Locally accurate motion estimation for object-based video coding

Michael K. Steliaros; Graham R. Martin; Roger A. Packwood

doi:10.1117/12.298342

9 January 1998 Locally accurate motion estimation for object-based video coding

Michael K. Steliaros, Graham R. Martin, Roger A. Packwood

Proceedings Volume 3309, Visual Communications and Image Processing '98; (1998) https://doi.org/10.1117/12.298342
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

Abstract

We describe new motion coding algorithms that develop fixed size block matching (FSBM) into variable sized block matching (VSBM) and a modified approach (MVSBM) which can exploit irregularly shaped areas of uniform motion. New generations of video coding standards handle arbitrary shaped visual objects as well as frame based input. We explain how MVSBM strategies work when combining shaped data and block based algorithms. Locally accurate motion information is produced by the combination of otherwise ambiguous estimates produced by the small area matching required to detect locally diverse movements. The success of various prediction strategies indicates that the motion information is well behaved and thus likely to be accurate, given complex natural image sequence source material. MVSBM is evaluated by forcing it to perform with the same quality prediction as FSBM, then comparing the number of bits required by each technique. FSBM vector coding methods are taken from H.263 and MPEG-4 for comparison with those developed for MVSBM, extra compression phases are developed for MVSBM by utilizing the greater structure of the representation. Results are presented for three MPEG-4 test sequences, 'Container', 'weather' and 'Stefan'. We show bit savings of 67 percent for 'container', and 13 percent for 'Stefan' with more complex object activity.

Citation Download Citation

Michael K. Steliaros, Graham R. Martin, and Roger A. Packwood "Locally accurate motion estimation for object-based video coding", Proc. SPIE 3309, Visual Communications and Image Processing '98, (9 January 1998); https://doi.org/10.1117/12.298342

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