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中国科学家异质人脸图像识别研究取得新突破

2015-07-21 佚名 新华网

西安电子科技大学高新波教授带领的研究团队在异质人脸图像识别研究领域取得重要进展,其对香港中文大学人脸素描标准数据库(CUFS)的识别准确率达到了99.67%。根据这一研究成果研发的异质人脸图像识别系统,如果应用到刑侦过程中,有望帮助办案人员缩小犯罪嫌疑人的搜寻范围。 人脸识别是计算机视觉和人工智能研究领域一个重要课题,在身份认证等公共安全领域有大量应用。异质人脸识别是一种基于图像合成的人脸识别技术

西安电子科技大学高新波教授带领的研究团队在异质人脸图像识别研究领域取得重要进展,其对香港中文大学人脸素描标准数据库(CUFS)的识别准确率达到了99.67%。根据这一研究成果研发的异质人脸图像识别系统,如果应用到刑侦过程中,有望帮助办案人员缩小犯罪嫌疑人的搜寻范围。

人脸识别是计算机视觉和人工智能研究领域一个重要课题,在身份认证等公共安全领域有大量应用。异质人脸识别是一种基于图像合成的人脸识别技术。

“所谓异质人脸图像,就是不同方式、不同来源获得的不同质量的人脸图像。”高新波教授介绍说,由于数据来源不同、图片质量不同,在人脸识别研究领域,照片、素描等不同来源人脸图像,难以使用计算机进行直接比对。必须将不同人脸图像转换到同一表达空间,计算机才能够进行自动匹配识别。我们的研究,就是要解决这个问题。

国际上关于异质人脸识别的研究始于2000年左右。2001年,高新波便开始带领团队从事异质人脸图像合成与识别的研究。目前已经成功研制出了基于图像合成的人脸识别系统。通过该系统,人脸照片与手绘素描画像之间可以实现相互转化,进而实现不同模态人脸图像的检索比对与识别,该系统提高了异质人脸图像合成的效率及识别的准确率。

在刑侦过程中,经常能够通过监控视频获取犯罪嫌疑人画面,或者通过目击人的描述得到犯罪嫌疑人的人像素描。但使用这种方式得到的照片,要么分辨率太低,要么有遮挡,使得图像比对的难度大大增加。异质人脸合成及基于该技术研发的系统将成为缩小犯罪嫌疑人范围的重要辅助工具。

高新波介绍说,他们开发的基于图像合成的人脸识别系统,如果应用于刑侦过程中,警方就可以将依据监控图像或目击者描述绘制的嫌疑人模拟画像,直接输入系统合成出计算机可以识别的照片,并将合成照片在全国身份证数据库中进行比对。

原始出处:
Zhao L, Gao X, Tao D, Li X.Learning a Tracking and Estimation Integrated Graphical Model for Human Pose Tracking. IEEE Trans Neural Netw Learn Syst. 2015 Mar 27

Yang X, Gao X, Tao D, Li X, Han B, Li J.Shape-Constrained Sparse and Low-Rank Decomposition for Auroral Substorm Detection.IEEE Trans Neural Netw Learn Syst. 2015 Mar 27.

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    2015-10-28 zxxiang
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    2015-07-21 chenhui888

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