Direct estimation of nonrigid registrations with image-based self-occlusion reasoning

IEEE Transactions on Pattern Analysis and Machine Intelligence
Vincent Gay-BellilePatrick Sayd

Abstract

The registration problem for images of a deforming surface has been well studied. External occlusions are usually well handled. In 2D image-based registration, self-occlusions are more challenging. Consequently, the surface is usually assumed to be only slightly self-occluding. This paper is about image-based nonrigid registration with self-occlusion reasoning. A specific framework explicitly modeling self-occlusions is proposed. It is combined with an intensity-based, "direct" data term for registration. Self-occlusions are detected as shrinkage areas in the 2D warp. Experimental results on several challenging data sets show that our approach successfully registers images with self-occlusions while effectively detecting the self-occluded regions.

References

Oct 26, 1999·IEEE Transactions on Medical Imaging·D RueckertD J Hawkes
Aug 5, 2006·IEEE Transactions on Pattern Analysis and Machine Intelligence·Xiaolei HuangDimitris N Metaxas
Nov 8, 2008·IEEE Transactions on Pattern Analysis and Machine Intelligence·Adrien Bartoli

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Citations

Sep 10, 2015·IEEE Transactions on Pattern Analysis and Machine Intelligence·Adrien BartoliDaniel Pizarro
Sep 12, 2015·IEEE Transactions on Visualization and Computer Graphics·Nazim HaouchineMarie-Odile Berger
Feb 15, 2012·IEEE Transactions on Pattern Analysis and Machine Intelligence·Weiming HuZhongfei Zhang
Dec 24, 2009·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Shuhan ShenYuncai Liu
Dec 17, 2009·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Shuhan ShenYuncai Liu
Nov 4, 2015·IEEE Transactions on Visualization and Computer Graphics·Nazim HaouchineStephane Cotin
Jul 23, 2016·IEEE Transactions on Visualization and Computer Graphics·Gaku NaritaMasatoshi Ishikawa
Aug 24, 2017·Sensors·Simon DonnéWilfried Philips

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