基于视频分析的生物特征儿童和成人分类

Q4 Computer Science
O. F. Ince, I. Ince, Jangsik Park, Jongkwan Song, B. Yoon
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引用次数: 1

摘要

随着与社会犯罪相关的社会不安全感的增加,为了有效地抓捕罪犯,需要闭路电视摄像机对包括行人在内的物体的检测精度更高。随着行人检测功能的重要性逐渐得到社会的认可,基于图像和视频的行人检测的研究也越来越多。因此,本研究的目的是将行人分为儿童和成人两类。本研究使用Haar级联分类器。这种方法首先检测整个身体和头部。然后,它根据身体和头部的相对比例长度来测量生物特征。采用移动平均算法获得阈值比。实验结果表明,儿童的准确率为100%,成人的准确率为64.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CHILD AND ADULT CLASSIFICATION USING BIOMETRIC FEATURES BASED ON VIDEO ANALYTICS
As the number of social insecurity in regard to social crimes is on its rise, it requires a CCTV camera a higher accuracy in detecting the objects including pedestrians for efficient work of catching criminals. As the importance of the function of pedestrian detection is socially agreed upon, more studies on image and video based pedestrian detection have been conducted. In terms of that, the goal of this study is classification of pedestrian in two categories as a child and an adult. In this study, Haar cascade classifiers are used. This method first detects a full body and a head. Then, it measures the biometry given the relative proportioning length of a full body and a head. Moving average algorithm is used to obtain threshold ratio. Experimental results show the accuracy 100% for children and 64.5% for adults.
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来源期刊
ICIC Express Letters, Part B: Applications
ICIC Express Letters, Part B: Applications Computer Science-Computer Science (all)
CiteScore
1.00
自引率
0.00%
发文量
9
期刊介绍: The ICIC Express Letters, Part B: Applications (abbreviated as ICIC-ELB) is a peer-reviewed English language journal of research and surveys on Innovative Computing, Information and Control, and is published by ICIC International monthly. The primary aim of the ICIC-ELB is to publish timely quality short papers (generally no more than 8 printing pages) with emphasis on applications of established or new developed novel techniques, approaches and methodologies of computing systems, intelligent systems, information processing, and automation and control systems.
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