Buch, Englisch, 206 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 500 g
Buch, Englisch, 206 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 500 g
Reihe: Advances in Computer Vision and Pattern Recognition
ISBN: 978-1-84800-128-2
Verlag: Springer
Biometrics deal with recognition of individuals based on their physiological or behavioural characteristics. Researchers have done extensive studies on biometrics such as fingerprint, face, palm print, iris and gait. Ear, a viable new class of biometrics, has certain advantages over face and fingerprint, which are the two most common biometrics in both academic research and industrial applications.
This book explores all aspects of 3D ear recognition: representation, detection, recognition, indexing and performance prediction. It uses large datasets to quantify and compare the performance of various techniques.
Features and topics include: Ear detection and recognition in 2D image - 3D object recognition and 3D biometrics - 3D ear recognition - Performance comparison and prediction.
The techniques discussed will be of great interest to researchers, developers and decision makers who are involved in robust human recognition by computer for a large number of practical applications.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Datensicherheit, Datenschutz
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Grafikprogrammierung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein EDV & Informatik: Ausbildung & Berufe
- Naturwissenschaften Biowissenschaften Biowissenschaften
Weitere Infos & Material
Introduction.- Ear Detection and Recognition in 2D Images.- 3D Object Recognition and 3D Biometrics.- 3D Ear Detection.- Recognizing 3D Ears Using Helix/Anti-helix.- Recognizing 3D Ears using Local Surface Patches.- Rapid 3D Ear Indexing and Recognition.- Performance Comparison and Prediction.- Conclusion and Future Work.