Periocular biometrics: databases, algorithms and directions
원문 초록
Periocular biometrics has been established as an independent modality due to concerns on the performance of iris or face systems in uncontrolled conditions. Periocular refers to the facial region in the eye vicinity, including eyelids, lashes and eyebrows. It is available over a wide range of acquisition distances, representing a trade-off between the whole face (which can be occluded at close distances) and the iris texture (which do not have enough resolution at long distances). Since the periocular region appears in face or iris images, it can be used also in conjunction with these modalities. Features extracted from the periocular region have been also used successfully for gender classification and ethnicity classification, and to study the impact of gender transformation or plastic surgery in the recognition performance. This paper presents a review of the state of the art in periocular biometric research, providing an insight of the most relevant issues and giving a thorough coverage of the existing literature. Future research trends are also briefly discussed.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
YARE-GAN: Yet Another Resting State EEG-GAN
VANPY: Voice Analysis Framework
Graph Contrastive Learning for Connectome Classification
OSUM: Advancing Open Speech Understanding Models with Limited Resources in Academia
BN-AuthProf: Benchmarking Machine Learning for Bangla Author Profiling on Social Media Texts
GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in Explanations
토론
이 논문과 연결된 포럼 글이 아직 없습니다.