Journal
JOURNAL OF MATHEMATICAL IMAGING AND VISION
Volume 18, Issue 1, Pages 7-15Publisher
SPRINGER
DOI: 10.1023/A:1021837026373
Keywords
segmentation with depth; 2.1D sketch; disocclusion; variational methods; functionals with curvature; gamma convergence; nonlinear PDEs
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Given an image that depicts a scene with several objects in it, the goal of segmentation with depth is to automatically infer the shapes of the objects and the occlusion relations between them. Nitzberg, Mumford and Shiota formulated a variational approach to this problem: in their model, the solution is obtained as the minimizer of an energy. We describe a new technique of minimizing their energy that avoids explicit detection/connection of T-junctions.
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