TY - GEN
T1 - Algorithm of target tracking based on mean shift with RBF neural network
AU - Zhou, Bin
AU - Wang, Junzheng
AU - Mao, Jiali
PY - 2008
Y1 - 2008
N2 - The limitation of Mean Shift algorithm under crossing occlusion is analyzed. To solve this problem, a new tracking algorithm using Mean Shift with RBF neural network is proposed. According to the formal information about the object's location, the iteration start position is found with RBF neural network. And the object's real center is calculated by Mean Shift algorithm. Experimental results show that the proposal algorithm is stable to solve the crossing occlusion problem, and the iteration number is reduced.
AB - The limitation of Mean Shift algorithm under crossing occlusion is analyzed. To solve this problem, a new tracking algorithm using Mean Shift with RBF neural network is proposed. According to the formal information about the object's location, the iteration start position is found with RBF neural network. And the object's real center is calculated by Mean Shift algorithm. Experimental results show that the proposal algorithm is stable to solve the crossing occlusion problem, and the iteration number is reduced.
KW - Mean shift algorithm
KW - Motion object tracking
KW - RBF neural network
UR - http://www.scopus.com/inward/record.url?scp=52449091553&partnerID=8YFLogxK
U2 - 10.1109/CHICC.2008.4605198
DO - 10.1109/CHICC.2008.4605198
M3 - Conference contribution
AN - SCOPUS:52449091553
SN - 9787900719706
T3 - Proceedings of the 27th Chinese Control Conference, CCC
SP - 518
EP - 521
BT - Proceedings of the 27th Chinese Control Conference, CCC
T2 - 27th Chinese Control Conference, CCC
Y2 - 16 July 2008 through 18 July 2008
ER -