A Multi Resolution Algorithm for Real-Time Foreground Objects Detection based on Codebook

Ange Mikaël Mousse (1) , Bethel Atohoun (2)

1 UP - Université de Parakou = University of Parakou
2 ESGIS - Ecole Supérieure de Gestion d'Informatique et des Sciences [Lomé]

The object detection is first step for all automatic videosurveillance system. It is also one of the most interesting, well focused and well addressed but still challenging topic in computer vision. This paper introduced a new foreground-background segmentation method based on codebook. The main objective of our proposed method is to reduce the complexity of background modeling using codebook. For this, we proposed a background modeling based on superpixels. The number of superpixels is automatically update according to the size of the foreground objects detected. We use some frame-based metrics to evaluate the proposed method. Experimental results demonstrate the performance of our proposed approach.

Mots clés: Object detection; background modeling; Superpixels; Codebook

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Ange Mikaël Mousse, Bethel Atohoun. A Multi Resolution Algorithm for Real-Time Foreground Objects Detection based on Codebook. CARI 2020 - Colloque Africain sur la Recherche en Informatique et en Mathématiques Apliquées, Oct 2020, Thiès, Senegal. ⟨hal-02926189⟩