Feature matching in omnidirectional images with a large sensor motion for map generation of a mobile robot

Authors:
Young Jin Lee;Do-Yoon Kim;Myung Jin Chung
Affiliations:
Department of Electrical Engineering and Computer Science, KAIST, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, South Korea;Department of Electrical Engineering and Computer Science, KAIST, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, South Korea;Department of Electrical Engineering and Computer Science, KAIST, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, South Korea
Venue:
Pattern Recognition Letters
Year:
2004

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Abstract

This paper deals with a matching problem of finding correspondences of features in two omnidirectional images. To produce reliable matching results even though there are large translation and rotation of a sensor, we proposed a method that combines the advantages of sum of squared difference (SSD) and dynamic time warping (DTW). Dominant corresponding feature pairs are found using a proximity matrix and an SSD-based similarity matrix, and then the remaining feature matching is accomplished by DTW. Experimental results show that a zero failure rate of matching can be achieved in an indoor environment if the baseline is less than 20 cm.