Randomized Voting-based Rigid-body Motion Segmentation

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In this paper, we propose a novel rigid-body motion segmentation algorithm that uses randomized voting (RV) to assign high scores to correctly estimated models and low scores to wrongly estimated models. This algorithm is based on an epipolar geometrical representation of the camera motion, and computes scores using the distance between the feature point and the corresponding epipolar line. These scores are accumulated and utilized for motion segmentation. To evaluate the efficacy of our algorithm, we conduct a series of experiments using the Hopkins 155 dataset and the UdG dataset, which are representative test sets for rigid motion segmentation. Among several state-of-theart datasets, our algorithm achieves the most accurate motion segmentation results and, in the presence of measurement noise, achieves comparable results to the other algorithms. Finally, we analyze why our motion segmentation algorithm works using probabilistic and theoretical analysis.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2019-03
Language
English
Article Type
Article
Citation

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, v.29, no.3, pp.1 - 1

ISSN
1051-8215
DOI
10.1109/tcsvt.2018.2805838
URI
http://hdl.handle.net/10203/254133
Appears in Collection
EE-Journal Papers(저널논문)
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