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Title:
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Boosting a Biologically Inspired Local Descriptor for Geometry-free Face and Full Multi-view 3D Object Recognition |
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Author:
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Yokono, Jerry Jun; Poggio, Tomaso |
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Abstract:
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Object recognition systems relying on local descriptors are increasingly used because of their perceived robustness with respect to occlusions and to global geometrical deformations. Descriptors of this type -- based on a set of oriented Gaussian derivative filters -- are used in our recognition system. In this paper, we explore a multi-view 3D object recognition system that does not use explicit geometrical information. The basic idea is to find discriminant features to describe an object across different views. A boosting procedure is used to select features out of a large feature pool of local features collected from the positive training examples. We describe experiments on face images with excellent recognition rate. |
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URI:
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http://hdl.handle.net/1721.1/30557
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Issue Date:
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2005-07-07 |
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Keywords:
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AI, 3D multiview, object recognition, SVM and boosting classifiers |
