Document Type
Conference Paper
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
1.2 COMPUTER AND INFORMATION SCIENCE
Abstract
Target tracking in a cluttered environment remains a challenging research topic. The task of target tracking is a key component of video surveillance and monitoring systems. In this paper, we present an improved CamShift algorithm for tracking a target in video sequences in real time. Firstly, a background-weighted histogram which helps to distinguish the target from the background and other targets is introduced. Secondly, the window size is calculated to track the target as its shape and orientation change. Finally, we use a Kalman Filter to avoid being trapped by a local maximum. The introduction of the Kalman Filter also enables track recovery following a total occlusion. Experiments on various video sequences illustrate the proposed algorithm performs better than the original CamShift approach.
DOI
https://doi.org/ 10.21427/9ybe-pd55
Recommended Citation
Zhang, C., Qiao, Y., & Fallon, E. (2009). An improved CamShift algorithm for target tracking in video surveillance. 9th IT&T Conference, Technological University Dublin, Dublin, Ireland, 22nd.-23rd. October. doi:10.21427/9ybe-pd55
Publication Details
Paper presented at the 9th. IT&T Conference, Technological University Dublin, Dublin, Ireland, 22nd.-23rd. October, 2009.