期刊文献+

防止人-车碰撞的交叉口过街行人位置预测 被引量:1

Predicting position of pedestrian at crossroad for preventing pedestrian-vehicle collision
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摘要 为减少交叉口人-车碰撞事故的发生,利用单目视觉技术和行人横道线特征建立图像像素坐标与实际路面坐标的映射关系,进行行人检测,在获得实时、可靠的过街行人交通参数的基础上采用卡尔曼滤波器预测过街行人的位置,用于判断行人-车辆潜在冲突点,为驾驶员提供行人信息,以便驾驶员采取相应措施保障过街行人的安全;最后进行了相关试验验证。 In order to decrease the pedestrian-vehicle accident at crossroad,coordinate relations between the image and road position based on monocular camera and zebra stripes feature is founded.After detecting pedestrian and getting real-time and reliable traffic information of pedestrian at crossroad,the position of pedestrian is predicted based on Kalman prediction to prejudge pedestrian-vehicle conflict point and provide pedestrian information for driver.Finally detecting and predicting method experiments are performed and the method has been proved to be correct.
出处 《计算机工程与应用》 CSCD 北大核心 2008年第33期34-36,共3页 Computer Engineering and Applications
基金 国家教育部高等学校博士学科点专项科研基金新教师课题。
关键词 横道线特征 感兴趣区 卡尔曼预测 zebra stripes feature area of interesting Kalman prediction
作者简介 马国胜(1975-),男,博士研究生,讲师,研究方向为智能交通与主动安全;E-mail:ma_guosheng@163.com 白玉(1977-),女,博士,讲师,研究方向为智能交通与主动安全,交通系统设计; 朱彤(1977-),男,博士研究生,研究方向为智能交通与主动安全。
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参考文献6

  • 1郭烈,王荣本,顾柏园,余天洪.世界智能车辆行人检测技术综述[J].公路交通科技,2005,22(11):133-137. 被引量:18
  • 2Grubb G,Zelinsky A,Nilsson L,et al.3D vision sensing for improved pedestrian safety[C]//IEEE Intelligent Vehicles Symposium, 2004:19-24.
  • 3Pai Chia-Jung,Tyant Hsiao-Rong.Pedestrian detection and tracking at erossroads[C]//IEEE Intelligent Transportation Systems Conference, 2003:101-104.
  • 4容观澳.计算机图像处理[M].北京:清华大学出版社,2000..
  • 5马国胜,朱彤,杨晓光,等.基于横道线特征的预测交叉口行人-车辆事故的行人检测与跟踪方法研究[c]//国际交通技术创新与应用大会(TDIBP)论文集,2008:276-281.
  • 6Bozic M S.数字滤波和卡尔曼滤波[M].北京:科学出版社,1984.

二级参考文献15

  • 1P Marchal, SAVE-U: Sensors and System Architecture for Vulnerable Road Users Protection [ C ] .Bruxelles: ADASE Ⅱ-3rd Concertation meeting, Jan.2004: 19-20.
  • 2M Bertozzi, A Broggi, R Chapuis, F Chausse etc. Shape-based Pedestrian Detection and Localization [ C] . Ohio, USA: Procs. IEEE Intelligent Vehicles Symposium 2003, June 2003: 410 - 415.
  • 3D M Gavrila, J Geibel. Shape-Based Pedestrian Detection and Tracking [C] .Paris, France: Procs. IEEE Intelligent Vehicles Symposium 2002, June 2002.
  • 4B Heisele, C W ohler. Motion-based Recognition of Pedestrians [C] .Brisbane, Australia: IEEE Intelligent Conference on Pattern Recognition, August 1998: 1325- 1330.
  • 5A J Lipton. Local Application of Optic flow to Analyze Rigid Versus Non -rigid Motion [R] . USA: Robotics Institute, Carnegie Mellon University, Dec. 1999.
  • 6V Philomin, R Duraiswami, L Davis. Pedestrian Tracking from a MovingVehicle [C] . Dearborn, USA: Procs. IEEE Intelligent Vehicles Symposium 2000, Oct.2000.
  • 7O Masoud, NP Papanikolopoulos. Robust Pedestrian Tracking Using a Model-based Approach [ C] .Boston, USA: Proc. IEEE Conference on Intelligent Transportation Systems, Nov. 1997: 338 - 343.
  • 8K Rohr. Towards Model-based Recognition of Human Movements in Image Sequences [J] .CVGIP: Image Understanding, January 1994, 59(1): 94-115.
  • 9M Oren, C Papageorgiu, P Sihna, E Osuna, T Poggio, Pedestrian Detection using Wavelet Templates [C] .Puerto Rico: Procs. IEEE Conf. on Computer Vision and Pattern Recognition, June 1997:193 -199.
  • 10A Mohan, C Papageorgion, T Poggio. Example-based Object Detection in Images by Components [ J ] . IEEE Transactions on Pattern Analysis and Machine Intelligence, Apr.2001, 23 (4): 349-361.

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