Pedestrian Sensing Technology Review

Pedestrians are important yet vulnerable road users, especially in urban environments. Traffic accidents involving pedestrians usually lead to serious injuries or fatalities. From an application’s point of view, pedestrian detection can be used for traffic flow monitoring, intelligent pedestrian crossing or on-board vehicle for driver assistance. From the technology’s point view, different sensing technologies such as piezoelectric sensor, ultrasonic sensor, microwave radar, laser scanner and computer vision can be used for pedestrian detection. We have carried out an extensive review of existing literature and latest developments in related fields. The review is summarized below and categorized according to technology types.

[1]  Katharine Hunter-Zaworski,et al.  Passive Pedestrian Detection at Unsignalized Crossings , 1998 .

[2]  Rainer Kallenbach,et al.  Predictive Safety Systems - Steps Towards Collision Mitigation , 2004 .

[3]  M. Szarvas,et al.  Pedestrian detection with convolutional neural networks , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[4]  J. Scholz,et al.  Reliable pedestrian protection using laserscanners , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[5]  Sei-Wang Chen,et al.  Pedestrian detection and tracking at crossroads , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[6]  Xia Liu,et al.  Pedestrian detection and tracking with night vision , 2005, IEEE Transactions on Intelligent Transportation Systems.

[7]  David Binnie,et al.  Monitoring the Movement of Pedestrians Using Low-cost Infrared Detectors: Initial Findings , 2004 .

[8]  D A Noyce,et al.  AN EVALUATION OF TECHNOLOGIES FOR AUTOMATED DETECTION AND CLASSIFICATION OF PEDESTRIANS AND BICYCLISTS , 2002 .

[9]  David G Davies,et al.  RESEARCH, DEVELOPMENT, AND IMPLEMENTATION OF PEDESTRIAN SAFETY FACILITIES IN THE UNITED KINGDOM , 1999 .

[10]  G. Wanielik,et al.  Shape and motion-based pedestrian detection in infrared images: a multi sensor approach , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[11]  Klaus Dietmayer,et al.  Pedestrian recognition in urban traffic using a vehicle based multilayer laserscanner , 2002, Intelligent Vehicle Symposium, 2002. IEEE.

[12]  K. Fuerstenberg.  Pedestrian Detection and Classification by Laserscanners , 2003 .

[13]  P. Prasanna,et al.  Probabilistic signal interpretation methods for a thermopile pedestrian detection system , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[14]  J. Oksman,et al.  Design of pedestrian detection systems for the prediction of car-to-pedestrian accidents , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[15]  K. Dietmayer,et al.  Object tracking and classification for multiple active safety and comfort applications using a multilayer laser scanner , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[16]  A. Dupret,et al.  On chip vision system architecture using a CMOS retina , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[17]  Hideo Mori,et al.  A method for discriminating of pedestrian based on rhythm , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[18]  U. Lages,et al.  A multi-sensor approach for the protection of vulnerable traffic participants the PROTECTOR project , 2001, IMTC 2001. Proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference. Rediscovering Measurement in the Age of Informatics (Cat. No.01CH 37188).

[19]  A. Shashua,et al.  Pedestrian detection for driving assistance systems: single-frame classification and system level performance , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[20]  Chih-Hao Chen,et al.  Design and experimental study of an ultrasonic sensor system for lateral collision avoidance at low speeds , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[21]  Tomaso A. Poggio,et al.  Trainable pedestrian detection , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[22]  C. Thorpe,et al.  Dressed human modeling, detection, and parts localization , 2001 .

[23]  M. Mahlisch,et al.  A multiple detector approach to low-resolution FIR pedestrian recognition , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[24]  A. Broggi,et al.  Pedestrian localization and tracking system with Kalman filtering , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[25]  Y. Tamatsu,et al.  Solid or not solid: vision for radar target validation , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[26]  K. Dietmayer,et al.  Multiple hypothesis classification with laser range finders , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[27]  S. Heinrich,et al.  Fast obstacle detection for urban traffic situations , 2002, IEEE Trans. Intell. Transp. Syst..

[28]  Nanning Zheng,et al.  Pedestrian detection using sparse Gabor filter and support vector machine , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[29]  Tomaso A. Poggio,et al.  Example-Based Object Detection in Images by Components , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  B. Zavidovique,et al.  A context-dependent vision system for pedestrian detection , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[31]  D. Linzmeier,et al.  Pedestrian detection with thermopiles using an occupancy grid , 2004, Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No.04TH8749).

[32]  Massimo Bertozzi,et al.  IR Pedestrian Detection for Advanced Driver Assistance Systems , 2003, DAGM-Symposium.

[33]  S Milch,et al.  PEDESTRIAN DETECTION WITH RADAR AND COMPUTER VISION , 2001 .

[34]  Hyeran Byun,et al.  Real-Time Pedestrian Detection Using Support Vector Machines , 2002, Int. J. Pattern Recognit. Artif. Intell..

[35]  F. Suard,et al.  Pedestrian detection using stereo-vision and graph kernels , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[36]  Massimo Bertozzi,et al.  Shape-based pedestrian detection , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[37]  Kay Ch Fuerstenberg,et al.  PEDESTRIAN RECOGNITION IN URBAN TRAFFIC USING LASERSCANNERS , 2001 .

[38]  Dariu Gavrila,et al.  Real-time object detection for "smart" vehicles , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[39]  V. Willhoeft,et al.  Laser scanners for obstacle detection in automotive applications , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[40]  A. Broggi,et al.  A multi-resolution approach for infrared vision-based pedestrian detection , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[41]  M.-M. Meinecke,et al.  Radar sensors and sensor platform used for pedestrian protection in the EC-funded project SAVE-U , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[42]  Liang Zhao,et al.  Stereo- and neural network-based pedestrian detection , 2000, IEEE Trans. Intell. Transp. Syst..

[43]  A. Broggi,et al.  Infrared stereo vision-based pedestrian detection , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[44]  Ryosuke Shibasaki,et al.  A novel system for tracking pedestrians using multiple single-row laser-range scanners , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[45]  Xavier Binefa,et al.  Robust Real-Time Periodic Motion Detection, Analysis, and Applications , 2000, IEEE Trans. Pattern Anal. Mach. Intell..