Moving object tracking method based on n-step-ahead prediction using artificial neural network algorithm

Faris Adnan Padhilah, Wahidin Wahab

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper described a method of tracking a moving object based on 1 to 5 step ahead prediction. The prediction was using the artificial neural network with back propagation method for training the network. The moving object used in the experiments is a small table tennis ball. The ANN structures have six inputs neurons and five outputs neurons with ten neurons in the hidden layer. Using 70% data of the object movement positions for training, and 30% data for testing the prediction of the ball positions. It was shown that the training of the ANN can achieved means square error (MSE) as small as 0.0091 for the X coordinate and 0.0012 for the Y coordinate. At the ball position prediction testing, it was shown that the method can achieved the MSE of 4.72% for X coordinate and MSE of 2.48% for Y coordinate.

Original languageEnglish
Title of host publicationProceedings of 2018 International Conference on Control and Computer Vision, ICCCV 2018
PublisherAssociation for Computing Machinery
Pages96-100
Number of pages5
ISBN (Electronic)9781450364706
DOIs
Publication statusPublished - 15 May 2018
Event2018 International Conference on Control and Computer Vision, ICCCV 2018 - Singapore, Singapore
Duration: 15 Jun 201818 Jun 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2018 International Conference on Control and Computer Vision, ICCCV 2018
Country/TerritorySingapore
CitySingapore
Period15/06/1818/06/18

Keywords

  • Back propagation
  • Ball position prediction
  • N-step ahead
  • Neural network

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