Temporal scalable decoding process with frame rate conversion method for surveillance video

Wenxin Yu, Xin Jin, Satoshi Goto

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

This paper proposed a temporal scalable decoding process with frame rate conversion method for surveillance video. This method can be used to reduce the computational complexity in the decoding process and keep the video quality at the same time, and make the single layer bit stream sources much more flexible for various terminal devices. It is realized based on frame-skipping conception with the proposed reference frame index decision algorithm, motion vector composition algorithm and block-partition mode decision algorithm. Compare with the frame rate conversion in transcoding process, it is much lower complexity and more flexible. Through the experimental results, the reduction of computational complexity (decoding time) depends on the number of skipped frames, the more frames was skipped the more reduction of the computational complexity will be got. The PSNR loss is very small (about 0.1 ∼ 0.2 (dB)) for B frame skipping. And the PSNR loss is about 0.7 ∼ 2 (dB) (the loss of SSIM is only 0.002 ∼ 0.007) for 2/3 P frame skipping and reduce the computational complexity about 60%.

本文言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ページ297-308
ページ数12
6298 LNCS
PART 2
DOI
出版ステータスPublished - 2010
イベント11th Pacific Rim Conference on Multimedia, PCM 2010 - Shanghai
継続期間: 2010 9 212010 9 24

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
番号PART 2
6298 LNCS
ISSN(印刷版)03029743
ISSN(電子版)16113349

Other

Other11th Pacific Rim Conference on Multimedia, PCM 2010
CityShanghai
Period10/9/2110/9/24

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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