In this paper, we propose a generative model-based approach for audio-visual event classification. This approach is based on a new unsupervised learning method using an extended p...
Ming Li, Sanqing Hu, Shih-Hsi Liu, Sung Baang, Yu ...
This paper presents an approach for indexing a large set of videos by considering the dynamic behaviour of local visual features along the sequences. The proposed concept is based...
In intracranial pathological examinations using CT scan, brain midline shift (MLS) is an important diagnostic feature indicating the pathological severity and patient's survi...
To exploit co-occurrence patterns among features and target semantics while keeping the simplicity of the keywordbased visual search, a novel reranking methods is proposed. The ap...
We present a probabilistic framework for correspondence and egomotion. First, we suggest computing probability distributions of correspondence. This has the advantage of being rob...