ARTICLE Duffner_PR_2014/IDIAP Leveraging Colour Segmentation for Upper-Body Detection Duffner, Stefan Odobez, Jean-Marc EXTERNAL http://publications.idiap.ch/attachments/papers/2014/Duffner_PR_2014.pdf PUBLIC Pattern Recognition 47 6 2222-2230 2014 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.