Cross-Correlation Tracking Technique for Extracting Speed from Cameras Under Adverse Conditions

Author:

Schoepflin Todd N.1,Dailey Daniel J.1

Affiliation:

1. University of Washington, Box 352500, Seattle, WA 98195-2500

Abstract

An algorithm to estimate speed from traffic surveillance cameras in a variety of traffic congestion, weather, and lighting conditions is presented. The features from the images are projected into a one-dimensional sub-space and transformed into a linear coordinate system by using a simplified camera model. A cross-correlation technique is used to summarize the movement of features through a group of images and to estimate mean speed for each lane of vehicles. A Kalman filter technique with a set of maximum-likelihood optimal parameters is used to estimate the traffic speed by lane to create an optimal space-averaged speed.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enhancing unsupervised video-based vehicle tracking and modeling for traffic data collection;Canadian Journal of Civil Engineering;2020-08

2. Video-Based Automated Identification of Freeway Shoulder Events;Transportation Research Record: Journal of the Transportation Research Board;2006-01

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