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Commute time guided transformation for feature extraction
2012
Computer Vision and Image Understanding
This paper presents a random-walk-based feature extraction method called commute time guided transformation (CTG) in the graph embedding framework. The paper contributes to the corresponding field in two aspects. First, it introduces the usage of a robust probability metric, i.e., the commute time (CT), to extract visual features for face recognition via a manifold way. Second, the paper designs the CTG optimization to find linear orthogonal projections that would implicitly preserve the
doi:10.1016/j.cviu.2011.11.002
fatcat:spdplrv5ufhonm3f22m2s33tgu