Multi-view Face Recognition with Min-Max Modular SVMs

• Published in: Advances in Natural Computation pp. 396 - 399
• Main Authors: Fan, Zhi-Gang, Lu, Bao-Liang
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Face Recognition; Face Recognition Technique; Module Combination; Multiclass Support Vector Machine; Pattern recognition. Digital image processing. Computational geometry; Task Decomposition; Statistical analysis; Face recognition; Image processing; Pattern classification; Facies; Minimax method; Vector support machine; Pattern recognition

Through task decomposition and module combination, min-max modular support vector machines (M3-SVMs) can be successfully used for difficult pattern classification task. M3-SVMs divide the training data set of the original problem to several sub-sets, and combine them to a series of sub-problems whic...