Project-Team Stars
Personnel
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
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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.
  • 2B. Boulay, F. Brémond, M. Thonnat.
    Applying 3D Human Model in a Posture Recognition System, in: Pattern Recognition Letter, 2006, vol. 27, no 15, pp. 1785-1796.
  • 3F. 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.
  • 4N. Chleq, F. Brémond, M. Thonnat.
    Advanced Video-based Surveillance Systems, Kluwer A.P. , Hangham, MA, USA, November 1998, pp. 108-118.
  • 5F. 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.
  • 6F. Fusier, V. Valentin, F. Brémond, 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.
  • 7B. Georis, F. Brémond, 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.
  • 8C. 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.
  • 9N. 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.
  • 10V. Martin, J.-M. Travere, F. Brémond, 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.
  • 11S. Moisan.
    Knowledge Representation for Program Reuse, in: European Conference on Artificial Intelligence (ECAI), Lyon, France, July 2002, pp. 240-244.
  • 12S. 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.
  • 13S. 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.
  • 14A. 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.
  • 15A. Ressouche, D. Gaffé.
    Compilation Modulaire d'un Langage Synchrone, in: Revue des sciences et technologies de l'information, série Théorie et Science Informatique, June 2011, vol. 4, no 30, pp. 441-471.
    http://hal.inria.fr/inria-00524499/en
  • 16M. 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.
  • 17M. 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.
  • 18M. Thonnat.
    Special issue on Intelligent Vision Systems, in: Computer Vision and Image Understanding, May 2010, vol. 114, no 5, pp. 501-502.
  • 19V. Vu, F. Brémond, M. Thonnat.
    Temporal Constraints for Video Interpretation, in: Proc of the 15th European Conference on Artificial Intelligence, Lyon, France, 2002.
  • 20V. 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.
  • 21N. Zouba, F. Brémond, 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

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 24F. C. Crispim-Junior, A. Gómez Uría, C. Strumia, M. Koperski, A. Konig, F. Negin, S. Cosar, A.-T. Nghiem, G. Charpiat, F. Bremond, D. P. Chau.
    Online recognition of daily activities by color-depth sensing and knowledge models, in: Sensors, June 2017, vol. 17, no 7, pp. 1-15. [ DOI : 10.3390/s17071528 ]
    https://hal.inria.fr/hal-01658438
  • 25A. Konig, L. Klaming, M. Pijl, A. Demeurraux, R. David, P. Robert.
    Objective measurement of gait parameters in healthy and cognitively impaired elderly using the dual-task paradigm, in: Aging Clinical and Experimental Research, December 2017, vol. 29, no 6, pp. 1181 - 1189. [ DOI : 10.1007/s40520-016-0703-6 ]
    https://hal.inria.fr/hal-01672597

International Conferences with Proceedings

  • 27C. F. Crispim-Junior, J. Vlasselaer, A. Dries, F. Bremond.
    BEHAVE - Behavioral analysis of visual events for assisted living scenarios, in: Assisted Computer Vision and Robotics workshop in conjunction with International Conference on Computer Vision, Venice, Italy, October 2017.
    https://hal.inria.fr/hal-01658665
  • 28S. DAS, M. Koperski, F. Bremond, G. Francesca.
    Action Recognition based on a mixture of RGB and Depth based skeleton, in: AVSS 2017 - 14-th IEEE International Conference on Advanced Video and Signal-Based Surveillance, Lecce, Italy, August 2017.
    https://hal.inria.fr/hal-01639504
  • 29E. De Maria, D. Gaffé, A. Ressouche, C. Girard Riboulleau.
    A Model-checking Approach to Reduce Spiking Neural Networks, in: BIOINFORMATICS 2018 - 9th International Conference on Bioinformatics Models, Methods and Algorithms, Funchal Madeira, Portugal, January 2018, pp. 1-8.
    https://hal.archives-ouvertes.fr/hal-01638248
  • 30E. De Maria, T. L 'yvonnet, D. Gaffé, A. Ressouche, F. Grammont.
    Modelling and Formal Verification of Neuronal Archetypes Coupling , in: CSBio 2017 - 8th International Conference on Computational Systems-Biology and Bioinformatics, Nha Trang, Vietnam, CSBio '17 Proceedings of the 8th International Conference on Computational Systems-Biology and Bioinformatics, ACM, December 2017, vol. 17, pp. 3-10. [ DOI : 10.1145/3156346.3156348 ]
    https://hal.inria.fr/hal-01643862
  • 31F. M. Khan, F. Bremond.
    Multi-shot Person Re-Identification Using Part Appearance Mixture, in: WACV 2017 - IEEE Winter Conference on Applications of Computer Vision, Santa Rosa, CA, United States, IEEE, March 2017, pp. 605-614. [ DOI : 10.1109/WACV.2017.73 ]
    https://hal.inria.fr/hal-01654916
  • 32N. Linz, J. Tröger, J. Alexandersson, A. Konig.
    Using Neural Word Embeddings in the Analysis of the Clinical Semantic Verbal Fluency Task, in: IWCS 2017 - 12th International Conference on Computational Semantics, Montpellier, France, September 2017, pp. 1-7.
    https://hal.inria.fr/hal-01672593
  • 33N. Linz, J. Tröger, J. Alexandersson, A. Konig, P. Robert, M. Wolters.
    Predicting Dementia Screening and Staging Scores From Semantic Verbal Fluency Performance, in: ICDM 2017 - IEEE International Conference on Data Mining, Workshop on Data Mining for Aging, Rehabilitation and Independent Assisted Living, New Orleans, United States, November 2017, pp. 719-728. [ DOI : 10.1109/ICDMW.2017.100 ]
    https://hal.inria.fr/hal-01672590
  • 34I. SARRAY, A. Ressouche, S. Moisan, J.-P. Rigault, D. Gaffé.
    An Activity Description Language for Activity Recognition, in: IINTEC 2017 - IEEE International Conference on Internet of Things, Embedded Systems and Communications, Gafsa, Tunisia, October 2017.
    https://hal.inria.fr/hal-01649674
  • 35N. Thi Lan Anh, F. M.Khan, F. Negin, F. Bremond.
    Multi-Object tracking using Multi-Channel Part Appearance Representation, in: AVSS 2017 : 14-th IEEE International Conference on Advanced Video and Signal-Based Surveillance, Lecce , Italy, August 2017.
    https://hal.inria.fr/hal-01651938
  • 36S. Yoon, F. M. Khan, F. Bremond.
    Efficient Video Summarization Using Principal Person Appearance for Video-Based Person Re-Identification, in: The British Machine Vision Conference (BMVC), London, United Kingdom, September 2017.
    https://hal.inria.fr/hal-01593238

Conferences without Proceedings

  • 37A. Dantcheva, P. Bilinski, H. T. Nguyen, J.-C. Broutart, F. Bremond.
    Expression Recognition for Severely Demented Patients in Music Reminiscence-Therapy, in: European Signal Processing Conference (EUSIPCO), Kos island, Greece, August 2017, 5 p.
    https://hal.archives-ouvertes.fr/hal-01543231

Internal Reports

  • 38I. Sarray, A. Ressouche, S. Moisan, J.-P. Rigault, D. Gaffé.
    Synchronous Automata For Activity Recognition, Inria Sophia Antipolis, April 2017, no RR-9059, STARS,MCSOC.
    https://hal.inria.fr/hal-01505754
  • 39R. Trichet, F. Bremond.
    Dataset Optimization for Real-Time Pedestrian Detection, Inria Sophia-Antipolis, June 2017, no RR-9084, 15 p.
    https://hal.inria.fr/hal-01566517

Other Publications

  • 40C. Girard Riboulleau.
    Modèles probabilistes et vérification de réseaux de neurones, Université Nice - Sophia-Antipolis, June 2017.
    https://hal.inria.fr/hal-01550133
  • 41A. Ressouche, D. Gaffé, D. Havayarimana.
    Études et développement de diagrammes de décision linéaires, UNSA, September 2017, pp. 1-36.
    https://hal.inria.fr/hal-01665717
References in notes
  • 42M. 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
  • 43M. 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
  • 44S. H. Bae, K. J. Yoon.
    Robust Online Multi-object Tracking Based on Tracklet Confidence and Online Discriminative Appearance Learning, in: 2014 CVPR, June 2014, pp. 1218-1225.
    http://dx.doi.org/10.1109/CVPR.2014.159
  • 45A. Bar-Hillel, D. Levi, E. Krupka, C. Goldberg.
    Part-based feature synthesis for human detection, in: ECCV, 2010.
  • 46R. Benenson, M. Mathias, T. Tuytelaars, L. V. Gool.
    Seeking the Strongest Rigid Detector, in: CVPR, 2013.
  • 47R. Benenson, M. Omran, J. Hosang, B. Schiele.
    Ten years of pedestrian detection, what have we learned?, in: ECCV, CVRSUAD workshop, 2014.
  • 48B. Berkin, B. K. Horn, I. Masaki.
    Fast Human Detection With Cascaded Ensembles On The GPU, in: IEEE Intelligent Vehicles Symposium, 2010.
  • 49P. Bilinski, M. Koperski, S. Bak, F. Brémond.
    Representing Visual Appearance by Video Brownian Covariance Descriptor for Human Action Recognition, in: AVSS - 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, Seoul, South Korea, IEEE, August 2014.
    https://hal.inria.fr/hal-01054943
  • 50G. Brazil, X. Yin, X. Liu.
    Illuminating Pedestrians via Simultaneous Detection & Segmentation, in: Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy, 2017.
  • 51Z. Cao, T. Simon, S.-E. Wei, Y. Sheikh.
    Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields, in: arXiv preprint arXiv:1611.08050, 2016.
  • 52Z. Cao, T. Simon, S.-E. Wei, Y. Sheikh.
    Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields, in: CVPR, 2017.
  • 53S. Chan-Lang, Q. Pham, C. Achard.
    Bidirectional Sparse Representations for Multi-Shot Person Re-identification, in: AVSS, 2016.
  • 54G. Chen, Y. Ding, J. Xiao, T. X. Han.
    Detection Evolution with Multi-Order Contextual Co-occurrence, in: CVPR, 2013.
  • 55G. Chéron, I. Laptev, C. Schmid.
    P-CNN: Pose-based CNN Features for Action Recognition, in: ICCV, 2015.
  • 56E. Corvee, F. Bremond.
    Haar like and LBP based features for face, head and people detection in video sequences, in: International Workshop on Behaviour Analysis and Video Understanding (ICVS 2011), Sophia Antipolis, France, September 2011, 10 p.
    https://hal.inria.fr/inria-00624360
  • 57A. D. Costea, S. Nedevschi.
    Word Channel Based Multiscale Pedestrian Detection without Image Resizing and Using Only One Classifier, in: CVPR, 2014.
  • 58C. 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
  • 59N. Dalal, B. Triggs.
    Histograms of oriented gradients for human detection, in: CVPR, 2005.
  • 60N. 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.
  • 61A. 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
  • 62R. 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.
  • 63E. 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
  • 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.
  • 66P. Dollár, R. Appel, W. Kienzle.
    Crosstalk Cascades for Frame-Rate Pedestrian Detection, in: ECCV, 2012.
  • 67N. Dvornik, K. Shmelkov, J. Mairal, C. Schmid.
    BlitzNet: A Real-Time Deep Network for Scene Understanding, in: IEEE International Conference on Computer Vision (ICCV), 2017.
  • 68M. Farenzena, L. Bazzani, A. Perina, V. Murino, M. Cristani.
    Person re-identification by symmetry-driven accumulation of local features, in: CVPR, 2010.
  • 69P. F. Felzenszwalb, R. B. Girshick, D. McAllester.
    Cascade object detection with deformable part models, in: CVPR, 2010.
  • 70P. 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.
  • 71P. Felzenszwalb, D. McAllester, D. Ramanan.
    A discriminatively trained, multiscale, deformable part model, in: Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, IEEE, 2008, pp. 1–8.
  • 72A. Gaidon, Z. Harchaoui, C. Schmid.
    Temporal Localization of Actions with Actoms, in: IEEE Trans. Pattern Anal. Mach. Intell., 2013, vol. 35, no 11, pp. 2782–2795.
    https://doi.org/10.1109/TPAMI.2013.65
  • 73C. Gao, J. Wang, L. Liu, J.-G. Yu, N. Sang.
    Temporally aligned pooling representation for video-based person re-identification, in: ICIP, 2016, pp. 4284–4288.
  • 74R. Girshick, J. Donahue, T. Darrell, J. Malik.
    Rich feature hierarchies for accurate object detection and semantic segmentation, in: Computer Vision and Pattern Recognition, 2014.
  • 75R. Girshick.
    Fast r-cnn, in: Proceedings of the IEEE international conference on computer vision, 2015, pp. 1440–1448.
  • 76D. Gray, H. Tao.
    Viewpoint invariant pedestrian recognition with an ensemble of localized features, in: Computer Vision–ECCV, 2008, pp. 262–275.
  • 77M. Hirzer, C. Beleznai, P. M. Roth, H. Bischof.
    Person Re-identification by Descriptive and Discriminative Classification, in: Image Analysis, Springer, 2011, pp. 91–102.
  • 78M. Hirzer, P. Roth, M. Köstinger, H. Bischof.
    Relaxed pairwise learned metric for person re-identification, in: ECCV, 2012.
  • 79S. Hochreiter, J. Schmidhuber.
    Long short-term memory, in: Neural computation, 1997, vol. 9, no 8, pp. 1735–1780.
  • 80S. Karanam, Y. Li, R. J. Radke.
    Person Re-Identification with Discriminatively Trained Viewpoint Invariant Dictionaries, in: ICCV, 2015.
  • 81W. Ke, Y. Zhang, P. Wei, Q. Ye, J. Jiao.
    Pedestrian detection via PCA filters based convolutional channel features, in: ICASSP, 2015.
  • 82M. Koperski, P. Bilinski, F. Brémond.
    3D Trajectories for Action Recognition, in: ICIP - The 21st IEEE International Conference on Image Processing, Paris, France, IEEE, October 2014.
    https://hal.inria.fr/hal-01054949
  • 83M. 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
  • 84M. Kostinger, M. Hirzer, P. Wohlhart, P. M. Roth, H. Bischof.
    Large scale metric learning from equivalence constraints, in: 2012 CVPR, June 2012, pp. 2288-2295.
    http://dx.doi.org/10.1109/CVPR.2012.6247939
  • 85C. 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.
  • 86R. Layne, T. M. Hospedales, S. Gong, Q. Mary.
    Person Re-identification by Attributes, in: Bmvc, 2012, vol. 2, no 3, 8 p.
  • 87Y. LeCun, L. Bottou, Y. Bengio, P. Haffner.
    Gradient-based learning applied to document recognition, in: Proceedings of the IEEE, 1998, vol. 86, no 11, pp. 2278–2324.
  • 88Y. Li, Z. Wu, S. Karanam, R. Radke.
    Multi-Shot Human Re-identification Using Adaptive Fisher Discriminant Analysis, in: BMVC, 2015.
  • 89S. Liao, Y. Hu, S. Z. Li.
    Joint Dimension Reduction and Metric Learning for Person Re-identification, in: CoRR, 2014, vol. abs/1406.4216.
    http://arxiv.org/abs/1406.4216
  • 90S. Liao, Y. Hu, X. Zhu, S. Z. Li.
    Person Re-identification by Local Maximal Occurrence Representation and Metric Learning, in: CVPR, 2015.
  • 91W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. E. Reed, C. Fu, A. C. Berg.
    SSD: Single Shot MultiBox Detector, in: CoRR, 2015, vol. abs/1512.02325.
    http://arxiv.org/abs/1512.02325
  • 92W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, A. C. Berg.
    SSD: Single Shot MultiBox Detector, in: ECCV, 2016.
  • 93K. Liu, W. Zhang, R. Huang.
    A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification, in: ICCV, 2015.
  • 94B. Ma, Y. Su, F. Jurie.
    Local descriptors encoded by Fisher descriptors for person re-identification, in: ECCV Workshops, 2012.
  • 95J. Marin, D. Vazquez, A. M. Lopez, J. Amores, B. Leibe.
    Random Forests of Local Experts for Pedestrian Detection, in: ICCV, 2013.
  • 96N. McLaughlin, J. M. del Rincon, P. Miller.
    Recurrent Convolutional Network for Video-based Person Re-identification, in: CVPR, 2016.
  • 97P. Mettes, J. C. van Gemert, S. Cappallo, T. Mensink, C. G. M. Snoek.
    Bag-of-Fragments: Selecting and Encoding Video Fragments for Event Detection and Recounting, in: Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, Shanghai, China, June 23-26, 2015, A. G. Hauptmann, C. Ngo, X. Xue, Y. Jiang, C. Snoek, N. Vasconcelos (editors), ACM, 2015, pp. 427–434.
    http://doi.acm.org/10.1145/2671188.2749404
  • 98S. 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
  • 99T. Ojala, M. Pietikainen, D. Harwood.
    A Comparative Study of Texture Measures with Classification Based on Feature Distributions, in: Pattern Recognition, 1996, vol. 29, no 3, pp. 51–59.
  • 100T. Ojala, M. Pietikainen, T. Maenpaa.
    Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns, in: PAMI, 2002.
  • 101D. Oneata, J. Verbeek, C. Schmid.
    The LEAR submission at Thumos 2014, HAL CCSD, 2014.
  • 102W. Ouyang, X. Wang.
    A discriminative deep model for pedestrian detection with occlusion handling, in: Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, IEEE, 2012, pp. 3258–3265.
  • 103W. Ouyang, X. Wang.
    Joint Deep Learning for Pedestrian Detection, in: ICCV, 2013.
  • 104S. Paisitkriangkrai, C. Shen, A. van den Hengel.
    Strengthening the Effectiveness of Pedestrian Detection with Spatially Pooled Features, in: ECCV, 2014.
  • 105G. Pavlakos, X. Zhou, K. G. Derpanis, K. Daniilidis.
    Coarse-to-fine volumetric prediction for single-image 3D human pose, in: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2017, pp. 1263–1272.
  • 106S. Pedagadi, J. Orwell, S. Velastin, B. Boghossian.
    Local Fisher discriminant analysis for pedestrian re-identification, in: CVPR, 2013.
  • 107L. Pishchulin, E. Insafutdinov, S. Tang, B. Andres, M. Andriluka, P. V. Gehler, B. Schiele.
    Deepcut: Joint subset partition and labeling for multi person pose estimation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 4929–4937.
  • 108F. Poiesi, R. Mazzon, A. Cavallaro.
    Multi-target tracking on confidence maps: An application to people tracking, in: Computer Vision and Image Understanding, 2013, vol. 117, no 10, pp. 1257 - 1272. [ DOI : 10.1016/j.cviu.2012.08.008 ]
    http://www.sciencedirect.com/science/article/pii/S1077314212001634
  • 109J. Redmon, A. Farhadi.
    YOLO9000: Better, Faster, Stronger, in: arXiv preprint arXiv:1612.08242, 2016.
  • 110S. Ren, K. Hen, R. Girshick, J. Sun.
    Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, in: NIPS, 2015.
  • 111L. 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
  • 112R. 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
  • 113A. Roshan Zamir, A. Dehghan, M. Shah.
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