Filtering strategy on affine invariant feature detecting based on information content and distribution constraints

Liang Cheng; Jianya Gong; Peng Han; Lei Cai

doi:10.1117/12.740252

15 November 2007 Filtering strategy on affine invariant feature detecting based on information content and distribution constraints

Liang Cheng, Jianya Gong, Peng Han, Lei Cai

Author Affiliations +

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 678609 (2007) https://doi.org/10.1117/12.740252
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Liang Cheng, Jianya Gong, Peng Han, and Lei Cai "Filtering strategy on affine invariant feature detecting based on information content and distribution constraints", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 678609 (15 November 2007); https://doi.org/10.1117/12.740252

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