Dominant plane detection using optical flow and independent component analysis

Authors:
Naoya Ohnishi;Atsushi Imiya
Affiliations:
School of Science and Technology, Chiba University, Japan, Chiba, Japan;Institute of Media and Information Technology, Chiba University, Japan, Chiba, Japan
Venue:
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
Year:
2005

Citing 7
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Abstract

Dominant plane is an area which occupies the largest domain in an image. A dominant plane detection is an essential task for an autonomous navigation of mobile robots equipped with a vision system, since we assume that robots move on the dominant plane. In this paper, we develop an algorithm for the dominant plane detection using optical flow and Independent Component Analysis. Since the optical flow field is a mixture of flows of the dominant plane and the other area, we separate the dominant plane using Independent Component Analysis. Using an initial data as a supervisor signal, the robot detects the dominant plane. For each image in a sequence, the dominant plane corresponds to an independent component. This relation provides us a statistical definition of the dominant plane. Experimental results using a real image sequence show that our method is robust against a non-unique velocity of the mobile robot motion.