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Parametric Motion Vector Prediction for Hybrid Video Coding
Citation key 1347Tok2012
Author Michael Tok and Alexander Glantz and Andreas Krutz and Thomas Sikora
Title of Book Proceedings of the 29th IEEE Picture Coding Symposium (PCS 2012)
Year 2012
Address Kraków, Poland
Month may
Note ISBN: 978-1-4577-2048-2
Organization IEEE
Abstract Motion compensated prediction still is the main technique for redundancy reduction in modern hybrid video codecs. However, the resulting motion vector fields are highly redundant as well. Thus, motion vector prediction and difference coding are used for compressing. One drawback of all common motion vector prediction techniques is, that they are not able to predict complex motion as rotation and zoom efficiently. We present a novel parametric motion vector predictor (PMVP), based on higher-order motion models to overcome this issue. To transmit the needed motion models, an efficient compression scheme is utilized. This scheme is based on transformation, quan- tization and difference coding. By incorporating this predictor into the HEVC test model HM 3.2 gains of up to 2.42% are achieved.
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