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Content based access for a massive database of human observation video

Laurent Joyeux 1 Erika Doyle 1 Hugh Denman 1 Andy Crawsord Adrien Bousseau 2 Anil Kokaram 1 Ray Fuller 1 
2 ARTIS - Acquisition, representation and transformations for image synthesis
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : We present in this paper a CBIR system for use in a psychological study of the relationship between human movement and Dyslexia. The system allows access to up to 500 hours of video and is an example of a scientific user context. This user context requires 100% accurate indexing and retrieval for a set of specific queries. This paper presents a novel use of interactive visual and audio cues for attaining this level of indexing performance. Furthermore, the issue of motion estimation accuracy in the presence of compression artifacts is explored as part of the data integrity storage problem. In addition, content based motion analysis techniques accurate enough to parse sequences on the basis of motion and objectively evaluate that motion are investigated. The tool allows Psychologists to undertake a study that would previously be impractical and the paper presents a number of lessons gained from the ongoing work.
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Submitted on : Wednesday, October 13, 2010 - 3:56:06 PM
Last modification on : Friday, February 4, 2022 - 3:21:45 AM
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  • HAL Id : inria-00510162, version 1



Laurent Joyeux, Erika Doyle, Hugh Denman, Andy Crawsord, Adrien Bousseau, et al.. Content based access for a massive database of human observation video. MIR '04: Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval, 2004, New York, United States. pp.46 -- 52. ⟨inria-00510162⟩



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