Abstract: The present disclosure seeks to perform real-time video streaming on a mobile device toward maintaining user QoE even under bandwidth constraints while being acceptable to the lightweight computing capacity of the mobile device. To this end, the embodiments apply deep neural network-based SR to a small number of pre-selected video frames and utilize the video frames to which SR is applied to enhance the resolution of the remaining frames, wherein the pre-selected frames are chosen for SR within a preset quality margin. Additionally, the present disclosure provides an apparatus and a method for SR acceleration for real-time video streaming under the lightweight computing capacity and video-specific constraints of a mobile device, which allow a server to deliver multiple options on a deep neural network and a cache profile including SR application information and enable the mobile device to select an option suitable for its computing capacity.

Abstract: The present disclosure seeks to perform real-time video streaming on a mobile device toward maintaining user QoE even under bandwidth constraints while being acceptable to the lightweight computing capacity of the mobile device. To this end, the embodiments apply deep neural network-based SR to a small number of pre-selected video frames and utilize the video frames to which SR is applied to enhance the resolution of the remaining frames, wherein the pre-selected frames are chosen for SR within a preset quality margin. Additionally, the present disclosure provides an apparatus and a method for SR acceleration for real-time video streaming under the lightweight computing capacity and video-specific constraints of a mobile device, which allow a server to deliver multiple options on a deep neural network and a cache profile including SR application information and enable the mobile device to select an option suitable for its computing capacity.