We develop a framework for the automatic discovery of query classes for query-class-dependent search models in multimodal retrieval. The framework automatically discovers useful q...
Design and development of novel human-computer interfaces poses a challenging problem: actions and intentions of users have to be inferred from sequences of noisy and ambiguous mu...
Vladimir Pavlovic, James M. Rehg, Ashutosh Garg, T...
In this paper, we propose a framework that can efficiently combine features for robust tracking based on fusing the outputs of multiple spatiogram trackers. This is achieved withou...
A new method for object tracking in video sequences is presented. This method exploits the benefits of particle filters to tackle the multimodal distributions emerging from clutte...
Alexandros Makris, Dimitrios I. Kosmopoulos, Stavr...
This paper describes revised content-based search experiments in the context of TRECVID 2003 benchmark. Experiments focus on measuring content-based video retrieval performance wi...