Using support vector machines to enhance the performance of elastic graph matching for frontal face authentication

• Published in: IEEE transactions on pattern analysis and machine intelligence Vol. 23; no. 7; pp. 735 - 746
• Main Authors: Tefas, A., Kotropoulos, C., Pitas, I.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2001; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Authentication; Constraint optimization; Face recognition; Graph matching; Humans; Inequalities; Neural networks; Optimization; Pattern recognition; Performance enhancement; Polynomials; Similarity; Support vector machines; System testing

A novel method for enhancing the performance of elastic graph matching in frontal face authentication is proposed. The starting point is to weigh the local similarity values at the nodes of an elastic graph according to their discriminatory power. Powerful and well-established optimization technique...