EN FR
EN FR
STARS - 2017
STARS - 2017
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
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.

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