Video Transcoding Algorithm through Visual Attention Model Analysis for H.264/AVC

• Main Authors: Shih-meng Chen, 陳世孟
• Other Authors: Chia-Hung Yeh
• Format: Others
• Language: en_US
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/16035153361160593462

碩士 === 國立中山大學 === 電機工程學系研究所 === 96 === The proposed transcoding system consists of the spatial-resolution reduction and the temporal-resolution reduction method via visual attention model analysis. In the spatial domain, the visual attention model can be used to obtain the visual attention region. Then, the bitrate can be reduced since we can extract attention region of the original frame. The attention region conveys the same concept as that of the original frame. In the temporal domain, a frame skipping algorithm is proposed for reducing the temporal resolution to fit the channel target bitrate. The visual attention model is employed to measure the frame complexity in order to determine whether the frames should be skipped or not. Then, we can preserve the significant frames to avoid jerky effect. After combining with the motion vector composition algorithm, we can speedup the transcoding process with slight quality degradation.