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:2019,28(7):51-57
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基于视频的行人视力状况分析展示系统
(1.四川大学 电子信息学院, 成都 610065;2.成都市规划设计研究院, 成都610081)
Pedestrians' Visual Acuity Analysis and Display System Based on Video
(1.College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China;2.Chengdu Institute of Planning & Design, Chengdu 610081, China)
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投稿时间:2019-01-17    修订日期:2019-02-03
中文摘要: 视力是群体健康的重要指标之一,是建设健康城市的重要调查内容.传统调查群体视力的方法存在局限.本文采用深度学习的方式分析监控视频中行人的人脸属性,识别公共群体中视力障碍的数量和比例,并且分性别研究,作为区域人群群体健康的样本指标.针对视频中人脸属性的识别问题,引入人脸检测卷积神经网络来检测行人人脸,在此基础上提出了改进的人脸分析卷积神经网络,分别完成性别的识别及是否佩戴眼镜的识别.最后研究建立了以百度地图为基础的区域视力数据展示系统,并在Web端分街道和区域对男女视力障碍比例进行数据可视化展示,为接下来的实际应用打下基础.实验结果及系统展示表明,本文提出的方法能有效识别群体视力障碍情况,为群体视力健康调查工作提供了新思路.
Abstract:Visual acuity is one of the most important indicators of group health and a vital survey content of building a healthy city. Traditional methods of investigating group vision have limitations. In this study, the pedestrian's face attributes in the surveillance video are analyzed by deep learning. We identify the number and proportion of visual impairments in public group and study them by gender, and use it as a sample index of regional population health. Aiming at the problem of face attributes recognition in video, the convolutional neural network for face detection is introduced to detect pedestrian's face. On this basis, an improved convolutional neural network for face analysis is proposed to recognize gender and whether or not to wear glasses. Finally, a regional visual data display system based on Baidu Map is established, and the visual data of the proportion of male and female visual impairment is displayed in streets and regions of the Web, which lays the foundation for the next practical application. The experimental results and system demonstration show that the proposed method can effectively identify group visual impairment and provide a new idea for group visual health survey.
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基金项目:国家自然科学基金(61871278);四川省科技计划项目(2018HH0143)
引用文本:
季珂,韩龙玫,卿粼波,刘美,吴晓红.基于视频的行人视力状况分析展示系统.计算机系统应用,2019,28(7):51-57
JI Ke,HAN Long-Mei,QING Lin-Bo,LIU Mei,WU Xiao-Hong.Pedestrians' Visual Acuity Analysis and Display System Based on Video.COMPUTER SYSTEMS APPLICATIONS,2019,28(7):51-57

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