Robust foveal wavelet-based object tracking

Aldo Maalouf 1 Mohamed-Chaker Larabi 2
Université de Poitiers, XLIM - XLIM
Abstract : In this work, a foveal wavelet-based Mean Shift Tracking Algorithm is presented. The foveal wavelets introduced by Mallat [16] are known by their high capability to precisely characterize the holder regularity of singularities. Therefore, by using the foveal wavelet transform, image features are accurately identified and are well discriminated from noise. These wavelets are used to extract the texture features of the target object. The extracted features are then used to construct a joint color-foveal textures histogram to represent the target object. Once the joint histogram is obtained, it is applied to the mean shift framework in order to track a target object in a video sequence. The experimental results showed that the proposed approach overcomes the traditional mean shift tracking technique as well as other existing tracking algorithms.
Type de document :
Communication dans un congrès
ICASSP, Mar 2012, Kyoto, Japan. pp.1489 - 1492, 2012
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Contributeur : Mohamed-Chaker Larabi <>
Soumis le : vendredi 6 décembre 2013 - 12:53:19
Dernière modification le : jeudi 11 janvier 2018 - 06:27:03


  • HAL Id : hal-00914985, version 1



Aldo Maalouf, Mohamed-Chaker Larabi. Robust foveal wavelet-based object tracking. ICASSP, Mar 2012, Kyoto, Japan. pp.1489 - 1492, 2012. 〈hal-00914985〉



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