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Spatio-temporal segmentation and regions tracking of high definition video sequences based on a Markov Random Field model

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4 Author(s)
Brouard, O. ; CNRS, Univ. of Nantes, Nantes ; Delannay, F. ; Ricordel, V. ; Barba, D.

In this paper, we propose a Markov random field sequence segmentation and regions tracking model, which aims at combining color, texture, and motion features. First a motion-based segmentation is realized. Namely the global motion of the video sequence is estimated and compensated. From the remaining motion information, a rough motion segmentation is achieved. Then, we use a Markovian approach to update and track over time the video objects. The spatio-temporal map is updated and compensated using our Markov Random Field segmentation model to keep consistency in video objects tracking.

Published in:

Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on

Date of Conference:

12-15 Oct. 2008

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