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Biometric Indexing

Dept. of Computer Science (January 13, 2017)

CONFERENCE / SYMPOSIUM : IAPR/IEEE Winter School on Biometrics

Biometric Data Analysis
Multimodal Biometrics with Auxiliary Information: Quality, User-specific, ...
2D and 3D Face Recognition
Human Identification via Gait Recognition
Hand-Based Biometrics
Recent Progress of Iris Recognition
Mobile Biometrics: Trends and Issues
Deep Learning in Face Analysis
Fingerprint Recognition
Machine Learning for Person Identification
Soft Biometrics and Continuous Authentication
Secure Scalable CCTV, Mobile, and Wearable Video Face Recognition
Biometric Indexing
Face Recognition System Security: Template Protection and Anti-spoofing
MAJOR SPEAKER : Wang, Alice Yi
LENGTH : 103 min.
ACCESS : Open to all
SUMMARY : Biometric identification systems typically require one-to-many comparisons by evaluating the biometric similarity between an input query and the database records. With increasing data volume and access demand, it is necessary to develop effective and efficient methods that can help to narrow the search range and reduce the matching complexity for computationally intensive tasks such as identity de-duplication and identification based on secured templates. Biometric indexing is designed to address the problem by assigning an index vector to every identity in the database, with the aim of fast retrieving a small number of candidate identities for matching. This talk will discuss problems and recent developments of biometric indexing from three aspects, namely, accuracy, efficiency and privacy. In particular, examples of hash-based indexing methods will be provided for biometric identification.  [Go to the full record in the library's catalogue]

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