Tracking of moving objects using neural network

K. C. Chan, S. S. Leong, J. Xie, G. C.L. Lin, B. Shirinzadeh

Research output: Contribution to conferencePaper


This paper presents a new technique for tracking of two dimensional moving objects. The approach is a hybrid consisting of an algorithm for next position prediction using an estimated jerk, and a neural network for pose (position and orientation) determination. A three layer feed-forward perceptron with back-propagation is implemented as a mapping approximator to determine the object pose from the area information contained in a localized processing window. Objects with arbitrary shapes can be tracked after the network is properly trained. The experimental result of the implementation of this algorithm is also presented.

Original languageEnglish
Number of pages4
Publication statusPublished - 1 Dec 1992
Externally publishedYes
EventProceedings of the 1992 Japan - USA Symposium on Flexible Automation Part 1 (of 2) - San Francisco, United States of America
Duration: 13 Jul 199215 Jul 1992


ConferenceProceedings of the 1992 Japan - USA Symposium on Flexible Automation Part 1 (of 2)
Country/TerritoryUnited States of America
CitySan Francisco

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