Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - An Efficient Visual Tracking Method for Multiple Moving Targets
AU - Chen, Xiaohui
AU - Bull, David R.
AU - Mihaylova, Lyudmila
AU - Canagarajah, Nishan
PY - 2007
Y1 - 2007
N2 - An efficient algorithm of the edge detection according to integrating the edge gradient with the average filter is proposed, which can significantly reduce sensitivity of the background subtraction method to noise and illumination. Taking into account the features of the target such as colour, size, etc., a new modified nearest neighbour (NN) algorithm for data association using the target features is designed. A designed interacting multiple model (IMM) filter is utilized to track the maneuvering target motion, i.e. the feature point (called the centroid of the target) motion of the target. The algorithms are validated via an example with natural video sequences. The results show the algorithms are performances and validity for visual tracking. In complex environment, the algorithm can still work well.
AB - An efficient algorithm of the edge detection according to integrating the edge gradient with the average filter is proposed, which can significantly reduce sensitivity of the background subtraction method to noise and illumination. Taking into account the features of the target such as colour, size, etc., a new modified nearest neighbour (NN) algorithm for data association using the target features is designed. A designed interacting multiple model (IMM) filter is utilized to track the maneuvering target motion, i.e. the feature point (called the centroid of the target) motion of the target. The algorithms are validated via an example with natural video sequences. The results show the algorithms are performances and validity for visual tracking. In complex environment, the algorithm can still work well.
U2 - 10.1109/CISW.2007.4425488
DO - 10.1109/CISW.2007.4425488
M3 - Conference contribution/Paper
SN - 978-0-7695-3073-4
SP - 267
EP - 270
BT - Computational Intelligence and Security Workshops, 2007. CISW 2007. International Conference on
PB - IEEE Computer Society
CY - Washington, DC, USA
ER -