EYE SPY Face Detection and Identification using YOLO

M. Vigil, M. Barhanpurkar, NS Rahul Anand, Yash Soni, Anmol Anand
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引用次数: 3

Abstract

YOLO (You Only Look Once) is a state of the art object detection system. The object detection algorithms of YOLO is taken and is used on a custom made dataset to identify the person on camera. This method will revolutionize surveillance and security methods. This paper addresses fundamental challenges faced in making the dataset. It also compares conventional methods with YOLO. YOLO is the fastest and most accurate object detection technique. This paper also states the applications of this technology along with its advantages and various disadvantages. It uses a multi-scale training method that can run at various sizes offering an excellent relation speed and accuracy. We have based our model on yolo v2 all the while bringing our own changes for shifting from object detection to Face identification.
EYE SPY人脸检测与YOLO识别
YOLO (You Only Look Once)是一种最先进的物体检测系统。采用YOLO的目标检测算法,并在自定义数据集上对相机上的人进行识别。这种方法将彻底改变监视和安全方法。本文解决了在制作数据集时面临的基本挑战。它还比较了传统方法和YOLO。YOLO是最快和最准确的目标检测技术。本文还阐述了该技术的应用以及它的优点和各种缺点。它使用多尺度训练方法,可以在各种规模上运行,提供了良好的速度和准确性关系。我们的模型一直基于yolo v2,同时将我们自己的变化从物体检测转移到人脸识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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