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» Application of Level Set Methods in Computer Vision
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CVPR
2005
IEEE
16 years 13 days ago
Jensen-Shannon Boosting Learning for Object Recognition
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
Xiangsheng Huang, Stan Z. Li, Yangsheng Wang
ICCV
2005
IEEE
16 years 13 days ago
Learning the Probability of Correspondences without Ground Truth
We present a quality assessment procedure for correspondence estimation based on geometric coherence rather than ground truth. The procedure can be used for performance evaluation...
Qingxiong Yang, R. Matt Steele, David Nisté...
215
Voted
VAST
2004
ACM
16 years 7 days ago
Image-Based Registration of 3D-Range Data Using Feature Surface Elements
Digitizing real-life objects via range scanners, stereo vision or tactile sensors usually requires the composition of multiple range images. In this paper we exploit intensity ima...
Gerhard H. Bendels, Patrick Degener, Roland Wahl, ...
ECCV
2010
Springer
15 years 12 months ago
Non-Local Kernel Regression for Image and Video Restoration
This paper presents a non-local kernel regression (NL-KR) method for image and video restoration tasks, which exploits both the non-local self-similarity and local structural regul...
SCALESPACE
1999
Springer
15 years 11 months ago
Morphing Active Contours
ÐA method for deforming curves in a given image to a desired position in a second image is introduced in this paper. The algorithm is based on deforming the first image toward the...
Marcelo Bertalmío, Guillermo Sapiro, Gregor...