EN FR
EN FR
STARS - 2016
Overall Objectives
Bilateral Contracts and Grants with Industry
Bibliography
Overall Objectives
Bilateral Contracts and Grants with Industry
Bibliography


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, no 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, no 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, no 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, no 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, no 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, no 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, no 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, no 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, no 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, no 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, no 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, no 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, no 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, no 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, no 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, no 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, no 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, no 8, pp. 453 - 464. [ DOI : 10.1016/j.imavis.2014.04.005 ]

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