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Several applications require demographic information of ordinary people inunconstrained scenarios. This is not a trivial task due to significant humanappearance variations. In this work, we introduce trixels for clustering imageregions, enumerating their advantages compared to superpixels. The classicalGrabCut algorithm is later modified to segment trixels instead of pixels in anunsupervised context. Combining with face detection lead us to a clothessegmentation approach close to real time. The study uses the challenging PascalVOC dataset for segmentation evaluation experiments. A final experimentanalyzes the fusion of clothes features with state-of-the-art genderclassifiers in ClothesDB, revealing a significant performance improvement ingender classification.

Optimized clothes segmentation to boost gender classification in unconstrained scenarios