Abstract
Multi-view video consists of multiple views which are shot simultaneously by multiple cameras from different viewpoints. Users can watch the video while choosing a viewpoint from them freely. In the multi-view video streaming, we need to deal with a problem that the multi-view videos put an enormous burden on the network for delivering because of transmitting many videos at a same time. Hierarchical multi-view streaming(HMVS) has been proposed as one of the methods of reducing the transmission quantity of multi-view video. The prediction of switching viewpoints is necessary for bandwidth allocation in HMVS. In this paper, we propose a viewpoint switching prediction model based on viewing logs for HMVS. The proposed model divides the sequence of multi-view video into some scenes and learns the probability of switching viewpoints for each scene from viewing logs. Through the evaluation experiment, the proposed model achieved effective viewpoint switching predictions.
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call