This paper considers the problems of feature variation and concept uncertainty in typical learning-based video semantic classification schemes. We proposed a new online semantic c...
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
A dynamic classification using the support vector machine (SVM) technique is presented in this paper as a new `incremental' framework for multiple-classifying video stream da...
In this paper, we will propose a novel semi-automatic annotation scheme for video semantic classification. It is well known that the large gap between high-level semantics and low...
This paper proposes a framework to aid video analysts in detecting suspicious activity within the tremendous amounts of video data that exists in today’s world of omnipresent su...