Depth map coding by dense disparity estimation for MVD compression
作者： Marco Cagnazzo , Beatrice Pesquet-Popescu
DOI: 10.1109/ICDSP.2011.6005011
关键词: Depth map coding 、 Computer vision 、 Transmission bandwidth 、 Coding (social sciences) 、 Computer science 、 Pixel 、 User experience design 、 Multiview Video Coding 、 Depth map 、 Artificial intelligence 、 Multiple view
摘要: In multiview video representation, one of the most popular format is so-called multiple view plus depth. This representation made up N image sequences, each accompanied by a sequence depth maps, telling distance represented pixel from observing camera. The maps are needed at decoder side in order to generate intermediate views and therefore enrich user experience. very flexible but also demanding, terms storage space or transmission bandwidth. Therefore, compression needed. At this end, key steps an efficient maps. work we build over proposed method for coding, based on dense disparity estimation between views. allows us obtain compact high-quality depthmap representation. particular explore complex relationship encoding parameters, showing that optimal parameter set exist, fine-tuning phase adaption its results subsequent phase. Experiments encouraging, remarkable gain simple methods such as H.264/AVC simulcast, even some with respect more sophisticated techniques MVC.
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