An Experimental Comparison of Image Feature Detectors and Descriptors applied to Grid Map Matching
نویسندگان
چکیده
Applying computer vision feature detectors and descriptors to occupancy grids has important practical applications for the problem of grid map matching in mobile robot localization and mapping, although this approach has received little attention by the community. This review presents a thorough performance evaluation for several combinations of detectors (Harris, KLT, SIFT and SURF) and descriptors (SIFT, SURF and circular patches) using maps obtained from real datasets. It is shown how a combination of the Harris or KLT detector with circular patch descriptors provides the best results in both computation time and classification success ratio.
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