This paper presents an alternative to distance-based neural networks. A distance measure is the underlying property on which many neural models rely, for example self-organizing ma...
We investigate the problem of anomaly detection for video surveillance applications. In our approach, we use a compression-based similarity measure to determine similarity between...
This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
The H.264 adopts various block types and multiple reference frames for motion compensation. For transcoding a video sequence from the H.263 format to the H.264 format, it is benef...
We propose an original approach for the characterization of video dynamic content with a view to supplying new functionalities for motion-based video indexing and retrieval with q...