Fast analysis of scalable video for adaptive browsing interfaces
Mrak, M, Calic, J and Kondoz, A (2009) Fast analysis of scalable video for adaptive browsing interfaces Computer Vision and Image Understanding, 113 (3). 425 - 434. ISSN 1077-3142
Available under License : See the attached licence file.
Driven by a high demand for user-centred video interfaces and recent advances in scalable video coding technology, this work introduces a novel framework for video browsing by utilising inherently hierarchical compressed-domain features of scalable video and e cient dynamic video summarisation. This approach enables instant adaptability of generated video summaries to user requirements, available channel bandwidth as well as display size. By utilising compressed domain features an e cient hierarchical analysis of motion activity at di erent layers of complexity is achieved. Exploiting a contour evolution algorithm, a scale space of temporal video descriptors is generated, enabling dynamic video summarisation in real-time. Given the spatial resources of terminal display and generated video summary, the nal browsing layout is generated utilising an unsupervised robust spectral clus- tering technique and a fast discrete optimisation algorithm. Results show excellent scalability of the video browsing interface and good algorithm efficiency.
|Divisions :||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing|
|Date :||1 January 2009|
|Identification Number :||10.1016/j.cviu.2008.08.004|
|Related URLs :|
|Additional Information :||NOTICE: This is the author’s version of a work that was accepted for publication in Computer Vision and Image Understanding. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Vision and Image Understanding, 113(3), March 2009, DOI: 10.1016/j.cviu.2008.08.004|
|Depositing User :||Symplectic Elements|
|Date Deposited :||11 May 2012 14:57|
|Last Modified :||09 Jun 2014 13:30|
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