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HUMAN DETECTION IN VIDEO AND IMAGES - A STATE-OF-THE-ART SURVEY

机译:视频和图像中的人类检测-最新的调查

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The aim of this paper is to give an overview of state-of-the-art human detection methods, classify them into reasonable categories and listing new trends in this field. Human detection in static images or video sequences is a challenging area of research with its main application in surveillance, defence, intelligent vehicles and robotics. In this survey paper, we classify the human detection methods based upon the mode of data acquisition and features used for detection of human. The review of different algorithms reported in last few years for human detection is tabulated. Also, we reviewed standard dataset for evaluation of human detection and studied the statistics about these dataset such as number of frames, challenging environments conditions, ground truth structure, camera details, etc. Different performance measures for human detection algorithms both qualitative and quantitative are listed out. Our survey gauges the gap between the present research and future requirements.
机译:本文的目的是概述最新的人体检测方法,将其分类为合理的类别,并列出该领域的新趋势。静态图像或视频序列中的人体检测是一项具有挑战性的研究领域,主要应用于监视,防御,智能车辆和机器人技术。在本调查文件中,我们根据数据采集的模式和用于检测人类的特征对人类检测方法进行分类。列出了近年来报告的用于人类检测的不同算法的综述。此外,我们审查了用于评估人类检测的标准数据集,并研究了有关这些数据集的统计数据,例如帧数,挑战性环境条件,地面真实结构,相机细节等。列出了针对人类检测算法的不同性能指标(定性和定量)出来。我们的调查衡量了当前研究与未来需求之间的差距。

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