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Saliency-guided integration of multiple scans

Song, Ran, Liu, Yonghuai, Martin, Ralph Robert and Rosin, Paul L. 2012. Saliency-guided integration of multiple scans. Presented at: IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, 16-21 June 2012. Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. pp. 1474-1481. 10.1109/CVPR.2012.6247836

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Abstract

We present a novel method to integrate multiple 3D scans captured from different viewpoints. Saliency information is used to guide the integration process. The multi-scale saliency of a point is specifically designed to reflect its sensitivity to registration errors. Then scans are partitioned into salient and non-salient regions through an Markov Random Field (MRF) framework where neighbourhood consistency is incorporated to increase the robustness against potential scanning errors. We then develop different schemes to discriminatively integrate points in the two regions. For the points in salient regions which are more sensitive to registration errors, we employ the Iterative Closest Point algorithm to compensate the local registration error and find the correspondences for the integration. For the points in non-salient regions which are less sensitive to registration errors, we integrate them via an efficient and effective point-shifting scheme. A comparative study shows that the proposed method delivers improved surface integration.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: MRF framework , Markov random field framework , effective point-shifting scheme , iterative closest point algorithm , local registration error compensation , multiscale saliency , neighbourhood consistency , nonsalient regions , potential scanning errors , registration error sensitivity , saliency information , saliency-guided multiple 3D scan integration method
ISBN: 9781467312264
Last Modified: 04 Jun 2017 04:17
URI: http://orca.cf.ac.uk/id/eprint/36108

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