一种基于疑犯照片的任意视图人脸识别方法

Q Physics and Astronomy Journal of the Optical Society of Korea Pub Date : 2016-04-01 DOI:10.3807/JOSK.2016.20.2.239
Dan Zeng, Shuqin Long, Jing Li, Qijun Zhao
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引用次数: 5

摘要

四川大学计算机科学学院,合成视觉基础科学国家重点实验室,成都610065(2015年11月18日收稿,2016年2月11日修稿,2016年3月4日收稿)犯罪嫌疑人面部图像,是警方常规采集的面部图像,通常包含正面和侧面视图。现有的自动人脸识别方法是利用人脸数据库,利用人脸图像生成的合成多视图人脸图像来扩大数据库。本文提出将查询任意视图人脸图像直接与注册的正面和侧面人脸图像进行匹配。在匹配过程中,利用从犯罪嫌疑人面部图像重构的三维脸型模型,在查询人脸图像和图库人脸图像之间建立相应的语义部分,并在此基础上进行比对。将匹配结果与正面和侧面人脸图像融合得到最终的识别结果。与以前的方法相比,该方法更好地利用了人脸数据库,而没有使用可能存在伪影的合成人脸图像。在Color FERET和CMU PIE数据库上验证了该方法的有效性。关键词:疑犯照片人脸识别,任意视图人脸识别,三维人脸重建ocis代码:(100.5010)模式识别;(100.0100)图像处理;(100.3008)图像识别、算法和滤波器;(100.6890)三维图像处理
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A Novel Approach to Mugshot Based Arbitrary View Face Recognition
National Key Laboratory of Fundamental Science on Synthetic Vision,College of Computer Science, Sichuan University, Chengdu 610065, P. R. China(Received November 18, 2015 : revised February 11, 2016 : accepted March 4, 2016)Mugshot face images, routinely collected by police, usually contain both frontal and profile views. Existing automated face recognition methods exploited mugshot databases by enlarging the gallery with synthetic multi-view face images generated from the mugshot face images. This paper, instead, proposes to match the query arbitrary view face image directly to the enrolled frontal and profile face images. During matching, the 3D face shape model reconstructed from the mugshot face images is used to establish corresponding semantic parts between query and gallery face images, based on which comparison is done. The final recognition result is obtained by fusing the matching results with frontal and profile face images. Compared with previous methods, the proposed method better utilizes mugshot databases without using synthetic face images that may have artifacts. Its effectiveness has been demonstrated on the Color FERET and CMU PIE databases. Keywords : Mugshot-based face recognition, Arbitrary view face recognition, Three-dimensional face reconstructionOCIS codes : (100.5010) Pattern recognition; (100.0100) Image processing; (100.3008) Image recognition, algorithms and filters; (100.6890) Three-dimensional image processing
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CiteScore
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审稿时长
2.3 months
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