| dc.description.abstract | A lot of traffic accidents are caused by driver’s incomplete understanding of the whole vehicle surroundings. To reduce the accidents caused by collision with surrounding obstacles, we mount four wide-angle cameras at the front, rear, and both sides of the vehicle to capture consecutive images; then we present a real-time surrounding top-view monitor and obstacle detection system for slow driving and parking assistance.
In offline steps of surrounding top-view monitor system, we first calibrate camera intrinsic parameters, distortion of lens, and vignetting effects of four wide-angle cameras. Then we calibrate the geometric relationships (extrinsic parameters) of four cameras using a proposed multi-camera calibration method. Third, we calculate the feathering weights of pixels on overlapped image areas to produce a seamless surrounding top-view image. At last, we build look-up tables for the mapping between the captured images and the surrounding synthesized image to speed up the processing. In online procedure, the proposed system interpolates and generates the surrounding synthesized image by those look-up tables directly.
In obstacle detection system, we utilize different algorithms for driving environments of different texture complexity. If texture of road surface is complicated, we can generally detect enough features for estimating the optical flow from captured images. After estimating ego-motion of vehicle, we can distinct the non-ground features and ground-features. Obstacle detection is performed based on static color information if the texture of road surface is simple, and no features for detection was found, then we can use color of road region to separate obstacles from road. In our experiment, the detection accuracy is about 88%. | en_US |