基于视点预测的全景视频码率自适应策略.

To solve the problems of video freezes and low quality of experience (QoE) in panoramic video transmission, this paper proposed a bitrate adaptive strategy based on viewpoint prediction (VPBAS) by studying the current popular viewpoint adaptive transmission scheme.Firstly, this paper constructed a viewpoint prediction model based on long short-term memory network and full convolutional network.The model concatenated the viewpoint data and video saliency information to realize the mutual complement and correction of different modal data, so as to improve the accuracy of viewpoint prediction.Secondly, the client used the random forest algorithm to predict the current available bandwidth, and selected the bitrate for video segments according to the prediction results and available bandwidth information.Finally, the client sent the selected bitrate information to the server regularly, and the server pushed the panoramic video stream of the best bitrate to the client according to the feedback information.It repeated this interactive process continuously during the video playback until the client finished watching.Experimental results show that VPBAS can effectively improve the user’s viewing experience under bandwidth limitation compared with other schemes. [ABSTRACT FROM AUTHOR]