Hybrid Object-Based Video Compression Scheme Using a Novel Content-Based Automatic Segmentation Algorithm

Nick A. Tsoligkas, Donglai Xu, Ian French

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Abstract

This paper describes a hybrid object-based video coding scheme that achieves efficient compression by separating moving objects from stationary background and transmitting the shape, motion and residuals for each segmented object. In this scheme, a new content-based object segmentation algorithm is proposed, which does not assume any prior modeling of the objects being segmented. The binarization process, which finds large object regions, is based on a threshold function that calculates block histograms and takes image noise into account. The resultant binary mask is further processed using morphological operations. The motion vectors are estimated inside the change detection mask using block-matching method between two successive frames, and then the dense motion field is estimated using the motion vectors and the Horn-Schunck algorithm.
Original languageEnglish
Title of host publicationIEEE International Conference on Communications
Pages2654-2659
DOIs
Publication statusPublished - 2007
Event2007 IEEE International Conference on Communications - Glasgow, Scotland, United Kingdom
Duration: 24 Jun 200728 Jun 2007

Conference

Conference2007 IEEE International Conference on Communications
CountryUnited Kingdom
CityScotland
Period24/06/0728/06/07

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    Tsoligkas, N. A., Xu, D., & French, I. (2007). Hybrid Object-Based Video Compression Scheme Using a Novel Content-Based Automatic Segmentation Algorithm. In IEEE International Conference on Communications (pp. 2654-2659) https://doi.org/10.1109/ICC.2007.440