State of the Art of Quality Assessment of Facial Images
The goal of the project "Facial Metrics for EES" is to develop, implement and publish an open source algorithm for the quality assessment of facial images (OFIQ) for face recognition, in particular for border control scenarios.1 In order to stimulate the harmonization of the requirements and practices applied for QA for facial images, the insights gained and algorithms developed in the project will be contributed to the current (2022) revision of the ISO/IEC 29794-5 standard. Furthermore, the implemented quality metrics and algorithms will consider the recommendations and requirements from other relevant standards, in particular ISO/IEC 19794-5:2011, ISO/IEC 29794-5:2010, ISO/IEC 39794-5:2019 and Version 5.2 of the BSI Technical Guideline TR-03121 Part 3 Volume 1. In order to establish an informed basis for the selection of quality metrics and the development of corresponding quality assessment algorithms, the state of the art of methods and algorithms (defining a metric), implementations and datasets for quality assessment for facial images is surveyed. For all relevant quality aspects, this document summarizes the requirements of the aforementioned standards, known results on their impact on face recognition performance, publicly available datasets, proposed methods and algorithms and open source software implementations.
Code (0)
등록된 구현이 없습니다.
Tasks
Face RecognitionSimilar Papers 제목 키워드 기반
Surveillance Facial Image Quality Assessment: A Multi-dimensional Dataset and Lightweight Model
Surveillance facial images are often captured under unconstrained conditions, resulting in severe quality degradation due to factors such as low resolution, motion blur, occlusion, and poor lighting. Although recent face…
Image Quality AssessmentRank-based No-reference Quality Assessment for Face Swapping
Face swapping has become a prominent research area in computer vision and image processing due to rapid technological advancements. The metric of measuring the quality in most face swapping methods relies on several dist…
Face SwappingImage Quality AssessmentNo-Reference Image Quality AssessmentNR-IQADeep Face Quality Assessment
Face image quality is an important factor in facial recognition systems as its verification and recognition accuracy is highly dependent on the quality of image presented. Rejecting low quality images can significantly i…
Face Image QualityFace Image Quality AssessmentImage Quality AssessmentAesthetics Assessment of Images Containing Faces
Recent research has widely explored the problem of aesthetics assessment of images with generic content. However, few approaches have been specifically designed to predict the aesthetic quality of images containing human…
Intelligent Frame Selection as a Privacy-Friendlier Alternative to Face Recognition
The widespread deployment of surveillance cameras for facial recognition gives rise to many privacy concerns. This study proposes a privacy-friendly alternative to large scale facial recognition. While there are multiple…
Face Image QualityFace Image Quality AssessmentFace RecognitionFace Verification+1