Abstract
Recent statistical data of traffic accidents reveals that pedestrian fatalities are a particular priority in Europe and Japan. Many active safety systems for pedestrian protection based on sensor fusion approach such as millimeter wave radar, Laser Imaging Detecting And Ranging (LIDAR) and monocular/stereo camera are proposed. Aiming at large-scale system penetration in automobile markets, low-cost driver assistance system development becomes an important issue, therefore a monocular camera is one of solutions. To realize zero-traffic accident society, the objective of this paper is to develop a driver assistance system for pedestrian collision prevention based on using a monocular camera. As the concept of the system, moving objects on and nearby a crosswalk are interpreted as pedestrians. An on-board camera image processing algorithm is designed to detect the existence of a crosswalk in front of the vehicle. The feature extraction technique used in the algorithm is based on the feature called “cross ratio” of the crosswalk edges and the periodicity of the crosswalk paints. Then, nearby the detected crosswalk position, the region of interest is determined to be used in the moving object detection module. The position and the velocity of the moving object are obtained with the application of optical flow algorithm. Crosswalk image database in real-world traffic in Japan is constructed, and the precision of crosswalk detection is examined by using the database. Optical flow algorithm is applied on the region nearby the detected crosswalk in order to detect moving objects which are inferred as pedestrians. Image-based egomotion estimation is used to compensate the error in distance estimation and pedestrian movement. The effectiveness of the proposed system is verified by test drives. The system can perform the detection of crosswalks in urban area in various weather conditions with high detection rate. Pedestrians on crosswalks can also be detected by Optical Flow-based image processing algorithm. The detectable range of the proposed pedestrian detection with crosswalk detection function is 20–25 m in front of vehicle. This approach does not claim to cover 100 % of all pedestrian accidents, but has the advantage of high robustness, low false alarm rate and cost efficient implementation. The feasibility of the proposed camera-based pedestrian detection system is shown in the paper. The validation of the crosswalk detection and pedestrian detection algorithm using real-world driving database will be conducted and demonstrated in the full paper.
F2012-F03-013
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References
ITARDA (2010) Special issue on vehicle to pedestrian accidents. ITARDA Inf 83:1–12
NHTSA. Traffic safety facts 2009 data. DOT HS 811 394
European Road Safety Observatory. Traffic safety basic facts: pedestrians. DaCoTA
ITARDA. Pedestrian accidents, ITARDA statistical data, Japan, 2007. http://www8.cao.go.jp/koutu/taisaku/h20kou_haku/pdffiles/honpen/gh1_112.pdf
Bishop R (2005) Intelligent vehicle technology and trends. Artech House, Boston, pp 144–150
Gandhi T, Trivedi MM (2007) Pedestrian protection systems: issues, survey, and challenges. IEEE Trans Intell Transp Syst 28(3):413–423
Gavrila DM, Munder S (2007) Multi-cue pedestrian detection and tracking from a moving vehicle. Int J Comput Vision 73(1):41–59
Coelingh E, Eidehall A, Bengtsson M (2010) Collision warning with full auto brake and pedestrian detection—a practical example of automatic emergency braking. In: Proceedings of IEEE ITSC’10, pp 55–160
Henn RW, Grotendiek T, Knoop S, Braeuchle C (2011) Active pedestrian protection by surround sensor technologies. In: Proceedings of 18th world congress on ITS, Florida, USA, 2011
Keller CG, Dang T, Fritz H, Joos A, Rabe C, Gavrila DM (2011) Active pedestrian safety by automatic braking and evasive steering. IEEE Trans Intell Transp Syst 12(4):1292–1304
Viola P, Jones M, Snow D (2003) Detecting pedestrians using patterns of motion and appearance. In: Proceedings of the ICCV’03, vol 2, pp 34–741
Munder S, Gavrila DM (2006) An experimental Study on pedestrian classification. IEEE Trans Pattern Anal Mach Intell 28(11):1863–1868
Raksincharoensak P, Takimoto Y, Muroi H, Shimizu I, Nagai M, Darms M, Adomat R (2009) Development of a pedestrian collision warning system by sensor fusion of monocular camera and millimeter wave radar. In: Proceedings of AAET 2009 symposium (Automatisierungs-, Assistenzsysteme und eingebettete Systeme für Transportmittel), Braunschweig, Germany, pp 1–10
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Raksincharoensak, P., Sakai, Y., Shimizu, I., Nagai, M., Ulbricht, D., Adomat, R. (2013). Development of an On-Board Pedestrian Detection System Using Monocular Camera for Driver Assistance Applications. In: Proceedings of the FISITA 2012 World Automotive Congress. Lecture Notes in Electrical Engineering, vol 197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33805-2_28
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DOI: https://doi.org/10.1007/978-3-642-33805-2_28
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