2012 IEEE International Conference on Imaging Systems and Techniques Proceedings 2012
DOI: 10.1109/ist.2012.6295521
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A mini-batch discriminative feature weighting algorithm for LBP - Based face recognition

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Cited by 4 publications
(25 citation statements)
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“…The list of selected features is Local Binary Patterns (LBP) [15], Histograms of Oriented Gradients (HOG) [16] and HAAR-like features for face recognition [17]. The LBP is a very popular descriptor in the field of face recognition [15], [18]. The simplicity and high discriminative power of LBP in various computer vision tasks motivated the development of various extensions of the paradigm [19].…”
Section: Multimodal Face Recognition Algorithmmentioning
confidence: 99%
See 4 more Smart Citations
“…The list of selected features is Local Binary Patterns (LBP) [15], Histograms of Oriented Gradients (HOG) [16] and HAAR-like features for face recognition [17]. The LBP is a very popular descriptor in the field of face recognition [15], [18]. The simplicity and high discriminative power of LBP in various computer vision tasks motivated the development of various extensions of the paradigm [19].…”
Section: Multimodal Face Recognition Algorithmmentioning
confidence: 99%
“…The final step of the pipeline is recognition. Three recognition strategies are tested here: the most simplistic one based on Nearest Neighbor Classifier (NNC), the Weighted NNC based approach [18], [19] and Linear SVM based principle with "One-vs-All" classification scheme. The algorithmic details are discussed later.…”
Section: Multimodal Face Recognition Algorithmmentioning
confidence: 99%
See 3 more Smart Citations