Vision-Based Driver Assistance System using Integration Information from Lane Geometry and Traffic Direction
Date Issued
2007
Date
2007
Author(s)
Huang, Chan-Yu
DOI
en-US
Abstract
This thesis presents an approach to detect multiple lane and vehicles. Instead of assuming that the processes of lane and vehicle detection should do independently, we integrate these two processes in a mutually supporting way to achieve more accurate results.
In lane boundary detection, the process of identifying possible features of a lane boundary is often affected by the edges and color of the vehicles on the road. Likewise, the results of vehicle detection could be non-robust if there are some background features which can confuse the process of indentifying possible vehicle features.
Thus, in the thesis, we use the distance between the central position of a lane and the position of the hypothesized vehicle to filter out the non-vehicle object. And we use the similarity between the lane boundary direction and the moving directions of the hypothesized vehicles to get the optimal lane solution. By applying iterative optimization algorithm, we can obtain the near-optimal solutions of both lane and vehicle detections. Finally the experimental results are provided to validate the effectiveness of the proposed novel approach.
Subjects
多車輛偵測
多車道線偵測
曲線車道線偵測
multiple vehicle detection
multiple lane detection
integratio framework
curve lane detection
Type
thesis
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