pulsar_09
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====== Ma partie du rapport d' | ====== Ma partie du rapport d' | ||
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===== Multiple Services for Device Adaptive Platform for Scenario Recognition ===== | ===== Multiple Services for Device Adaptive Platform for Scenario Recognition ===== | ||
- | ===== Participants: | + | * Participants: |
Activity recognition and monitoring systems based on multi-sensor and multi-device approaches are more and more popular to enhance events production for scenario analysis. Underlying software and hardware infrastructures can be considered as static (no changes during the overall recognition process quasi-static (no changes during two reconfigurations of the process) or really dynamic (depending on dynamic appearance and disappearance of numerous sensors and devices in the scene, communicating with the system, during recognition process). | Activity recognition and monitoring systems based on multi-sensor and multi-device approaches are more and more popular to enhance events production for scenario analysis. Underlying software and hardware infrastructures can be considered as static (no changes during the overall recognition process quasi-static (no changes during two reconfigurations of the process) or really dynamic (depending on dynamic appearance and disappearance of numerous sensors and devices in the scene, communicating with the system, during recognition process). | ||
In this last case, we need to partially and reactively adapt the application to the evolution of the environment, | In this last case, we need to partially and reactively adapt the application to the evolution of the environment, | ||
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In order to address such a challenge our researches try to federate the inherent constraints of platform devoted to action recognition, | In order to address such a challenge our researches try to federate the inherent constraints of platform devoted to action recognition, | ||
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In this axis, we propose to rely on a synchronous modeling of component behavior and component assembly to allow the usage of model checking techniques to formally validate services composition. | In this axis, we propose to rely on a synchronous modeling of component behavior and component assembly to allow the usage of model checking techniques to formally validate services composition. | ||
We began to consider this topic in 2008 through a collaborative action (SynComp) between Rainbow team at University of Nice Sophia Antipolis and INRIA Pulsar team. Within the Rainbow team, SLCA/AA experimental platform called WComp is dedicated to the reactive adaptation of applications in the domain of ubiquitous computing. During this collaboration, | We began to consider this topic in 2008 through a collaborative action (SynComp) between Rainbow team at University of Nice Sophia Antipolis and INRIA Pulsar team. Within the Rainbow team, SLCA/AA experimental platform called WComp is dedicated to the reactive adaptation of applications in the domain of ubiquitous computing. During this collaboration, | ||
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This approach allows us to benefit from model checking techniques to ensure that there are no unpredictable states of WComp components on concurrent access. This year, during his training, Vivien Fighiera (already involved in the SynComp action), has completed the theoretical work done in SynComp. He studied how to prove safety properties regarding WComp component models relying on the NuSMV [52] model checker. This year, the collaboration between Rainbow and Pulsar has been strengthened since Jean-Yves Tigli is a full time researcher at Pulsar team since September, in sabbatical year sponsored by INRIA. Now, we plan to modelize the overall assembly of WComp components with a synchronous approach to allow the usage of model checking techniques to formally validate application design. In order to obtain results based on experimental scenarios to evaluate SynComp improvements for adaptive recognition process, we plan to integrate SUP platform as a software services provider. | This approach allows us to benefit from model checking techniques to ensure that there are no unpredictable states of WComp components on concurrent access. This year, during his training, Vivien Fighiera (already involved in the SynComp action), has completed the theoretical work done in SynComp. He studied how to prove safety properties regarding WComp component models relying on the NuSMV [52] model checker. This year, the collaboration between Rainbow and Pulsar has been strengthened since Jean-Yves Tigli is a full time researcher at Pulsar team since September, in sabbatical year sponsored by INRIA. Now, we plan to modelize the overall assembly of WComp components with a synchronous approach to allow the usage of model checking techniques to formally validate application design. In order to obtain results based on experimental scenarios to evaluate SynComp improvements for adaptive recognition process, we plan to integrate SUP platform as a software services provider. | ||
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The SUP platform gathers a set of modules devoted to design applications in the domain of activity recognition. WComp is aimed at assembling services which evolve in a dynamic and heterogeneous environment. Indeed, the services provided by SUP can be seen as complex high-level services whose functionalities depend on the SUP treatments; this latter dealing with the dynamic change of the environment. Thus, considering SUP services as web services for devices for example, the devices associated with SUP services will be discovered dynamically by WComp and used with other heterogeneous devices. | The SUP platform gathers a set of modules devoted to design applications in the domain of activity recognition. WComp is aimed at assembling services which evolve in a dynamic and heterogeneous environment. Indeed, the services provided by SUP can be seen as complex high-level services whose functionalities depend on the SUP treatments; this latter dealing with the dynamic change of the environment. Thus, considering SUP services as web services for devices for example, the devices associated with SUP services will be discovered dynamically by WComp and used with other heterogeneous devices. | ||
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+ | ===== References ===== | ||
+ | |||
+ | |||
+ | [1] A. AVANZI, F. BRÉM OND, C. TORNIERI, M. THONNAT. Design and Assessment of an Intelligent Activity Monitoring Platform, in " | ||
+ | |||
+ | [2] H. BENHADDA, J. PATINO, | ||
+ | |||
+ | [3] B. BOULAY, F. BREM OND, M. THONNAT. Applying 3D Human Model in a Posture Recognition System., in | ||
+ | " | ||
+ | |||
+ | |||
+ | [4] F. BRÉMOND, M. THONNAT. Issues of Representing Context Illustrated by Video-surveillance Applications, | ||
+ | " | ||
+ | |||
+ | |||
+ | [5] Y. C. LIU, M. THONNAT. Understanding of Human Behaviors from Videos in Nursing Care Monitoring | ||
+ | Systems, in " | ||
+ | |||
+ | |||
+ | [6] N. CHLEQ, F. BRÉMOND, M. THONNAT. Image Understanding for Prevention of Vandalism in Metro Stations, in " | ||
+ | 108-118. | ||
+ | |||
+ | |||
+ | [7] V. CLÉMENT, M. THONNAT. A Knowledge-Based | ||
+ | " | ||
+ | |||
+ | |||
+ | [8] F. CUPILLARD, F. BRÉMOND, M. THONNAT. Tracking Group of People for Video Surveillance, | ||
+ | |||
+ | 34 Activity Report INRIA 2009 | ||
+ | |||
+ | |||
+ | [9] B. GEORIS, F. BREM OND, M. THONNAT. Real-Time Control of Video Surveillance Systems with Program | ||
+ | Supervision Techniques, in " | ||
+ | |||
+ | |||
+ | [10] S. LIU, P. SAINT-MARC, M. THONNAT, M. BERTHOD. Feasibility Study of Automatic Identification of | ||
+ | Planktonic Foraminifera by Computer Vision, in " | ||
+ | 1996, p. 113–123. | ||
+ | |||
+ | |||
+ | [11] N. MAILLOT, M. THONNAT, A. BOUCHER. Towards Ontology Based Cognitive Vision, in " | ||
+ | |||
+ | |||
+ | [12] S. MOISAN. Une plate-forme pour une programmation par composants de systèmes à base de connaissances, | ||
+ | |||
+ | [13] S. MOISAN, A. RESSOUCHE, J.-P. RIGAULT. Blocks, a Component Framework with Checking Facilities for | ||
+ | Knowledge-Based Systems, in " | ||
+ | 25, no 4, November 2001, p. 501-507. | ||
+ | |||
+ | |||
+ | [14] J. PATINO, H. BENHADDA, E. CORVEE, F. BREM OND, T. M.. Video-Data Modelling and Discovery, in "4th | ||
+ | IET International Conference on Visual Information Engineering VIE 2007, London, UK", 25th - 27th July | ||
+ | 2007. | ||
+ | |||
+ | |||
+ | [15] J. 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", | ||
+ | - 19th September 2007. | ||
+ | |||
+ | |||
+ | [16] M. THONNAT, M. GANDELIN. Un système expert pour la description et le classement automatique de zooplanctons à partir d’images monoculaires, | ||
+ | 1992, p. 373–387. | ||
+ | |||
+ | |||
+ | [17] M. 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", | ||
+ | |||
+ | |||
+ | [18] M. THONNAT. Vers une vision cognitive: mise en oeuvre de connaissances et de raisonnements pour l’analyse et l’interprétation | ||
+ | |||
+ | [19] M. THONNAT. Toward an Automatic Classification of Galaxies, in "The World of Galaxies", | ||
+ | 1989, p. 53-74. | ||
+ | |||
+ | |||
+ | [20] A. TOSHEV, F. BRÉMOND, M. THONNAT. An A priori-based Method for Frequent Composite Event Discovery in Videos, in " | ||
+ | |||
+ | [21] V. T. VU, F. BRÉM OND, M. THONNAT. Temporal Constraints for Video Interpretation, | ||
+ | European Conference on Artificial Intelligence, | ||
+ | |||
+ | Project-Team Pulsar 35 | ||
+ | |||
+ | |||
+ | [22] V. T. VU, F. BRÉMOND, M. THONNAT. Automatic Video Interpretation: | ||
+ | |||
+ | Year Publications | ||
+ | |||
+ | Doctoral Dissertations and Habilitation Theses | ||
+ | |||
+ | [23] M.-B. KAÂNICHE. Human Gesture Recognition from video sequences, Ph. D. Thesis, Université de Nice | ||
+ | Sophia-Antipolis, | ||
+ | |||
+ | |||
+ | [24] T.-L. LE. Indexation et Recherche de Vidéo pour la Vidéo Surveillance, | ||
+ | Sophia-Antipolis, | ||
+ | |||
+ | |||
+ | [25] P. VERNET. Interprétation géologique de données sismiques par une méthode supervisée basée sur la vision cognitive, Ph. D. Thesis, Ecole Nationale Supérieure des Mines de Paris, September 2009. | ||
+ | |||
+ | Articles in International Peer-Reviewed Journal | ||
+ | |||
+ | [26] T.-L. LE, M. THONNAT, A. BOUCHER, F. BRÉMOND. Surveillance video indexing and retrieval using objet features and semantic events, in " | ||
+ | |||
+ | [27] J.-Y. TIGLI, S. LAVIROTTE, G. REY, V. HOURDIN, D. CHEUNG, E. CALLEGARI, M. RIVEILL. WComp middleware for ubiquitous computing: Aspects and composite event-based Web services, in " | ||
+ | Telecommunications", | ||
+ | |||
+ | |||
+ | [28] J.-Y. TIGLI, S. LAVIROTTE, G. REY, V. HOURDIN, M. RIVEILL. Lightweight Service Oriented Architecture for Pervasive Computing, in "IJCSI International Journal of Computer Science Issues", | ||
+ | 0784 ISSN (Print): 1694-0814, vol. 4, no 1, 2009. | ||
+ | |||
+ | |||
+ | [29] N. ZOUBA, F. BRÉMOND, M. THONNAT, A. ANFOSSO, E. PASCUAL, P. MALLEA, V. MAILLAND, O. | ||
+ | GUERIN. A computer system to monitor older adults at home: Preliminary results, in "The Gerontechnology | ||
+ | Journal: Official Journal of the International Society for Gerontechnology", | ||
+ | |||
+ | International Peer-Reviewed Conference/ | ||
+ | |||
+ | [30] M. ACHER, P. COLLET, F. FLEUREY, P. LAHIRE, S. MOISAN, J.-P. RIGAULT. Modeling Context and | ||
+ | Dynamic Adaptations with Feature | ||
+ | 2009. | ||
+ | |||
+ | |||
+ | [31] M. ACHER, P. LAHIRE, S. MOISAN, J.-P. RIGAULT. Tackling High Variability in Video Surveillance Systems through a Model Transformation Approach, in " | ||
+ | 2009. | ||
+ | |||
+ | |||
+ | [32] S. BAK, S. SURESH, E. CORVÉE, F. BRÉMOND, M. THONNAT. Fusion of motion segmentation and learning based tracker for visual surveillance, | ||
+ | |||
+ | 36 Activity Report INRIA 2009 | ||
+ | |||
+ | |||
+ | [33] P. BILINSKI, | ||
+ | |||
+ | [34] C. CARINCOTTE, F. BRÉMOND, J.-M. ODOBEZ, L. PATINO, B. RAVERA, X. DESURM ONT. Multimedia | ||
+ | Knowledge-Based Content Analysis over Distributed Architecture, | ||
+ | 2009 NEM Summit - " | ||
+ | |||
+ | |||
+ | [35] G. CHARPIAT. Learning Shape Metrics based on Deformations and Transport, in " | ||
+ | 2009 and its Workshops, Second Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment | ||
+ | (NORDIA), Kyoto, Japan", | ||
+ | |||
+ | |||
+ | [36] D.-P. CHAU, F. BRÉM OND, E. CORVÉE, M. THONNAT. Online evaluation of tracking algorithm perfor- mance, in "The 3rd International Conference on Imaging for Crime Detection and Prevention, London, United Kingdom", | ||
+ | |||
+ | [37] D.-P. CHAU, F. BRÉMOND, E. CORVÉE, M. THONNAT. Repairing People Trajectories Based on Point Clustering, in "The International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP), Lisbon, Portugal", | ||
+ | |||
+ | [38] E. CORVÉE, F. BRÉM OND. Combining face detection and people tracking in video surveillance, | ||
+ | |||
+ | [39] C. GARATE, P. BILINSKI, F. BRÉMOND. Crowd Event Recognition Using HOG Tracker, in " | ||
+ | |||
+ | [40] V. HOURDIN, J.-Y. TIGLI, S. LAVIROTTE, M. RIVEILL. Context-Sensitive Authorization for Asynchronous Communications, | ||
+ | |||
+ | [41] M.-B. KAÂNICHE, F. BRÉMOND. Tracking HOG Descriptors for Gesture Recognition, | ||
+ | September 2009. | ||
+ | |||
+ | |||
+ | [42] V. MARTIN, F. BRÉMOND, J.-M. TRAVERE, V. MONCADA, G. DUNAND. Thermal Event Recognition Ap- plied to Tokamak Protection during Plasma Operation, in "IEEE International Instrumentation and Measure- ment Technology Conference", | ||
+ | |||
+ | [43] S. MOISAN, J.-P. RIGAULT. Teaching Object-Oriented Modeling and UML to Various Audiences, in "MOD- ELS’09 Educators’ Symposium, Denver, CO, USA", best paper award, October 2009. | ||
+ | |||
+ | [44] A.-T. NGHIEM, F. BRÉMOND, M. THONNAT. Controlling Background Subtraction Algorithms for Robust Object Detection, in "The 3rd International Conference on Imaging for Crime Detection and Prevention, London, United Kingdom", | ||
+ | |||
+ | Project-Team Pulsar 37 | ||
+ | |||
+ | |||
+ | [45] G. PUSIOL, F. BRÉMOND, M. THONNAT. Trajectory-based Primitive Events for Learning and Recognizing Activity, in " | ||
+ | |||
+ | [46] R. ROMDHANE, F. BRÉMOND, M. THONNAT. Handling Uncertainty for Video Event Recognition, | ||
+ | 3rd International Conference on Imaging for Crime Detection and Prevention, London, United Kingdom", | ||
+ | December 2009. | ||
+ | |||
+ | |||
+ | [47] M. SIALA, N. KHLIFA, F. BRÉM OND, K. HAMROUNI. People Detection in Complex Scene Using a Cascade of Boosted Classifiers based on Haar-like-features, | ||
+ | |||
+ | [48] N. ZOUBA, F. BRÉMOND, M. THONNAT, A. ANFOSSO, E. PASCUAL, P. MALLEA, V. MAILLAND, O. | ||
+ | GUERIN. Assessing Computer Systems for the Real Time Monitoring of Elderly People Living at Home, in | ||
+ | "The 19th IAGG World Congress of Gerontology and Geriatrics (IAGG), Paris, France", | ||
+ | |||
+ | |||
+ | [49] N. ZOUBA, F. BRÉMOND, M. THONNAT. Multisensor Fusion for Monitoring Elderly Activities at Home, in "The 6th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Genoa, Italy", | ||
+ | |||
+ | [50] M. ZUNIGA, F. BRÉMOND, M. THONNAT. Incremental Video Event Learning, in " | ||
+ | IEEE International Conference on Computer Vision Systems, Liege Belgium", | ||
+ | |||
+ | Scientific Books (or Scientific Book chapters) | ||
+ | |||
+ | [51] G. CHARPIAT, I. BEZRUKOV, Y. ALTUN, M. HOFMANN, B. SCHÖLKOPF. Machine Learning Methods for Automatic Image Colorization, | ||
+ | |||
+ | References in notes | ||
+ | |||
+ | [52] A. CIMATTI, E. CLARKE, E. GIUNCHIGLIA, | ||
+ | Copenhagen, Danmark", | ||
+ | 2002, p. 359-364, http:// | ||
+ | |||
+ | |||
+ | [53] N. DALAL, B. TRIGGS. Histograms of Oriented Gradients for Human Detection, in "CVPR, San Diego, CA, USA", vol. 1, IEEECSP, June 20-25 2005, p. 886–893, http:// | ||
+ | |||
+ | [54] ECVISION. A Research Roadmap of Cognitive Vision, Technical report, no IST-2001-35454, | ||
+ | 2005. | ||
+ | |||
+ | |||
+ | [55] F. FLEUREY, A. SOLBERG. A Domain Specific Modeling Language Supporting Specification, | ||
+ | Execution of Dynamic Adaptive Systems, in " | ||
+ | |||
+ | |||
+ | [56] D. GAFFÉ, A. RESSOUCHE. The Clem Toolkit, in " | ||
+ | |||
+ | 38 Activity Report INRIA 2009 | ||
+ | |||
+ | |||
+ | [57] N. HALBWACHS, F. LAGNIER, P. RAYM OND. Synchronous observers and the verification of reactive systems, in "Third Int. Conf. on Algebraic Methodology and Software Technology, AMAST’93, Twente", | ||
+ | |||
+ | [58] C. KÄSTNER, S. APEL, S. TRUJILLO, M. KUHLEM ANN, D. BATORY. Guaranteeing Syntactic Correctness for All Product Line Variants: A Language-Independent Approach, in "TOOLS (47)", 2009, p. 175-194. | ||
+ | |||
+ | [59] A. RESSOUCHE, D. GAFFÉ, V. ROY. Modular Compilation of a Synchronous Language, Research Report, no | ||
+ | 6424, INRIA, 01 2008, https:// | ||
+ | |||
+ | |||
+ | [60] A. RESSOUCHE, D. GAFFÉ, V. ROY. Modular Compilation of a Synchronous Language, in " | ||
+ | |||
+ | [61] E. ROSTEN, T. DRUM MOND. Machine learning for high-speed corner detection, in "ECCV, Graz, Austria", | ||
+ | |||
+ | [62] T. STAHL, M. VOELTER. Model-driven Software Development: | ||
+ | |||
pulsar_09.1262868089.txt.gz · Dernière modification : 2010/01/07 12:41 de tigli