Center-biased frame selection algorithms for fast multi-frame motion estimation IN H.264

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Detail(s)

Original languageEnglish
Title of host publicationProceedings of 2003 International Conference on Neural Networks and Signal Processing, ICNNSP'03
Pages1258-1261
Volume2
Publication statusPublished - 2003

Publication series

Name
Volume2

Conference

Title2003 International Conference on Neural Networks and Signal Processing, ICNNSP'03
PlaceChina
CityNanjing
Period14 - 17 December 2003

Abstract

The new upcoming video coding standard, H.264, allows motion estimation performing on multiple reference frames. This new feature improves the prediction accuracy of inter-coding blocks significantly, but it is extremely computational intensive. Its reference software adopts a full search scheme. The complexity of multi-frame motion estimation increases linearly with the number of used reference frames. However, the distortion gain given by each reference frame varies with the motion content of the video sequence, and it is not efficient to search through all the candidate frames. In this paper, a novel center-biased frame selection method is proposed to speed up the multi-frame motion estimation process in H.264. We apply a center-biased frame selection path to identify the ultimate reference frame from all the candidates. Simulation results show that our proposed method can save about 77% computations constantly while keeping similar picture quality as compared to full search. © 2003 IEEE.

Citation Format(s)

Center-biased frame selection algorithms for fast multi-frame motion estimation IN H.264. / Ting, Chi-Wang; Po, Lai-Man; Cheung, Chun-Ho.

Proceedings of 2003 International Conference on Neural Networks and Signal Processing, ICNNSP'03. Vol. 2 2003. p. 1258-1261 1281099.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review