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2006
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Acoustic Range Image Segmentation by Effective Mean Shift

10 years 11 months ago
Acoustic Range Image Segmentation by Effective Mean Shift
Image perception in underwater environment is a difficult task for a human operator, and data segmentation becomes a crucial step toward an higher level interpretation and recognition of the observing scenarios. This paper contributes to the related state of the art, by fitting the mean shift clustering paradigm to the segmentation of acoustical range images, providing a segmentation approach in which whatever parameter tuning is absent. Moreover, the method exploits actively the connectivity information provided by the range map, by using reverse projection as acceleration technique. Therefore, the method is able to produce, starting from raw range data, meaningful segmented clouds of points in a fully automatic and efficient fashion.
Umberto Castellani, Marco Cristani, Vittorio Murin
Added 22 Oct 2009
Updated 22 Oct 2009
Type Conference
Year 2006
Where ICIP
Authors Umberto Castellani, Marco Cristani, Vittorio Murino
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