结合车辆检测和分割提高消失点精度

Fumiaki Sato, T. Koshizen
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摘要

为了减少混合交通流条件下涉及两轮和四轮车辆的侧滑和碰撞事故,我们之前创建了一个智能手机应用程序(app),用于预测两轮车辆的加速和行驶车道行为。在该系统中,通过智能手机摄像头拍摄的道路图像检测车辆,并通过投影转换算法估计车辆在道路上的位置。但是,对于这款app,需要提高相机图像中消失点计算的准确性。因此,为了降低计算成本,我们创建了一种将道路分割和车辆检测相结合的方法,创建了一种新的方案,即使在没有车道线的道路上也可以检测道路边缘和消失点。这些改进将有助于保持消失点计算的准确性,同时促进其高实时特性。
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Improved Vanishing Point Accuracy by Integrating Vehicle Detection and Segmentation
To reduce sideswipes and collision accidents involving two- and four-wheeled vehicles under mixed traffic flow conditions, we previously created a smartphone application (app) that predicts acceleration and driving lane behaviors of two-wheeled vehicles. In this system, vehicles are detected from road images taken by a smartphone camera, and vehicles positions on the road are estimated by our projection conversion algorithm. However, regarding that app, it is necessary to improve the accuracy of the vanishing point calculations in the camera images. Accordingly, in order to reduce calculation costs, we created a method that integrates road segmentation and vehicle detection to create a new scheme for detecting road edges and the vanishing point, even on roads without lane lines. These improvements will help maintain the accuracy of vanishing point calculations while facilitating their high real-time characteristics.
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