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Proceedings Paper

Filtering strategy on affine invariant feature detecting based on information content and distribution constraints
Author(s): Liang Cheng; Jianya Gong; Peng Han; Lei Cai
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Paper Abstract

Stereo matching is one of the most important and challenging subjects in computer vision, digital photogrammetry, and image understanding. For the purpose of wide-baseline stereo matching, a novel approach on high-quality affine invariant feature extraction is proposed. The key contribution of the novel approach is a filtering strategy for affine invariant features detecting based on information content and spatial dispersion quality constraints. The essential idea is to remove the features with low information content and bad distribution, just select the high-quality features (high information content and good distribution). Based on the filtering strategy, an automatic algorithm on high-quality affine invariant feature extraction is introduced. The experiment using image sequences with different texture conditions proves that our algorithm can get much higher repeatability than the other algorithms, which is more suitable for subsequent wide baseline stereo matching.

Paper Details

Date Published: 15 November 2007
PDF: 9 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678609 (15 November 2007); doi: 10.1117/12.740252
Show Author Affiliations
Liang Cheng, Wuhan Univ. (China)
Jianya Gong, Wuhan Univ. (China)
Peng Han, Wuhan Univ. (China)
Lei Cai, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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