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Template Matching with Deformable Diversity Similarity

2019-12-04 | |  41 |   38 |   0
Abstract We propose a novel measure for template matching named Deformable Diversity Similarity – based on the diversity of feature matches between a target image window and the template. We rely on both local appearance and geometric information that jointly lead to a powerful approach for matching. Our key contribution is a similarity measure, that is robust to complex deformations, significant background clutter, and occlusions. Empirical evaluation on the most up-to-date benchmark shows that our method outperforms the current state-of-the-art in its detection accuracy while improving computational complexity

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