基于人体特征提取的人体识别

Martino C. Khuangga, D. H. Widyantoro
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引用次数: 3

摘要

一个可以记录人员出勤的系统成为越来越重要的工具。它通常需要人的动作来检测一个人的存在,比如把手指放在指纹检测系统的扫描仪上。有一些系统不需要人的动作(如在人脸识别系统中使用摄像头),但它需要人脸数据库。本文介绍了一种实现人体特征提取的人体识别系统,该系统可以跟踪房间中是否有人存在。该系统使用摄像头作为输入设备,以消除所需的特殊动作。之所以选择人体特征,是因为人体特征更容易被发现,可以作为识别进入房间的人的强烈身份,但我们不需要先训练人体特征。在这个系统中有两个主要过程。首先,系统检测进入房间的人。其次,它还能检测出离开房间的同一个人。该应用程序是使用图像处理技术实现的,例如使用HOG描述符的人体检测、HSV颜色转换和模板匹配。由于该系统仍然无法处理某些特殊情况,因此可能会发生来自该应用程序的跟踪故障。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human Identification Using Human Body Features Extraction
A system that can mark personnel attendance becomes an increasingly important tool. It usually requires human action in order to detect the presences of a person such as putting finger on a scanner in a fingerprint detection system. There are some systems that do not need human action (such as the use of camera in a face recognition system) but it requires human face database. This paper introduces human identification system implementing human body feature extraction, which can track the presence of persons in a room. The system uses camera as input device to remove the special action needed. Features on human body was chosen because they tend to be easier to detect and serve as a strong identity to mark person who enter a room, yet we do not need to train body features first. There are two main processes in this system. First, the system detects person entering a room. Second, it also detects the same person leaving the room. This application was implemented using image processing techniques such as human detection using HOG descriptors, HSV color conversion, and template matching. Tracking failures from this application could happen because this system still could not handle some special cases.
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