Sparse graphical representation based discriminant analysis for heterogeneous face recognition
•We propose an adaptive sparse graphical representation scheme to represent heterogeneous face images. By skipping the K nearest neighbor selection process, adaptive sparse vectors can be generated from the Markov networks model, which is evaluated to be much more effective for heterogeneous face re...
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Published in | Signal processing Vol. 156; pp. 46 - 61 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.03.2019
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Subjects | |
Online Access | Get full text |
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