Fast Image Matching with Visual Attention and SURF Descriptors

The paper describes an image matching method based on visual attention and SURF keypoints. Biologically inspired visual attention system is used to guide local interest point detection. Interest points are represented with SURF descriptors. One–to–one symmetric search is performed on descriptors to select a set of matched interest point pairs. Pairs are then weighted according to attention distribution and weights are summed up yielding a similarity score. Images are considered to be near–duplicates if similarity score exceeds a certain threshold. Experimental results illustrate high accuracy and superior computational efficiency of proposed approach in comparison with other matching techniques.