Free Space Detection from Catadioptric Omnidirectional Images for Visual Navigation using Optical Flow

Abstract : In this paper, we develop a free space detection algorithm for the visual navigation of the autonomous robot mounting a catadioptiric omnidirectional imaging system. The algorithm detects the dominant plane as the free space from a sequence of omnidirectional images cap- tured by a camera mounted on the autonomous robot. The dominant plane, which can be detected from the optical-flow field, is the largest planar area in the image. For the detection of the dominant plane from the optical-flow field, we adopt the motion separation property, that is, the optical-flow vector is decomposed into infinitesimal rotation, translation, and divergent motions on the images. The algorithm matches the measured translation optical-flow field with the template translation optical-flow field to separate the dominant-plane as the free space for the navigation and the obstacle area. The template optical-flow field is generated from a preobserved image sequence without any calibration of the internal parameters of both the robot and camera.
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Wataru Yoshizaki, Yoshihiko Mochizuki, Naoya Ohnishi, Atsushi Imiya. Free Space Detection from Catadioptric Omnidirectional Images for Visual Navigation using Optical Flow. The 8th Workshop on Omnidirectional Vision, Camera Networks and Non-classical Cameras - OMNIVIS, Rahul Swaminathan and Vincenzo Caglioti and Antonis Argyros, Oct 2008, Marseille, France. ⟨inria-00325322⟩

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