Abstract
This paper deals with the use of a model dedicated to human motion analysis in a video. This model has the particularity to be able to adapt itself to the current resolution or the required level of precision through possible decompositions into several hierarchical levels. The first level of the model has been described in previous works: it is region-based and the matching process between the model and the current picture is performed by the comparison of the extracted subject shape and a graphical representation of the model consisting in a set of ribbons. To proceed to this comparison, a chamfer matching algorithm is applied on those regions. Until now, the correspondence problem was treated in an independent way for each element of the model in a search area, one for each limb. No physical constraints were applied while positioning the different ribbons, as no temporal information has been taken into account. We present in this paper how we intend to introduce all those parameters in the definition of the different search areas according to positions obtained in the previous frames, distance with neighbor ribbons, and quality of previous matching.
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Fourès, T., Joly, P. (2004). Defining Search Areas to Localize Limbs in Body Motion Analysis. In: Nürnberger, A., Detyniecki, M. (eds) Adaptive Multimedia Retrieval. AMR 2003. Lecture Notes in Computer Science, vol 3094. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25981-7_10
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DOI: https://doi.org/10.1007/978-3-540-25981-7_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22163-0
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