Discriminative Learning in Biometrics
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 the...
| Main Authors: | , , |
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| Corporate Author: | |
| Language: | English |
| Published: |
Singapore :
Springer Singapore : Imprint: Springer,
2016.
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| Edition: | 1st ed. 2016. |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-981-10-2056-8 |
| Summary: | 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. . |
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| Physical Description: | XIII, 266 p. 110 illus., 73 illus. in color. online resource. |
| ISBN: | 9789811020568 |