A Feature-Based Vehicle Tracking System in Congested Traffic Video Sequences

Authors:
Young-Kee Jung;Yo-Sung Ho
Affiliations:
-;-
Venue:
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Year:
2001

Citing 2
Cited 1

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A Real-time Computer Vision System for Measuring Traffic Parameters

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Learning sequences of sparse correlated patterns using small-world attractor neural networks: An application to traffic videos

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Abstract

This paper describes a new feature-based vehicle tracking system using trajectory matching, which extracts corner features of the vehicle and tracks the features using linear Kalman filtering, where features from the same vehicle are grouped together. We also propose a new grouping algorithm using trajectory matching to make our tracking system robust enough for segmenting different vehicles in the congested traffic situation. The proposed system has demonstrated good performance for crossway traffic video sequences.