Abstract
This paper presents a new technique based on perceptual information for the robust segmentation of noisy 3D scenes acquired by stereo vision. A low-pass geometric filter is first applied to the given cloud of 3D points to remove noise. The tensor voting algorithm is then applied in order to extract perceptual geometric information. Finally, a graph-based segmenter is utilized for extracting the different geometric structures present in the scene through a region-growing procedure that is applied hierarchically. The proposed algorithm is evaluated on real 3D scenes acquired with a trinocular camera.
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Moreno, R., Garcia, M.A., Puig, D. (2007). Graph-Based Perceptual Segmentation of Stereo Vision 3D Images at Multiple Abstraction Levels. In: Escolano, F., Vento, M. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2007. Lecture Notes in Computer Science, vol 4538. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72903-7_14
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DOI: https://doi.org/10.1007/978-3-540-72903-7_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72902-0
Online ISBN: 978-3-540-72903-7
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