Detection and classification of vehicles

被引：464

作者：

Gupte, S ^{[1
]}

Masoud, O ^{[1
]}

Martin, RFK ^{[1
]}

Papanikolopoulos, NP ^{[1
]}

机构：

[1] Univ Minnesota, Dept Comp Sci & Engn, Minneapolis, MN 55455 USA

来源：

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | 2002年 / 3卷 / 01期

基金：

美国国家科学基金会;

关键词：

camera calibration; vehicle classification; vehicle detection; vehicle tracking;

D O I：

10.1109/6979.994794

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

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.

引用

页码：37 / 47

页数：11

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