An improvement of kernel-based object tracking based on human perception
The objective of the paper is to embed perception rules into the kernel-based target tracking algorithm and to evaluate to what extent these rules are able to improve the original tracking algorithm, without any additional computational cost. To this aim, the target is represented through features that are related to its visual appearance; then, it is tracked in subsequent frames using a metric that, again, correlates well with the human visual perception (HVP).