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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Robust curb and ramp detection for safe parking using the Canesta TOF camera
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Orazio Gallo, University of California, Santa Cruz. USA
Roberto Manduchi, University of California, Santa Cruz. USA
Abbas Rafii, Canesta Inc., USA
Range sensors for assisted backup and parking have potential for saving human lives and for facilitating parking in challenging situations. However, important features such as curbs and ramps are difficult to detect using ultrasonic or microwave sensors. TOF imaging range sensors may be used successfully for this purpose. In this paper we present a study concerning the use of the Canesta TOF camera for recognition of curbs and ramps. Our approach is based on the detection of individual planar patches using CC-RANSAC, a modified version of the classic RANSAC robust regression algorithm. Whereas RANSAC uses the whole set of inliers to evaluate the fitness of a candidate plane, CC-RANSAC only considers the largest connected components of inliers. We provide experimental evidence that CC-RANSAC provides a more accurate estimation of the dominant plane than RANSAC with a smaller number of iterations.
Citation:
Orazio Gallo, Roberto Manduchi, Abbas Rafii, "Robust curb and ramp detection for safe parking using the Canesta TOF camera," cvprw, pp.1-8, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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