Distributed Real-Time Generative 3D Hand Tracking using Edge GPGPU Acceleration

This work demonstrates a real-time 3D hand tracking application that runs via computation offloading. The proposed framework enables the application to run on low-end mobile devices such as laptops and tablets, despite the fact that they lack the sufficient hardware to perform the required computations locally. The network connection takes the place of a GPGPU accelerator and sharing resources with a larger workstation becomes the acceleration mechanism. The unique properties of a generative optimizer are examined and constitute a challenging use-case, since the requirement for real-time performance makes it very latency-sensitive.