NDLI: A hybrid algorithm combined color feature and keypoints for object detection

Content Provider	IEEE Xplore Digital Library
Author	Peiliang Wu Lingfu Kong Xianshan Li Kaiyuan Fu
Copyright Year	2008
Description	Author affiliation: Coll. of Inf. Sci. & Eng., Yanshan Univ., Qinhuangdao (Peiliang Wu; Lingfu Kong; Xianshan Li)
Abstract	Object detecting methods based on local keypoints have shown stable and effective performance to detect object in clutter and occlusion environment, but these methods usually ignore color region information which is useful for object to distinguish it from background and other objects. To improve the veracity and celerity of object detection under clutter, we present a new approach for object detection with the basic idea of multi-features unity. Firstly, we define a novel color region descriptor called object dominant color set (ODCS). Then use an indirect approach combining ODCS region-based detection and scale invariant feature transform (SIFT) keypoint-based detection in an ordinal coarse-to-fine manner. At last, introduce a voting mechanism to decide the final detection result. The proposed approach has both the celerity of color region-based detector and veracity of keypoint-based detector concurrently, and is more effective to detect objects of few keypoints. The experimental data illuminate the potential of the proposed approach.
Starting Page	1408
Ending Page	1412
File Size	638786
Page Count	5
File Format	PDF
ISBN	9781424417179
DOI	10.1109/ICIEA.2008.4582750
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-03
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article

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