Cross-sensor iris recognition using adversarial strategy and sensor-specific information
文献类型:会议论文
作者 | Wei Jianze2,3,4; Wang Yunlong2,3; Wu Xiang2,3; He Zhaofeng1; He Ran2,3; Sun Zhenan2,3 |
出版日期 | 2019 |
会议日期 | 23-26 September 2019 |
会议地点 | Tampa, FL, USA |
英文摘要 | Due to the growing demand of iris biometrics, lots of new sensors are being developed for high-quality image acquisition. However, upgrading the sensor and re-enrolling for users is expensive and time-consuming. This leads to a dilemma where enrolling on one type of sensor but recognizing on the others. For this cross-sensor matching, the large gap between distributions of enrolling and recognizing images usually results in degradation in recognition performance. To alleviate this degradation, we propose Cross-sensor iris network (CSIN) by applying the adversarial strategy and weakening interference of sensor-specific information. Specifically, there are three valuable efforts towards learning discriminative iris features. Firstly, the proposed CSIN adds extra feature extractors to generate residual components containing sensor-specific information and then utilizes these components to narrow the distribution gap. Secondly, an adversarial strategy is borrowed from Generative Adversarial Networks to align feature distributions and further reduce the discrepancy of images caused by sensors. Finally, we extend triplet loss and propose instance-anchor loss to pull the instances of the same class together and push away from others. It is worth mentioning that the proposed method doesn't need pair-same data or triplet, which reduced the cost of data preparation. Experiments on two real-world datasets validate the effectiveness of the proposed method in cross-sensor iris recognition. |
语种 | 英语 |
源URL | [http://ir.ia.ac.cn/handle/173211/48638] |
专题 | 自动化研究所_智能感知与计算研究中心 |
作者单位 | 1.Beijing IrisKing Co., Ltd 2.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 3.Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 4.School of Artificial Intelligence, University of Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Wei Jianze,Wang Yunlong,Wu Xiang,et al. Cross-sensor iris recognition using adversarial strategy and sensor-specific information[C]. 见:. Tampa, FL, USA. 23-26 September 2019. |
入库方式: OAI收割
来源:自动化研究所
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