Presentation 1999/2/2
Video Coding based upon Learning Motion Vector Quantization
Keiichirou HOSOISHI, Ryuji HAMABE,
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Abstract(in English) We have already proposed Learning Motion Vector Quantization (LMVQ) that can eliminate the optimal codebook design procedure on Motion Vector Quantization (MVQ). In addition to motion estimation, this LMVQ method is simultaneously to do the codebook learning according to the nature of input image. In this paper, we will show a learning method that refers to the frequency counters of codewords at codebook learning and report the simulation results employing the Flower Garden video data. In performance evaluation of motion compensation, the SNR of this method was better than that of MVQ. In comparison with MPEG-1, although the SNR or LMVQ was about 0.4dB poorer, we could achieve the significant results such as reducing the computer amount of motion compensation to 1/11 and shortening the total processing time to 33%.
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Keyword(in English) video coding / motion vector quatization / learning vector quantization
Paper # EID98-157
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Conference Date 1999/2/2(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Video Coding based upon Learning Motion Vector Quantization
Sub Title (in English)
Keyword(1) video coding
Keyword(2) motion vector quatization
Keyword(3) learning vector quantization
1st Author's Name Keiichirou HOSOISHI
1st Author's Affiliation Department of Communication and Computer Engineering, Fukuoka Institute of Technology()
2nd Author's Name Ryuji HAMABE
2nd Author's Affiliation Department of Communication and Computer Engineering, Fukuoka Institute of Technology
Date 1999/2/2
Paper # EID98-157
Volume (vol) vol.98
Number (no) 573
Page pp.pp.-
#Pages 6
Date of Issue