A Real-time Virtual Reality Adaptive Streaming System

Cloud VR (Virtual Reality) is a VR scheme based on cloud computing, which can reduce the computing burden on terminal equipment. It uses edge computing for adaptive streaming to minimize the response latency and bandwidth consumption. However, traditional adaptive streaming approaches based on preprocessing have some limitations. In this paper, we proposed a novel adaptive Cloud VR system with real-time processing. We design and implement a GPU acceleration scheme to perform efficient projection and coding, which makes the computing latency acceptable. The scheme is further extended to pipeline execution with simple orientation prediction to support higher frame rate. The real-time processing not only reduces the storage size, but also eliminates the drawbacks of pre-generating limited video versions. According to the experimental results, our scheme can provide a VR stream matching user viewport more precisely. Through optimized GPU algorithm, we shorten the processing time to 1/10 of the original. Compared to classic pyramid projection scheme, our system effectively reduces the average orientation deviation by 90.23%, thus provides more robust service.