|
|
|
|
| LEADER |
00000cam a2200000 7i4500 |
| 001 |
0000078729 |
| 005 |
20130409093000.0 |
| 008 |
120625s2011 enk eng |
| 020 |
|
|
|a 0521115965 (hardback : alk. paper)
|
| 020 |
|
|
|a 9780511921056 (ebook)
|
| 020 |
|
|
|a 9780521115964 (hardback : alk. paper)
|
| 020 |
|
|
|a 9781139099349 (ebook)
|
| 020 |
|
|
|a 9781139101363 (ebook)
|
| 050 |
0 |
0 |
|a TK7882.B56
|b M85 2011
|
| 090 |
0 |
0 |
|a TK7882.B56
|b M85 2011
|
| 245 |
0 |
0 |
|a Multibiometrics for human identification
|c edited by Bir Bhanu, Venu Govindaraju
|
| 260 |
|
|
|a Cambridge, england ;
|a New York :
|b Cambridge University Press ,
|c 2011
|
| 300 |
|
|
|a xiv, 388 p., [4] p. of plates :
|b ill. (some col.) ;
|c 24 cm.
|
| 504 |
|
|
|a Includes bibliographical references
|
| 505 |
0 |
|
|a 1. Multimodal ear and face modeling and recognition -- 2. Audio-visual speech synchrony detection by a family of bimodal linear prediction models -- 3. Multispectral contact-free palmprint recognition -- 4. Face recognition under the skin -- 5. Biometric authentication: a copula based approach -- 6. An investigation into feature level fusion of face and fingerprint biometrics -- 7. Adaptive multibiometric systems -- 8. Multiple projector camera system for three-dimensional gait recognition -- 9. Gait recognition using motion physics in a neuromorphic computing framework -- 10. Face tracking and recognition in a camera network -- 11. Bidirectional relighting for 3D aided 2D face recognition -- 12. Acquisition and analysis of a dataset comprising of gait, ear and semantic data -- 13. Dynamic security management in multibiometrics -- 14. Prediction for fusion of biometrics systems -- 15. Predicting performance in large-scale identification systems by score resampling
|
| 520 |
|
|
|a "In today's security-conscious society, real-world applications for authentication or identification require a highly accurate system for recognizing individual humans. The required level of performance cannot be achieved through the use of a single biometric such as face, fingerprint, ear, iris, palm, gait, or speech. Fusing multiple biometrics enables the indexing of large databases, more robust performance, and enhanced coverage of populations. Multiple biometrics are also naturally more robust against attacks than single biometrics. This book addresses a broad spectrum of research issues on multibiometrics for human identification, ranging from sensing modes and modalities to fusion of biometric samples and combination of algorithms. It covers publicly available multibiometrics databases, theoretical and empirical studies on sensor fusion techniques in the context of biometrics authentication, identification, and performance evaluation and prediction"-- Provided by publisher
|
| 650 |
|
0 |
|a Biometric identification
|
| 700 |
1 |
|
|a Bhanu, Bir ,
|e author
|
| 700 |
1 |
|
|a Govindaraju, Venugopal ,
|e author
|
| 999 |
|
|
|a 1000152367
|b Book
|c OPEN SHELF (30 DAYS)
|e Gong Badak Campus
|