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This paper presents a technique for shape-based recognition that fuses pixellevel and object-level approaches into a unified framework. A pixel-level algorithm classifies individual pixels as belonging to a target object or clutter based on automatically-selected shape features computed in a spatial arrangement around them; an object-level algorithm classifies object-sized rectangular image regions as objects or clutter by aggregating pixel classifier scores in the regions. We train a cascadedoi:10.5244/c.18.99 dblp:conf/bmvc/CarmichaelH04 fatcat:bpo3baapi5cxpb67pnqgeanz2e