Mitsubishi Electric Research Laboratories, Inc.

Michael A Casey

Regunathan Radhakrishnan

Ajay Divakaran

A method segments a compressed video by extracting audio and visual features from the compressed video. The audio features are clustered according to K-means clustering in a set of classes, and the compressed video is then partitioned into first segments according to the set of classes. The visual features are then used to partitioning each first segment into second segments using motion analysis. Summaries of the second segments can be provided to assist in the browsing of the compressed video.

Audio-assisted video segmentation and summarization

A method extracts features from a mixture of signals. The method filters the mixture of signals by a filterbank to produce a plurality of band-pass signals. Each band-pass signal is windowed to produce a plurality of multi-dimensional observation matrices. The multi-dimensional observation matrices are reduced in their dimensionality. Features are extracted from the reduced dimensionality matrices using independent component analysis. The features can include temporal and spectral characteristics.

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Cambridge, MA, United States of America

Michael A Casey