Real-Time Vehicle Detection in Urban Traffic Using AdaBoost

被引：4

作者：

Park, Jong-Min ^{[1
]}

Choi, Hyun-Chul ^{[1
]}

Oh, Se-Young ^{[1
]}

机构：

[1] Pohang Univ Sci & Technol POSTECH, Pohang 790784, Gyeongbuk, South Korea

来源：

IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010) | 2010年

关键词：

D O I：

10.1109/IROS.2010.5652639

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a method for detecting vehicles in urban traffic. The proposed method extracts vehicle candidates using AdaBoost. The candidate extraction process was speeded up further, exploiting inverse perspective transform matrix. Then the vehicle candidates were verified by the existence of vertical and horizontal edges. The detected vehicle regions were corrected by the vertical edges and shadow. Our algorithm showed the detection rate of 90.77% in urban traffic under normal lighting condition. The proposed algorithm can also detect vehicles in heavy rain. Our algorithm takes 37.13ms on average to detect vehicles in 320 by 240 images on a laptop computer (Intel (R) Core (TM) 2 T7200, 2.00GHz, 1.00GB RAM).

引用

页码：3598 / 3603

页数：6

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