TY - GEN
T1 - Moving object tracking method based on n-step-ahead prediction using artificial neural network algorithm
AU - Padhilah, Faris Adnan
AU - Wahab, Wahidin
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/5/15
Y1 - 2018/5/15
N2 - 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.
AB - 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.
KW - Back propagation
KW - Ball position prediction
KW - N-step ahead
KW - Neural network
UR - http://www.scopus.com/inward/record.url?scp=85055313113&partnerID=8YFLogxK
U2 - 10.1145/3232651.3232674
DO - 10.1145/3232651.3232674
M3 - Conference contribution
AN - SCOPUS:85055313113
T3 - ACM International Conference Proceeding Series
SP - 96
EP - 100
BT - Proceedings of 2018 International Conference on Control and Computer Vision, ICCCV 2018
PB - Association for Computing Machinery
T2 - 2018 International Conference on Control and Computer Vision, ICCCV 2018
Y2 - 15 June 2018 through 18 June 2018
ER -