Ammar Qammaz
ABSTRACT
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.
- R. Montella, S. Kosta, D. Oro, J. Vera, C. Fernández, C. Palmieri, D. Di Luccio, G. Giunta, M. Lapegna, and G. Laccetti, "Accelerating linux and android applications on low-power devices through remote gpgpu offloading," Concurrency and Computation: Practice and Experience, vol. 29, no. 24, 2017.Google Scholar
- I. Oikonomidis, N. Kyriazis, and A. A. Argyros, "Efficient model-based 3d tracking of hand articulations using kinect," in British Machine Vision Conference (BMVC 2011), vol. 1, no. 2. Dundee, UK: BMVA, 2011, pp. 1--11.Google Scholar
- A. Qammaz, S. Kosta, N. Kyriazis, and A. Argyros, "On the Feasibility of Real-Time 3D Hand Tracking using Edge GPGPU Acceleration," ArXiv e-prints, Apr. 2018.Google Scholar
Recommendations
GPGPU: general-purpose computation on graphics hardware
SC '06: Proceedings of the 2006 ACM/IEEE conference on SupercomputingThe graphics processor (GPU) on today's commodity video cards has evolved into an extremely powerful and flexible processor. Modern graphics architectures provide tremendous memory bandwidth and computational horsepower, with dozens of fully ...
From GPGPU to Many-Core: Nvidia Fermi and Intel Many Integrated Core Architecture
Comparing the architectures and performance levels of an Nvidia Fermi accelerator with an Intel MIC Architecture coprocessor demonstrates the benefit of the coprocessor for bringing highly parallel applications into, or even beyond, GPGPU performance ...
Performance analysis of accelerated image registration using GPGPU
GPGPU-2: Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing UnitsThis paper presents a performance analysis of an accelerated 2-D rigid image registration implementation that employs the Compute Unified Device Architecture (CUDA) programming environment to take advantage of the parallel processing capabilities of ...
Comments