Face Image Quality Assessment: A Literature Survey

نویسندگان

چکیده

The performance of face analysis and recognition systems depends on the quality acquired data, which is influenced by numerous factors. Automatically assessing data in terms biometric utility can thus be useful to detect low-quality make decisions accordingly. This survey provides an overview image assessment literature, predominantly focuses visible wavelength input. A trend towards deep learning based methods observed, including notable conceptual differences among recent approaches, such as integration into models. Besides selection, also used a variety other application scenarios, are discussed herein. Open issues challenges pointed out, i.a. highlighting importance comparability for algorithm evaluations, challenge future work create approaches that interpretable addition providing accurate predictions.

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ژورنال

عنوان ژورنال: ACM Computing Surveys

سال: 2022

ISSN: ['0360-0300', '1557-7341']

DOI: https://doi.org/10.1145/3507901