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A Framework for Generic State Estimation in Computer Vision Applications

Cristian Sminchisescu 1 Alexandru C Telea 2
1 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Graphisme, Vision et Robotique, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : Experimenting and building integrated, operational systems in computational vision poses both theoretical and practical challenges, involving methodologies from control theory, statistics, optimization, computer graphics, and interaction. Consequently, a control and communication structure is needed to model typical computer vision applications and a flexible architecture is necessary to combine the above mentioned methodologies in an effective implementation. In this paper, we propose a three-layer computer vision framework that offers: a) an application model able to cover a large class of vision applications; b) an architecture that maps this model to modular, flexible and extensible components by means of object-oriented and dataflow mechanisms; and c) a concrete software implementation of the above that allows construction of interactive vision applications. We illustrate how a variety of vision techniques and approaches can be modeled by the proposed framework and we present several complex, application oriented, experimental results.
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https://hal.inria.fr/inria-00590158
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Cristian Sminchisescu, Alexandru C Telea. A Framework for Generic State Estimation in Computer Vision Applications. 2nd International Workshop ICVS 2001, Jul 2001, Vancouver, Canada. pp.21--34, ⟨10.1007/3-540-48222-9_2⟩. ⟨inria-00590158⟩

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