Wide Baseline Matching Using Support Vector Regression - Haifeng Xi Haifeng Xi; Weihua Cui (TELKOMNIKA (Telecommunication Computing Electronics and Control), 2013)
In this paper, we newly solve wide baseline matching using support vector regression (SVR). High correct ratio initial matches are used to train SVR relationships, obtained by matching large-scale SIFT features and discarding some mismatches by our improved topological filtering scheme; and new matches are searched near the prediction given by trained SVR relationships. Both indoor and outdoor environments image pairs under wide baseline condition are tested, experiment results show that our algorithm automatically gain large numbers of accurate point correspondences.