Adaptive and fast scale invariant feature extraction

The Scale Invariant Feature Transform, SIFT, has been successfully applied to robot vision, object recognition, motion estimation, etc. Still, the parameter settings are not fully investigated, especially when dealing with variable lighting conditions. In this work, we propose a SIFT improvement that allows feature extraction and matching between images taken under different illumination. Also an interesting approach to reduce the SIFT computational time is presented. Finally, results of robot vision based localization experiments using the proposed approach are presented.