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Efficient Face Detection And Identification In Networked Video Surveillance Systems

机译:网络视频监控系统中的有效人脸检测和识别

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Applications for face detection use algorithms that rely on identifying human faces in broader photos that may include environments, artifacts, and other sections of a person's physique. This work proposes a real-time identification system, based on modern image processing capabilities of open source API like OpenCV and due to the solution requirements, a study on the performance analysis of such solution compared to available commercial framework like SPID from NEC is intended. However, here, the study is available with the results of various experiments on the developed system. A systematic approach is followed to produce such outputs and have been measured using software codes. By using IP camera and a Raspberry Pi, the solution developed is simple in nature. This study relies on face detection and identification functionalities for human faces but not limited to live faces only but mix of faces from still images as well.
机译:面部检测应用程序使用的算法依赖于在更宽广的照片中识别人脸,其中可能包括环境,伪影和人的体质的其他部分。这项工作提出了一种实时识别系统,该系统基于开源API(例如OpenCV)的现代图像处理功能,并且由于解决方案要求,因此打算将这种解决方案的性能分析与NEC的SPID等商业框架进行比较。但是,在这里,可以使用已开发系统上的各种实验结果进行研究。遵循系统的方法来产生这样的输出,并且已经使用软件代码对其进行了测量。通过使用IP摄像机和Raspberry Pi,开发的解决方案本质上很简单。这项研究依赖于人脸的人脸检测和识别功能,但不仅限于活脸,还包括静止图像中的人脸混合。

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