Presentado al ICPR/2006 celebrado en Hong Kong (China). ; We present a framework for object detection that is invariant to object translation, scale, rotation, and to some degree, occlusion, achieving high detection rates, at 14 fps in color images and at 30 fps in gray scale images. Our approach is based on boosting over a set of simple local features. In contrast to previous approaches, and to efficiently cope with orientation changes, we propose the use of non-Gaussian steerable filters, together with a new orientation integral image for a speedy computation of local orientation. ; This work was supported by projects: 'Integration of robust perception, learning, and navigation systems in mobile robotics' (J-0929), 'Perception, action & cognition through learning of object-action complexes.' (4915). ; Financial support to M. Villamizar and A. Sanfeliu comes from the EURON Network Robot Systems Research Atelier NoE-507728, and the Spanish Ministry of Education and Science project NAVROBDPI 2004-05414. J. Andrade-Cetto is a Juan de la Cierva Postdoctoral Fellow of the Spanish Ministry of Education and Science under project TIC2003-09291, and is also funded in part by the EU PACO-PLUS project FP6-2004-IST-4-27657. ; Peer Reviewed
Computation of rotation local invariant features using the integral image for real time object detection
2006-01-01
Conference paper
Electronic Resource
English
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