2,085 research outputs found
Face Image Quality Assessment: A Literature Survey
The performance of face analysis and recognition systems depends on the
quality of the acquired face data, which is influenced by numerous factors.
Automatically assessing the quality of face data in terms of biometric utility
can thus be useful to detect low-quality data and make decisions accordingly.
This survey provides an overview of the face image quality assessment
literature, which predominantly focuses on visible wavelength face image input.
A trend towards deep learning based methods is observed, including notable
conceptual differences among the recent approaches, such as the integration of
quality assessment into face recognition models. Besides image selection, face
image quality assessment can also be used in a variety of other application
scenarios, which are discussed herein. Open issues and challenges are pointed
out, i.a. highlighting the importance of comparability for algorithm
evaluations, and the challenge for future work to create deep learning
approaches that are interpretable in addition to providing accurate utility
predictions
Biometric Systems
Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study
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