The advances of video technology and video-related applications demand appropriate video semantic models for representing video data and their semantics, and supporting powerful s...
Existing research on news video analysis mainly concentrates on structure analysis, semantic concept detection, annotation and search. However, little work has been contributed to...
Efficient multimodal fusion is a key feature of future video indexing systems. Hidden Markov Models provide a powerful framework for video structure analysis but they require all...
In this work we present a novel multi-modal mixed-state dynamic Bayesian network (DBN) for robust meeting event classification. The model uses information from lapel microphones,...
This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the ...