Gradient-based local affine invariant feature extraction for mobile robot localization in indoor environments

Authors:
Jihyo Lee;Hanseok Ko
Affiliations:
Department of Electronics and Computer Engineering, Korea University, 5ka-1 Anam-dong, Seongbuk-Gu, Seoul 136-713, Republic of Korea;Department of Electronics and Computer Engineering, Korea University, 5ka-1 Anam-dong, Seongbuk-Gu, Seoul 136-713, Republic of Korea
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

In this paper, we propose a gradient-based local affine invariant feature extraction algorithm (G-LAIFE), using affine moment invariants for robot localization in real indoor environments. The proposed algorithm is an effective feature extraction algorithm that is invariant to image translation and to 3D rotation, and it is within a partial range of the image scale. Representative performance analysis confirms that the proposed G-LAIFE algorithm significantly enhances the recognition rate and is more efficient than the scale invariant feature transform (SIFT), especially in terms of 3D rotation change and computational time.