- 學位論文
平行線段模型之車道偵測與具自動更新功能之車輛偵測
Piecewise-Linear Model for Lane Detection and Automatic Updating for Vehicle Detection
並列摘要
Every year many people died in traffic accidents, and the main factors are improper driving behavior or inattention to sudelen change in the surrounding environment. The circumstance stimulates the development of intelligent vehicles with driver assistance systems for enhancing the driving safety and efficiency. We are going to develop computer vision technologies as the core of such assistance system. We aim to detect the current lane region and vehicles in front of the host vehicle on road. The current lane region is bounded by two lane markings nearest to the host vehicle. For lane boundary detection, we propose a linear-piecewise lane model which has the ability to approximate arbitrary curves. For finding optimal configuration of the lane model, we first extract straight line segments and then group pairs of line segments by dynamic programming technique. For vehicle detection, we build a detector that slides a window over an image and verifies if the content inside the window represents a vehicle. The verification is based on a classifier trained by AdaBoost. Besides off-line training, we design an automatic on-line updating mechanism which can automatically learn new vehicle images and update the trained classifier. We develop and test our system on a personal computer. The test data is captured in urban scenes which contains hundreds of images.