| dc.description.abstract | In these few decades, the vehicle number is rapidly increasing due to people’s incomes increasing. In addition to the vehicle number, more factors of road situation, driving environment, and human attention result in a large amount of traffic accidents and casualties. If there is a mechanism to help the driver to detect the road situation and driving environment, and then provide some useful information to the driver in these situations, the danger is therefore avoided. It is important to develop real-time automotive driver assistance systems. Pedestrian collision avoidance is one of the important issues. In this study, we propose a method to get depth information with binocular stereo vision, and apply to pedestrian detection in front of the vehicle. Moreover, we use homography to detect obstacles to avoid the close collision.
In pedestrian detection system, we first adjust the illumination and vertical position of the image pair. Then, we use associated dynamic programming to generate disparity map. Thirdly, we use morphology to reduce noise. Finally, we generate connected component to detect pedestrians or obstacles and estimate distances based on the disparity.
In parking assistance system, we first use camera calibration to get the transform matrices between the cameras and the ground coordinate system. Then, we transform left image into the right image plane via the ground coordinate system. Thirdly, we subtract the right original image and the re-projected image to generate a difference image. Fourthly, we use morphology to reduce the noise in the difference image. Finally, we generate connected component from the difference image to detect obstacles.
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