Paper Info
Title
Accelerating computer vision algorithms using OpenCL framework on the mobile GPU - A case study
Abstract
Recently, general-purpose computing on graphics processing units (GPGPU) has been enabled on mobile devices thanks to the emerging heterogeneous programming models such as OpenCL. The capability of GPGPU on mobile devices opens a new era for mobile computing and can enable many computationally demanding computer vision algorithms on mobile devices. As a case study, this paper proposes to accelerate an exemplar-based inpainting algorithm for object removal on a mobile GPU using OpenCL. We discuss the methodology of exploring the parallelism in the algorithm as well as several optimization techniques. Experimental results demonstrate that our optimization strategies for mobile GPUs have significantly reduced the processing time and make computationally intensive computer vision algorithms feasible for a mobile device. To the best of the authors' knowledge, this work is the first published implementation of general-purpose computing using OpenCL on mobile GPUs.
Year
DOI
Venue
2013
10.1109/ICASSP.2013.6638132
ICASSP
Keywords
Field
DocType
mobile devices,optimisation,opencl framework,general-purpose computing,heterogeneous programming,mobile soc,parallel architectures,graphics processing units,exemplar-based inpainting,optimization,computer vision,gpgpu,cpu-gpu algorithm partitioning,computer vision implementation,mobile computing,mobile gpu,acceleration,kernel,mobile communication
Graphics,Mobile computing,Kernel (linear algebra),Computer architecture,Mathematical optimization,Computer science,Parallel computing,Inpainting,Mobile device,Computer vision algorithms,General-purpose computing on graphics processing units,Mobile telephony
Conference
ISSN
Citations 
PageRank 
1520-6149
36
1.79
References 
Authors
12
4
Name
Order
Citations
PageRank
Guohui Wang1108860.78
Yingen Xiong243730.25
Jay Yun3443.17
Joseph R. Cavallaro41175115.35