Abstract

Local feature matching has become a commonly used method to compare images. For tracking and human detection, a reliable method for comparing images can constitute a key component for localization and loop closing tasks. two different types of image feature algorithms, Scale - Invariant Feature Transform (SIFT) and the more recent Speeded Up Robust Features (SURF), have been used to compare the images. In this paper, we propose the use of a rich set of feature descriptors based on SIFT and SURF in the different color spaces.

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