DocumentCode :
3672415
Title :
Matching bags of regions in RGBD images
Author :
Hao Jiang
Author_Institution :
Boston College, USA
fYear :
2015
fDate :
6/1/2015 12:00:00 AM
Firstpage :
3358
Lastpage :
3366
Abstract :
We study the new problem of matching regions between a pair of RGBD images given a large set of overlapping region proposals. These region proposals do not have a tree hierarchy and are treated as bags of regions. Matching RGBD images using bags of region candidates with unstructured relations is a challenging combinatorial problem. We propose a linear formulation, which optimizes the region selection and matching simultaneously so that the matched regions have similar color histogram, shape, and small overlaps, the selected regions have a small number and overall low concavity, and they tend to cover both of the images. We efficiently compute the lower bound by solving a sequence of min-cost bipartite matching problems via Lagrangian relaxation and we obtain the global optimum using branch and bound. Our experiments show that the proposed method is fast, accurate, and robust against cluttered scenes.
Keywords :
"Image color analysis","Proposals","Shape","Histograms","Optimization","Three-dimensional displays","Yttrium"
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on
Electronic_ISBN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2015.7298957
Filename :
7298957
Link To Document :
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