Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2011-04-12
Computer Science
Computer Vision and Pattern Recognition
Scale Space and Variational Methods 2011
Scientific paper
We demonstrate the possibility of coding parts, features that are higher level than boundaries, using a modified AT field after augmenting the interaction term of the AT energy with a non-local term and weakening the separation into boundary/not-boundary phases. The iteratively extracted parts using the level curves with double point singularities are organized as a proper binary tree. Inconsistencies due to non-generic configurations for level curves as well as due to visual changes such as occlusion are successfully handled once the tree is endowed with a probabilistic structure. The work is a step in establishing the AT function as a bridge between low and high level visual processing.
Genctav Murat
Tari Sibel
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