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Face Matrix: A Quick Search and Indexing Method for Suspect Recognition in Police Departments

机译:人脸矩阵:在警察部门中对可疑嫌疑人进行识别的快速搜索和索引方法

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This study presents an indexing and a quick sort method that could be used to find the possible matching guilty pictures from the police database by using a tracing software and eyewitness descriptions about the suspected guilty profile. It is well known that databases located in the police departments have a large amount of prerecorded convicted guilty pictures. Searching a picture from database for recognition is very hard and it may take too much time. In addition to this, it can also require to track many redundant pictures to find the correct guilty. There is, of course, no guarantee that Photofit (robot picture) is included in database. Therefore police departments have difficult problems to recognize exact guilty using Photofits described by eyewitness. In this paper, a matrix construction using particular distances on face has been demonstrated. In order to find these certain points on the face, a new point selection schema and some existing recognition methods are presented. Finally, three different determinant values of this matrix are computed and are used for picture indexing in the database. In the test environment, the system results 30 different matches with the predefined Photofits by using this indexing algorithm together with a face tracing software and a patch program, proving that the tracking time for redundant pictures is reduced.
机译:这项研究提出了一种索引和一种快速排序的方法,该方法可用于通过使用跟踪软件和有关可疑犯罪特征的目击者描述,从警察数据库中查找可能匹配的有罪图像。众所周知,位于警察局的数据库中有大量预先录制的定罪有罪图片。从数据库中搜索图片以进行识别非常困难,并且可能需要太多时间。除此之外,还可能需要跟踪许多多余的图片才能找到正确的罪状。当然,我们无法保证数据库中包含Photofit(机器人图片)。因此,警察部门在使用目击者描述的Photofits识别确切的罪行时遇到了难题。在本文中,已经证明了使用特定距离的人脸矩阵。为了找到面部上的这些特定点,提出了一种新的点选择方案和一些现有的识别方法。最后,计算该矩阵的三个不同的行列式值,并将其用于数据库中的图片索引。在测试环境中,通过使用此索引算法,面部跟踪软件和补丁程序,系统可与预定义的Photofits进行30种不同的匹配,从而证明减少了冗余图片的跟踪时间。

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