Yong Xu - Böcker

It takes a big step toward practical facial beauty analysis, proposes more reliable and stable facial features for beauty analysis and designs new models, methods, algorithms and schemes while implementing a facial beauty analysis and beautification system.

Recognition, CCBR 2017, held in Shenzhen, China, in October 2017. The 15 full papers and 65 poster papers presented in this book were carefully reviewed and selected from 138 submissions. The papers are organized in topical sections on face; fingerprint, palm-print and vascular biometrics; feature extraction and classification theory;

It takes a big step toward practical facial beauty analysis, proposes more reliable and stable facial features for beauty analysis and designs new models, methods, algorithms and schemes while implementing a facial beauty analysis and beautification system.

This monograph describes the latest advances in discriminative learning methods for biometric recognition. Specifically, it focuses on three representative categories of methods: sparse representation-based classification, metric learning, and discriminative feature representation, together with their applications in palmprint authentication, face recognition and multi-biometrics. The ideas, algorithms, experimental evaluation and underlying rationales are also provided for a better understanding of these methods. Lastly, it discusses several promising research directions in the field of discriminative biometric recognition.