Abstract
Dominant plane is an area which occupies the largest domain in an image. Estimation of the dominant plane is an essential task for the autonomous navigation and the path planning of the mobile robot equipped with a vision system, since the robot moves on the dominant plane. In this paper, we develop an algorithm for dominant plane detection using optical flow and Independent Component Analysis(ICA). Since the optical flow field is a mixture of flows of the dominant plane and the other area, we separate the dominant plane using ICA. Using the 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 real image sequence show that our method is robust against a perturbation of the motion speed of robots.
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Ohnishi, N., Imiya, A. (2005). Dominant Plane Detection Using Optical Flow and Independent Component Analysis. In: De Gregorio, M., Di Maio, V., Frucci, M., Musio, C. (eds) Brain, Vision, and Artificial Intelligence. BVAI 2005. Lecture Notes in Computer Science, vol 3704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11565123_47
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DOI: https://doi.org/10.1007/11565123_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29282-1
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