TY - GEN
T1 - Temporal scalable decoding process with frame rate conversion method for surveillance video
AU - Yu, Wenxin
AU - Jin, Xin
AU - Goto, Satoshi
PY - 2010
Y1 - 2010
N2 - 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%.
AB - 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%.
KW - frame rate conversion
KW - frame-skipping
KW - low complexity
KW - surveillance video
KW - temporal scalable decoding
UR - http://www.scopus.com/inward/record.url?scp=78049428671&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78049428671&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15696-0_28
DO - 10.1007/978-3-642-15696-0_28
M3 - Conference contribution
AN - SCOPUS:78049428671
SN - 3642156959
SN - 9783642156953
VL - 6298 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 297
EP - 308
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 11th Pacific Rim Conference on Multimedia, PCM 2010
Y2 - 21 September 2010 through 24 September 2010
ER -