Ground truth annotation of traffic video data

被引:0
作者
Jose M. Mossi
Antonio Albiol
Alberto Albiol
Javier Oliver
机构
[1] Universitat Politècnica de València,ITeam
来源
Multimedia Tools and Applications | 2014年 / 70卷
关键词
Traffic; Ground truth; Vehicle; Video; Intelligent transportation systems;
D O I
暂无
中图分类号
学科分类号
摘要
This paper presents a software application to generate ground-truth data on video files from traffic surveillance cameras used for Intelligent Transportation Systems (IT systems). The computer vision system to be evaluated counts the number of vehicles that cross a line per time unit –intensity-, the average speed and the occupancy. The main goal of the visual interface presented in this paper is to be easy to use without the requirement of any specific hardware. It is based on a standard laptop or desktop computer and a Jog shuttle wheel. The setup is efficient and comfortable because one hand of the annotating person is almost all the time on the space key of the keyboard while the other hand is on the jog shuttle wheel. The mean time required to annotate a video file ranges from 1 to 5 times its duration (per lane) depending on the content. Compared to general purpose annotation tool a time factor gain of about 7 times is achieved.
引用
收藏
页码:461 / 474
页数:13
相关论文
共 14 条
[1]  
Albiol A(2011)Detection of parked vehicles using spatiotemporal maps IEEE Trans Intell Transport Syst 12 1277-1291
[2]  
Blunsden SJ(2010)The BEHAVE video dataset: ground truthed video for multi-person behavior classification Annal British Mach Vis Assoc 4 1-12
[3]  
Fisher R(2009)Semantic object classes in video: a high-definition ground truth database Pattern Recognit Lett 30 88-97
[4]  
Brostow GJ(2011)A review of computer vision techniques for the analysis of urban traffic IEEE Trans Intell Transp Syst 12 920-939
[5]  
Buch N(2012)Pedestrian detection: an evaluation of the state of the art IEEE Trans Pattern Anal Mach Intell 34 743-761
[6]  
Dollar P(2011)Adaptive background modeling integrated with luminosity sensors and occlusion processing for reliable vehicle detection IEEE Trans Intell Transport Syst 12 1398-1412
[7]  
Faro A(2010)GAT: a graphical annotation tool for semantic regions Multimed Tool Appl 46 155-174
[8]  
Giro-i-Nieto X(2009)Framework for performance evaluation of face, text, and vehicle detection and tracking in video: data, metrics, and protocol IEEE Trans Pattern Anal Mach Intell 31 319-336
[9]  
Kasturi R(2000)Mental fatigue and task control: planning and preparation Psychophysiology 37 614-625
[10]  
Lorist MM(2008)LabelMe: a database and web-based tool for image annotation Int J Comput Vis 77 157-173