Adaptive Visual System for Tracking Low Resolution Colour Targets

Bowden, R and KaewTraKulPong, P (2001) Adaptive Visual System for Tracking Low Resolution Colour Targets In: 12th British Machine Vision Conference (BMVC2001), 2001-09-10 - 2001-09-13, Manchester, UK.

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Abstract

This paper addresses the problem of using appearance and motion models in classifying and tracking objects when detailed information of the object’s appearance is not available. The approach relies upon motion, shape cues and colour information to help in associating objects temporally within a video stream. Unlike previous applications of colour in object tracking, where relatively large-size targets are tracked, our method is designed to track small colour targets. Our approach uses a robust background model based around Expectation Maximisation to segment moving objects with very low false detection rates. The system also incorporates a shadow detection algorithm which helps alleviate standard environmental problems associated with such approaches. A colour transformation derived from anthropological studies to model colour distributions of low-resolution targets is used along with a probabilistic method of combining colour and motion information. This provides a robust visual tracking system which is capable of performing accurately and consistently within a real world visual surveillance arena. This paper shows the system successfully tracking multiple people moving independently and the ability of the approach to recover lost tracks due to occlusions and background clutter.

Item Type:	Conference or Workshop Item (Conference Paper)
Subjects :	Computing
Divisions :	Faculty of Engineering and Physical Sciences > Computing Science
Authors :	Name Email ORCID Bowden, R KaewTraKulPong, P
Date :	10 September 2001
DOI :	10.5244/C.15.26
Copyright Disclaimer :	Copyright © BMVC 2001
Contributors :	Contribution Name Email ORCID Cootes, T Taylor, C
Depositing User :	Symplectic Elements
Date Deposited :	26 Oct 2016 15:35
Last Modified :	31 Oct 2017 18:51
URI:	http://epubs.surrey.ac.uk/id/eprint/812631

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