Line Drawing Interpretation Using Belief Propagation
The interpretation of line drawings of trihedral planer objects is a classic problem. In this paper, it is formulated as a Bayesian inference problem. Given a line drawing image, a Markov random field can be built whose nodes represent the labels of edges. Its clique potential functions are designed to encode the valid junctions in the Huffman-Clowes catalogue. The belief propagation algorithm is used to find the most probable labeling of the edges. We find this algorithm closely related to the...[Show more]
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|Source:||A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation|
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