Low-cost sensor to detect overtaking based on optical flow

被引:5
作者
Guzman, Pablo [1 ]
Diaz, Javier [1 ]
Ralli, Jarno [1 ]
Agis, Rodrigo [1 ]
Ros, Eduardo [1 ]
机构
[1] Univ Granada, CITIC UGR, ETSI Informat & Telecomunicac, Dept Comp Architecture & Technol, Granada, Spain
关键词
Machine vision; Intelligent sensors; Collision-avoidance systems; Lane-change decision aid systems; PROCESSOR ARRAY;
D O I
10.1007/s00138-011-0392-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The automotive industry invests substantial amounts of money in driver-security and driver-assistance systems. We propose an overtaking detection system based on visual motion cues that combines feature extraction, optical flow, solid-objects segmentation and geometry filtering, working with a low-cost compact architecture based on one focal plane and an on-chip embedded processor. The processing is divided into two stages: firstly analog processing on the focal plane processor dedicated to image conditioning and relevant image-structure selection, and secondly, vehicle tracking and warning-signal generation by optical flow, using a simple digital microcontroller. Our model can detect an approaching vehicle (multiple-lane overtaking scenarios) and warn the driver about the risk of changing lanes. Thanks to the use of tightly coupled analog and digital processors, the system is able to perform this complex task in real time with very constrained computing resources. The proposed method has been validated with a sequence of more than 15,000 frames (90 overtaking maneuvers) and is effective under different traffic situations, as well as weather and illumination conditions.
引用
收藏
页码:699 / 711
页数:13
相关论文
共 31 条
[1]  
Alcantarilla P.F., 2008, IEEE INT VEH S EINDH
[2]   Vehicle and guard rail detection using radar and vision data fusion [J].
Alessandretti, Giancarlo ;
Broggi, Alberto ;
Cerri, Pietro .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2007, 8 (01) :95-105
[3]  
[Anonymous], EYE RIS CMOS VISION
[4]  
[Anonymous], 2000, Transportation human factors, DOI DOI 10.1207/STHF02031
[5]  
[Anonymous], IEEE INT WORKSH CELL
[6]   Real-time lane and obstacle detection on the gold system [J].
Bertozzi, M ;
Broggi, A .
PROCEEDINGS OF THE 1996 IEEE INTELLIGENT VEHICLES SYMPOSIUM, 1996, :213-218
[7]  
Blanc N, 2007, 2007 IEEE INTELLIGENT VEHICLES SYMPOSIUM, VOLS 1-3, P1097
[8]  
Broggi A., 1996, INTEGR COMPUT AIDED, V4
[9]  
Davis L.S., 1975, Computer Graphics and Image Processing, V4, P248
[10]  
de la Escalera A., 2001, VISION COMPUTADOR FU