Matching Forensic Sketches to Mug Shot Photos
Matching Forensic Sketches to Mug Shot Photos
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DOI：
10.1109/tpami.2010.180
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发表时间：
2011-03-01
影响因子：
23.6
通讯作者：
Jain, Anil K.
中科院分区：
文献类型：
--
作者：
Klare, Brendan F.;Li, Zhifeng;Jain, Anil K.
本文讨论了将法医素描与嫌疑犯照片库相匹配的问题。之前关于素描匹配的研究只提供了匹配高度精确的草图的解决方案，这些草图是在看着被试（观看过的草图）时绘制的。法医素描与普通素描的不同之处在于，它们是由警察素描艺术家根据目击者提供的对嫌疑人的描述绘制的。为了识别法医草图，我们提出了一种基于局部特征的判别分析（LFDA）框架。在LFDA中，我们使用SIFT特征描述符和多尺度局部二值模式（MLBP）分别表示草图和照片。然后在基于特征的表示的分割向量上使用多个判别投影进行最小距离匹配。我们应用此方法将159个法医草图的数据集与包含10,159张图像的大头照库进行匹配。与领先的商业人脸识别系统相比，LFDA在将法医草图与相应的人脸图像匹配方面提供了实质性的改进。我们能够使用种族和性别信息进一步提高匹配性能，以减少目标画廊的大小。另外的实验表明，所提出的框架在匹配已查看的草图时具有最先进的精度。
The problem of matching a forensic sketch to a gallery of mug shot images is addressed in this paper. Previous research in sketch matching only offered solutions to matching highly accurate sketches that were drawn while looking at the subject (viewed sketches). Forensic sketches differ from viewed sketches in that they are drawn by a police sketch artist using the description of the subject provided by an eyewitness. To identify forensic sketches, we present a framework called local feature-based discriminant analysis (LFDA). In LFDA, we individually represent both sketches and photos using SIFT feature descriptors and multiscale local binary patterns (MLBP). Multiple discriminant projections are then used on partitioned vectors of the feature-based representation for minimum distance matching. We apply this method to match a data set of 159 forensic sketches against a mug shot gallery containing 10,159 images. Compared to a leading commercial face recognition system, LFDA offers substantial improvements in matching forensic sketches to the corresponding face images. We were able to further improve the matching performance using race and gender information to reduce the target gallery size. Additional experiments demonstrate that the proposed framework leads to state-of-the-art accuracys when matching viewed sketches.