Detection and classification of vehicles
Detection and classification of vehicles
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DOI：
10.1109/6979.994794
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发表时间：
2002-03-01
影响因子：
8.5
通讯作者：
Papanikolopoulos, NP
中科院分区：
文献类型：
--
作者：
Gupte, S;Masoud, O;Papanikolopoulos, NP
本文提出了一种基于视觉的交通场景单目图像序列车辆检测与分类算法。处理在三个级别上完成：原始图像、区域级别和车辆级别。将车辆建模为具有一定动态特性的矩形块。该方法基于车辆在图像序列中移动时区域和车辆之间的对应关系的建立。高速公路场景的实验结果验证了该方法的有效性。我们还简要介绍了我们开发的交互式相机校准工具，该工具用于使用用户选择的图像中的特征恢复相机参数。
This paper presents algorithms for vision-based detection and classification of vehicles in monocular image sequences of traffic scenes recorded by a stationary camera. Processing is done at three levels: raw images, region level, and vehicle level. Vehicles are modeled as rectangular patches with certain dynamic behavior. The proposed method is based on the establishment of correspondences between regions and vehicles, as the vehicles move through the image sequence. Experimental results from highway scenes are provided which demonstrate the effectiveness of the method. We also briefly describe an interactive camera calibration tool that we have developed for recovering the camera parameters using features in the image selected by the user.