[1]江晟,王殿海,陈永恒,等.基于视频的行人运动轨迹再现与过街行为表达[J].东南大学学报(自然科学版),2012,42(6):1233-1237.[doi:10.3969/j.issn.1001-0505.2012.06.038]
 Jiang Sheng,Wang Dianhai,Chen Yongheng,et al.Pedestrian movement trajectory reappearance and crossing feature expression based on video processing[J].Journal of Southeast University (Natural Science Edition),2012,42(6):1233-1237.[doi:10.3969/j.issn.1001-0505.2012.06.038]
点击复制

基于视频的行人运动轨迹再现与过街行为表达()
分享到:

《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
42
期数:
2012年第6期
页码:
1233-1237
栏目:
计算机科学与工程
出版日期:
2012-11-20

文章信息/Info

Title:
Pedestrian movement trajectory reappearance and crossing feature expression based on video processing
作者:
江晟1 王殿海12 陈永恒1 孙迪1
1 吉林大学交通学院,长春 130022; 2 浙江大学建筑工程学院,杭州 310058
Author(s):
Jiang Sheng1 Wang Dianhai12 Chen Yongheng1 Sun Di1
1 College of Transportation, Jilin University, Changchun 130022, China
2 College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
关键词:
智能交通 视频检测 行人行为 轨迹再现 特征表达
Keywords:
intelligent transportation video detection pedestrian behavior trajectory reappearance feature expression
分类号:
TP391;U121
DOI:
10.3969/j.issn.1001-0505.2012.06.038
摘要:
针对行人运动轨迹再现及表达的问题,结合视频检测技术,提出一种结合时空上下文信息的行人运动特征提取和轨迹跟踪算法,并在视频标定计算中引入中心偏移量,改进了共线模型中不考虑镜头畸变的缺点,提高了标定精度.利用该算法对实际视频进行处理,获取多组行人运动参数和轨迹曲线,再将该算法提取的数据与共线标定方法的计算数据及人工调查得到的真实数据进行对比,验证所提算法的准确性.最后定量分析了几种行人过街行为,对过街行为相应的轨迹特征状态进行了表达,为行人交通组织和控制提供支持.
Abstract:
According to the trajectory reappearance and feature expression of pedestrian movement, based on video processing, a pedestrian feature extraction and tracking algorithm combining with temporal and spatial context information is proposed. Then the center offset is introduced into the calibration to overcome the shortcomings of the collinear model which does not consider the lens distortion, thus the calibration precision is improved. This algorithm is used to obtain some groups of pedestrian movement parameters and trajectory curve on real video processing. Then the data extracted by this algorithm is compared with both the data calculated through the collinear calibration method and the real data from artificial investigation, in order to verify the accuracy of this algorithm. Finally, several pedestrian crossing behaviors are quantitatively analyzed and the corresponding feature statuses are expressed, which can support the organization and control of pedestrian traffic.

参考文献/References:

[1] 孙智勇,葛书芳,荣建,等.行人交通的数据采集方法研究[J].北京工业大学学报,2006,32(6):530-533.
  Sun Zhiyong,Ge Shufang,Rong Jian,et al.Study on pedestrian traffic data collection[J].Journal of Beijing University of Technology,2006,32(6):530-533.(in Chinese)
[2] Bernhoft I M,Carstensen G.Preferences and behavior of pedestrians and cyclists by age and gender[J].Transportation Research Part F,2008,11(2):83-95.
[3] Zhou R G,Horrey W J,Yu R F.The effect of conformity on pedestrians’ road-crossing intentions in China:an application of the theory of planned behaviour[J].Accident Analysis and Prevention,2009,41(3):491-497.
[4] 裴玉龙,冯树民.城市行人过街速度研究[J].公路交通科技,2006,23(9):104-107.
  Pei Yulong,Feng Shumin.Research on design speed of urban pedestrian crossing[J].Journal of Highway and Transportation Research and Development,2006,23(9):104-107.(in Chinese)
[5] Hoogendoorn S P,Daamen W,Bovy P H L.Extracting microscopic pedestrian characteristics from video data[C/CD] //Transportation Research Board Annual Meeting.Washington DC:National Academy Press,2003.
[6] Daamen W,Hoogendoorn S P,Bovy P H L.First-order pedestrian traffic flow theory[C/CD] //Transportation Research Board Annual Meeting.Washington DC:National Academy Press,2005.
[7] 王阿琴,杨万扣,孙长银.基于子图像的尺度自适应mean shift目标跟踪[J].东南大学学报:自然科学版,2010,40(增刊1):131-135.
  Wang Aqin,Yang Wankou,Sun Changyin.Scale adaptable mean shift object tracking based on image fragments[J].Journal of Southeast University:Natural Science Edition,2010,40(Sup 1):131-135.(in Chinese)
[8] 胡宏宇,王殿海,孙迪.基于视频跟踪方法的行人过街状态表达与分析[J].交通信息与安全,2009,27(3):43-47.
  Hu Hongyu,Wang Dianhai,Sun Di.Representation and analysis of pedestrian crossing states based on video tracking[J].Journal of Transport Information and Safety,2009,27(3):43-47.(in Chinese)
[9] 邵春福,李娟,赵熠,等.行人交通的视频检测方法综述[J].交通运输系统工程与信息,2008,8(4):23-29.
  Shao Chunfu,Li Juan,Zhao Yi,et al.Review of pedestrian traffic data collection method based on video image processing[J].Journal of Transportation Systems Engineering and Information Technology,2008,8(4):23-29.(in Chinese)
[10] 沈涛.基于视频检测的行人交通参数提取技术研究[D].北京:北京交通大学交通运输学院,2011.
[11] 刘轩.基于图像处理的行人运动微观行为特征实验研究[D].合肥:中国科学技术大学安全技术及工程学院,2009.

相似文献/References:

[1]宋翔,汤文成,李旭,等.基于两级滤波的车辆相对加速度估计[J].东南大学学报(自然科学版),2015,45(1):51.[doi:10.3969/j.issn.1001-0505.2015.01.010]
 Song Xiang,Tang Wencheng,Li Xu,et al.Estimation of vehicle relative acceleration based on two-level filter[J].Journal of Southeast University (Natural Science Edition),2015,45(6):51.[doi:10.3969/j.issn.1001-0505.2015.01.010]
[2]彭博,蔡晓禹,张有节,等.基于对称帧差和分块背景建模的无人机视频车辆自动检测[J].东南大学学报(自然科学版),2017,47(4):685.[doi:10.3969/j.issn.1001-0505.2017.04.010]
 Peng Bo,Cai Xiaoyu,Zhang Youjie,et al.Automatic vehicle detection from UAV videos based on symmetrical frame difference and background block modeling[J].Journal of Southeast University (Natural Science Edition),2017,47(6):685.[doi:10.3969/j.issn.1001-0505.2017.04.010]

备注/Memo

备注/Memo:
作者简介: 江晟(1985—),男,博士生; 陈永恒(联系人),男,博士,副教授, cyhjlu@yahoo.cn.
基金项目: 国家自然科学基金资助项目(51108208)、中国博士后科学基金面上资助项目(20110491307)、吉林大学科学前沿与交叉学科创新资助项目(201103146).
引文格式: 江晟,王殿海,陈永恒,等.基于视频的行人运动轨迹再现与过街行为表达[J].东南大学学报:自然科学版,2012,42(6):1233-1237. [doi:10.3969/j.issn.1001-0505.2012.06.038]
更新日期/Last Update: 2012-11-20