会议专题

N-LBP BASED VEHICLE MONITORING SYSTEM

In recent years, feature based object detection has attracted increasing attention in computer vision research community. However, to our best knowledge, no previous work has focused on utilizing local binary pattern (LBP) for vehicle detection in Intelligent Transportation System(ITS) domain. In this paper, we develop a novel traffic monitoring system based on N-LBP algorithm, which is the new LBP texture descriptor proposed. The approach includes three steps: firstly the general critical ingredients (GCI for short) are selected from LBP features through training to indicate vehicles. Then GCI are extracted from region of interest (ROI) in the new image for object detection and identification. Linear Kalman filter is employed for feature based tracking finally. Experimental results demonstrate the superiority of N-LBP feature over basic LBP feature, and performance of the new system is more stable and reliable.

ITS vehicle detection vehicle tracking N-LBP Kalman filter

Kunyan Lan Honggang Zhang Wenting Lu Jun Guo

Laboratory of Pattern Recognition and Intelligent System, Beijing University of Posts and Telecommun Laboratory of Pattern Recognition and Intelligent System,Beijing University of Posts and Telecommuni

国际会议

2009 IEEE International Conference on Network Infrastructure and Digital Content(2009年IEEE网络基础设施与数字内容国际会议 IEEE IC-NIDC2009)

北京

英文

701-706

2009-11-06(万方平台首次上网日期,不代表论文的发表时间)