A Robust Multi-Camera Approach to Object Tracking and Position Determination using a Self-Organising Map Initialised through Cross-Ratio Generated "Virtual Points"
Meagher, Tim, Maire, Frederic D., & Wong, On (2004) A Robust Multi-Camera Approach to Object Tracking and Position Determination using a Self-Organising Map Initialised through Cross-Ratio Generated "Virtual Points". In Mohammadian, Masoud (Ed.) International Conference on Computational Intelligence for Modelling Control and Automation - CIMCA'2004, 12 - 14 July 2004, Sheraton Mirage Hotel, Gold Coast, Australia.
This paper presents a new method for the tracking of an object, and the determination of its absolute position using the image coordinates provided from multiple cameras. Existing methods used in multi-camera tracking systems require the calibration of all camera parameters, with re-calibration needed when cameras are moved. The proposed method obtains the image coordinates of an object at known locations and generates "virtual points" that are used as initial codebook vectors in a Self-Organising Map. This is achieved through a novel use of the cross-ratio invariance. The use of the Self-Organising Map also allows for camera movement, addition and removal without the need for re-calibration. Experimental results are presented demonstrating the tracking capability of the system.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||Object tracking, multi camera systems|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2004 (please consult author)|
|Deposited On:||04 Jan 2006|
|Last Modified:||29 Feb 2012 13:08|
Repository Staff Only: item control page