Boosting Multi-modal Ocular Recognition via Spatial Feature Reconstruction and Unsupervised Image Quality Estimation

doi:10.1007/s11633-023-1415-y

CASIA OpenIR > 学术期刊 > Machine Intelligence Research

	Boosting Multi-modal Ocular Recognition via Spatial Feature Reconstruction and Unsupervised Image Quality Estimation
	Zihui Yan1 ; Yunlong Wang1 ; Kunbo Zhang1 ; Zhenan Sun1 ; Lingxiao He2
发表期刊	Machine Intelligence Research
ISSN	2731-538X
	2024
卷号	21 期号:1 页码:197-214
摘要	In the daily application of an iris-recognition-at-a-distance (IAAD) system, many ocular images of low quality are acquired. As the iris part of these images is often not qualified for the recognition requirements, the more accessible periocular regions are a good complement for recognition. To further boost the performance of IAAD systems, a novel end-to-end framework for multi-modal ocular recognition is proposed. The proposed framework mainly consists of iris/periocular feature extraction and matching, unsupervised iris quality assessment, and a score-level adaptive weighted fusion strategy. First, ocular feature reconstruction (OFR) is proposed to sparsely reconstruct each probe image by high-quality gallery images based on proper feature maps. Next, a brand new unsupervised iris quality assessment method based on random multiscale embedding robustness is proposed. Different from the existing iris quality assessment methods, the quality of an iris image is measured by its robustness in the embedding space. At last, the fusion strategy exploits the iris quality score as the fusion weight to coalesce the complementary information from the iris and periocular regions. Extensive experimental results on ocular datasets prove that the proposed method is obviously better than unimodal biometrics, and the fusion strategy can significantly improve the recognition performance.
关键词	Iris recognition, periocular recognition, spatial feature reconstruction, fully convolutional network, flexible matching, unsupervised iris quality assessment, adaptive weight fusion
DOI	10.1007/s11633-023-1415-y
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/56033
专题	学术期刊_Machine Intelligence Research
作者单位	1.Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 2.JD AI Research, Beijing 100176, China
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Zihui Yan,Yunlong Wang,Kunbo Zhang,et al. Boosting Multi-modal Ocular Recognition via Spatial Feature Reconstruction and Unsupervised Image Quality Estimation[J]. Machine Intelligence Research,2024,21(1):197-214.
APA	Zihui Yan,Yunlong Wang,Kunbo Zhang,Zhenan Sun,&Lingxiao He.(2024).Boosting Multi-modal Ocular Recognition via Spatial Feature Reconstruction and Unsupervised Image Quality Estimation.Machine Intelligence Research,21(1),197-214.
MLA	Zihui Yan,et al."Boosting Multi-modal Ocular Recognition via Spatial Feature Reconstruction and Unsupervised Image Quality Estimation".Machine Intelligence Research 21.1(2024):197-214.

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