A dynamic probabilistic multimedia retrieval model

We describe the application of a probabilistic multimedia model to video retrieval. From video shots, we compute Gaussian-mixture models that capture correlations in time and space, such as the appearance and disappearance of objects. These models improve the precision of "query by example/s" results in the TRECVID 2003 collection when compared to models that only make use of static visual information. Furthermore, integrated with information from automatic speech recognition (ASR) transcripts, they outperform ASR only results.