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Article Dans Une Revue Pattern Recognition Année : 2014

Leveraging Colour Segmentation for Upper-Body Detection

Résumé

This paper presents an upper-body detection algorithm that extends classical shape-based detectors through the use of additional semantic colour segmentation cues. More precisely, candidate upper-body image patches produced by a base detector are soft-segmented using a multi-class probabilistic colour segmentation algorithm that leverages spatial as well as colour prior distributions for different semantic object regions (skin, hair, clothing, background). These multi-class soft segmentation maps are then classified as true or false upper-bodies. By further fusing the score of this latter classifier with the base detection score, the method shows a performance improvement on three different public datasets and using two different upper-body base detectors, demonstrating the complementarity of the contextual semantic colour segmentation and the base detector.

Dates et versions

hal-01270720 , version 1 (08-02-2016)

Identifiants

Citer

Stefan Duffner, Jean-Marc Odobez. Leveraging Colour Segmentation for Upper-Body Detection. Pattern Recognition, 2014, 6, 47, pp.2222-2230. ⟨10.1016/j.patcog.2013.12.014⟩. ⟨hal-01270720⟩
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