Title :
Omnidirectional stereo vision based vehicle detection and distance measurement for driver assistance system
Author :
Donguk Seo ; Hansung Park ; Kanghyun Jo ; Kangik Eom ; Sungmin Yang ; Taeho Kim
Author_Institution :
Grad. Sch. of Electr. Eng., Univ. of Ulsan, Ulsan, South Korea
Abstract :
This paper proposes the driver assistance system based on the omnidirectional stereo vision. This system informs a driver to prepare unexpected situation during driving. This information is a relative distance between a preceding car and driving vehicle and obtained by using the omnidirectional stereo vision. The omnidirectional camera sees 360 degrees unlike a conventional perspective camera. Therefore it is useful to search the road conditions nearby a driving vehicle at every sequence. For detecting a preceding car, we use histogram of oriented gradient (HOG) which has is robustness to for illumination change. Because of stereo vision, the proposed algorithm measures the relative distance between preceding car and moving vehicle whenever preceding car is detected. In experiments, the ratio of detecting preceding car is 99.78% and 94.59% for left and right cameras respectively. The measurement process of relative distance is started when preceding car is detected both left and right cameras and the system detects a center point of tail right. In the measurement process, if a preceding car is not detected from left or right image scene, the system estimates the center point using optical flow consider with previous frame. The maximum error of estimated distance is less than 25cm shown in the Fig 9. Therefore the error of estimated distance is quite ignorable value because the normal relative distance between two moving car is over 2m.
Keywords :
driver information systems; gradient methods; image sensors; image sequences; object detection; road vehicles; stereo image processing; HOG; cameras; distance measurement; driver assistance system; driving vehicle; histogram of oriented gradient; omnidirectional stereo vision based vehicle detection; optical flow; preceding car; road conditions; unexpected situation; Calibration; Cameras; Histograms; Stereo vision; Vectors; Vehicle detection; Vehicles;
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
DOI :
10.1109/IECON.2013.6700034