Blob trackers have become increasingly powerful in recent years largely due to the adoption of statistical appearance models which allow effective background subtraction and robus...
This paper addresses the problem of fully automated
mining of public space video data. A novel Markov Clustering
Topic Model (MCTM) is introduced which builds on
existing Dynami...
One problem with the adaptive tracking is that the data that are used to train the new target model often contain errors and these errors will affect the quality of the new target...
In this paper, we present a stream-based mining algorithm for online anomaly prediction. Many real-world applications such as data stream analysis requires continuous cluster opera...
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...