A Tensor Voting Approach for the Hierarchical Segmentation of 3-D Acoustic Images

First International Symposium on 3D Data Processing Visualization and Transmission (3DPVT'02) p. 126
A Tensor Voting Approach for the Hierarchical Segmentation of 3-D Acoustic Images
Linmi Tao, University of Verona
Vittorio Murino, University of Verona
Gérard Medioni, University of Southern California

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TDPVT.2002.1024052
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Abstract
We present a hierarchical and robust algorithm addressing the problem of filtering and segmentation of three-dimensional acoustic images. This algorithm is based on the tensor voting approach — a unified computational framework for the inference of multiple salient structures. Unlike most previous approaches, no models or prior information of the underwater environment, nor the intensity information of acoustic images is considered in this algorithm. Salient structures and outlier noisy points are directly clustered in two steps according to both the density and the structural information of input data. Our experimental trials show promising results, very robust despite the low computational complexity.
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Citation: Linmi Tao, Vittorio Murino, Gérard Medioni, "A Tensor Voting Approach for the Hierarchical Segmentation of 3-D Acoustic Images," 3dpvt, p. 126, First International Symposium on 3D Data Processing Visualization and Transmission (3DPVT'02), 2002

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