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IVC
2006

Object detection using spatial histogram features

8 years 10 months ago
Object detection using spatial histogram features
In this paper, we propose an object detection approach using spatial histogram features. As spatial histograms consist of marginal distributions of an image over local patches, they can preserve texture and shape information of an object simultaneously. We employ Fisher criterion and mutual information to measure discriminability and features correlation of spatial histogram features. We further train a hierarchical classifier by combining cascade histogram matching and support vector machine. The cascade histogram matching is trained via automatically selected discriminative features. A forward sequential selection method is presented to construct uncorrelated and discriminative feature sets for support vector machine classification. We evaluate the proposed approach on two different kinds of objects: car and video text. Experimental results show that the proposed approach is efficient and robust in object detection. q 2006 Elsevier B.V. All rights reserved.
Hongming Zhang, Wen Gao, Xilin Chen, Debin Zhao
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2006
Where IVC
Authors Hongming Zhang, Wen Gao, Xilin Chen, Debin Zhao
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