Triangle-Constraint for Finding More Good Features

We present a novel method for finding more good feature pairs between two sets of features. We first select matched features by Bi-matching method as seed points, then organize these seed points by adopting the Delaunay triangulation algorithm. Finally, we use Triangle-Constraint (T-C) to increase both number of correct matches and matching score (the ratio between number of correct matches and total number of matches). The experimental evaluation shows that our method is robust to most of geometric and photometric transformations including rotation, scale change, blur, viewpoint change, JPEG compression and illumination change, and significantly improves both number of correct matches and matching score.

• Type: Conference
• Year: 2010
• Where: ICPR
• Authors: Xiaojie Guo, Xiaochun Cao
• Keywords: Computer Vision, Correct Matches, Delaunay Triangulation Algorithm, ICPR 2010, Seed Points