Face detection and identification is the most difficult and often used task in Artificial Intelligence systems. The goal of this study is to present and compare the results of several face detection and recognition algorithms used in the system. This system begins with a training image of a human, then continues on to the test image, identifying the face, comparing it to the trained face, and finally classifying it using OpenCV classifiers. This research will discuss the most effective and successful tactics used in the system, which are implemented using Python, OpenCV, and Matplotlib. It may also be used in locations with CCTV, such as public spaces, shopping malls, and ATM booths.
翻译:在人工智能系统中,发现和识别面部是最困难和经常使用的任务。本研究的目的是展示和比较系统中使用的若干面部检测和识别算法的结果。这个系统首先展示和比较一个人的训练图像,然后继续到测试图像上,识别脸部,将其与受过训练的面部进行比较,最后使用OpenCV分类器对其进行分类。这项研究将讨论系统中使用的最有效和最成功的策略,这些策略是使用Python、OpenCV和Matplotlib实施的。它也可以在有闭路电视的地点使用,如公共场所、购物中心、自动取款机亭。