CVPR, 2014.
81A. Milan, K. Schindler, S. Roth.

Multi-Target Tracking by Discrete-Continuous Energy Minimization, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, vol. PP, n^o 99, pp. 1-1. [ DOI : 10.1109/TPAMI.2015.2505309 ]
82S. Moisan, J.-P. Rigault, M. Acher, P. Collet, P. Lahire.

Run Time Adaptation of Video-Surveillance Systems: A software Modeling Approach, in: ICVS, 8th International Conference on Computer Vision Systems, Sophia Antipolis, France, September 2011.

http://hal.inria.fr/inria-00617279/en
83B. Morris, M. Trivedi.

Trajectory Learning for Activity Understanding: Unsupervised, Multilevel, and Long-Term Adaptive Approach, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, Nov 2011, vol. 33, n^o 11, pp. 2287-2301. [ DOI : 10.1109/TPAMI.2011.64 ]
84M. Mozaz, M. Garaigordobil, L. J. G. Rothi, J. Anderson, G. P. Crucian, K. M. Heilman.

Posture recognition in Alzheimer’s disease, in: Brain and cognition, 2006, vol. 62, n^o 3, pp. 241–245.
85T. L. A. NGUYEN, D. P. CHAU, F. Bremond.

Robust Global Tracker based on an Online Estimation of Tracklet Descriptor Reliability, in: Advanded Video and Signal-based Surveillance, Karlsruhe, Germany, August 2015.

https://hal.inria.fr/hal-01185874
86B. Ni, P. Moulin, S. Yan.

Order-Preserving Sparse Coding for Sequence Classification, in: ECCV, 2012.
87O. Oreifej, Z. Liu.

HON4D: Histogram of oriented 4D normals for activity recognition from depth sequences, in: CVPR, 2013.
88S. Ren, K. He, R. Girshick, J. Sun.

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, 2015.

https://papers.nips.cc/paper/5638-faster-r-cnn-towards-real-time-object-detection-with-region-proposal-networks.pdf
89L. M. Rocha, S. Moisan, J.-P. Rigault, S. Sagar.

Girgit: A Dynamically Adaptive Vision System for Scene Understanding, in: ICVS, Sophia Antipolis, France, September 2011.

http://hal.inria.fr/inria-00616642/en
90M. Rohrbach, M. Regneri, M. Andriluka, S. Amin, M. Pinkal, B. Schiele.

Script Data for Attribute-Based Recognition of Composite Activities, in: Computer Vision - ECCV 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part I, 2012, pp. 144–157.

http://dx.doi.org/10.1007/978-3-642-33718-5_11
91R. Romdhane, E. Mulin, A. Derreumeaux, N. Zouba, J. Piano, L. Lee, I. Leroi, P. Mallea, R. David, M. Thonnat, F. Bremond, P. Robert.

Automatic Video Monitoring system for assessment of Alzheimer's Disease symptoms, in: The Journal of Nutrition, Health and Aging Ms(JNHA), 2011, vol. JNHA-D-11-00004R1.

http://hal.inria.fr/inria-00616747/en
92L. Rybok, B. Schauerte, Z. Al-Halah, R. Stiefelhagen.

Important stuff, everywhere! Activity recognition with salient proto-objects as context, in: WACV, 2014.
93I. Sarray, A. Ressouche, D. Gaffé, J.-Y. Tigli, S. Lavirotte.

Safe Composition in Middleware for the Internet of Things, in: Middleware for Context-aware Applications for Internet of thing (M4IoT), Vancouver, Canada, December 2015. [ DOI : 10.1145/2836127.2836131 ]

https://hal.inria.fr/hal-01236976
94L. Seidenari, V. Varano, S. Berretti, A. Del Bimbo, P. Pala.

Recognizing Actions from Depth Cameras as Weakly Aligned Multi-part Bag-of-Poses, in: CVPRW, 2013.
95A. Shahroudy, G. Wang, T.-T. Ng.

Multi-modal feature fusion for action recognition in RGB-D sequences, in: ISCCSP, 2014.
96S. Tang, M. Andriluka, A. Milan, K. Schindler, S. Roth, B. Schiele.

Learning People Detectors for Tracking in Crowded Scenes, in: IEEE International Conference on Computer Vision (ICCV), December 2013.

http://www.cv-foundation.org/openaccess/content_iccv_2013/html/Tang_Learning_People_Detectors_2013_ICCV_paper.html
97S. Walk, N. Majer, K. Schindler, B. Schiele.

New features and insights for pedestrian detection, in: CVPR, 2010.
98X. Wang, T. X. Han, S. Yan.

An hog-lbp human detector with partial occlusion handling, in: ICCV, 2009.
99H. Wang, A. Kläser, C. Schmid, C.-L. Liu.

Action Recognition by Dense Trajectories, in: IEEE Conference on Computer Vision & Pattern Recognition, Colorado Springs, United States, June 2011, pp. 3169-3176.

http://hal.inria.fr/inria-00583818/en
100C. Wojek, B. Schiele.

A performance evaluation of single and multi-feature people detection, in: DAGM Symposium Pattern Recognition, 2008.
101Y. Wu.

Mining Actionlet Ensemble for Action Recognition with Depth Cameras, in: Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Washington, DC, USA, CVPR '12, IEEE Computer Society, 2012, pp. 1290–1297.

http://dl.acm.org/citation.cfm?id=2354409.2354966
102L. Xia, J. Aggarwal.

Spatio-temporal Depth Cuboid Similarity Feature for Activity Recognition Using Depth Camera, in: CVPR, 2013.
103J. Yang, Z. Shi, P. Vela, J. Teizer.

Probabilistic multiple people tracking through complex situations, in: PETS workshop, 2009.
104L. Zhang, Y. Li, R. Nevatia.

Global data association for multi-object tracking using network flows, in: Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, June 2008, pp. 1-8. [ DOI : 10.1109/CVPR.2008.4587584 ]
105Q. Zhu, S. Avidan, M. Yeh, K. Cheng.

Fast Human Detection using a Cascade of Histograms of Oriented Gradients, in: CVPR, 2006.
106Y. Zhu, W. Chen, G. Guo.

Evaluating spatiotemporal interest point features for depth-based action recognition, in: Image and Vision Computing, 2014, vol. 32, n^o 8, pp. 453 - 464. [ DOI : 10.1016/j.imavis.2014.04.005 ]

http://www.sciencedirect.com/science/article/pii/S0262885614000651

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