A GPU-enabled mobile telemedicine training system for graphic rendering
Zhipeng Fu, Jun Wei Zhou, Wanpeng Xu · Proceedings of the 28th Annual International Conference on Mobile Computing And Networking · 2022
Aiming for overcoming the constraints in graphic rendering of mobile devices used in telemedicine training for 3D images, this paper presents a GPU-enabled mobile telemedicine training system for graphic rendering. Two improvements are made to seamlessly display interactive 3D images of human organs, bones and blood vessels with realtime rendering. Firstly, instead of multiple stages of instruction translation between OpenGL ES and OpenGL, a bespoke GPU driver is added in Virtual Android to invoke GPU resources directly. Secondly, a Video Process Unit (VPU) is added to the hardware layer replacing CPU to code rendered results in H.264 format, reducing CPU load significantly. Test results suggest that the system can deliver consistent performance even in mobile devices of weak capability and a single server can support up to 24 concurrent virtual Android operating systems, each of which connects to 5 clients. The framework proposed by this paper is not only suitable for telemedicine training, but also for other application areas such as Virtual Reality and Augmented Reality in mobile environment.