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Incremental discovery of object parts in video sequences

Stéphane Drouin, Patrick Hébert and Marc Parizeau
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Abstract - This paper addresses the fundamental problem of automatically discovering an unknown moving deformable object in a monocular video sequence. No prior model of the object is used; it is only assumed that the object is composed of a set of apparently rigidparts that are not necessarily visible simultaneously, making it possible to circumvent the typical constraint of model initialization. A set of rigid parts describing the object is incrementally extracted in a modeling-tracking loop with reinforced memory. In this framework, low-level segmentation is considered as a necessary but non reliable process that helps initiating hypotheses. Motion-based layer segmentation from feature points and edges is applied only when and where no modeled parts can be tracked. Using the quantity of motion measure, it is further shown how to deal with temporal scale. The interest for this approach in applications such as human tracking is demonstrated for a set of various sequences including a rapidly evolving shape.

Bibtex:

@inproceedings{Drouin539,
author    = { Stéphane Drouin and Patrick Hébert and Marc Parizeau },
title     = { Incremental discovery of object parts in video sequences },
booktitle = { Tenth IEEE International Conference on Computer Vision. ICCV 2005. },
volume    = { 2 },
pages     = { 1754--1761 },
year      = { 2005 },
month     = { October 17-20 },
ISBN      = { 1550-5499 },
location  = { Beijing, China },
language  = { English },
web       = { http://vision.gel.ulaval.ca/~sdrouin/tracking/ }
}

Dernière modification: 2005/07/12 par sdrouin

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