Multimedia Mining on Manycore Architectures: The Case for GPUs
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
A Comparison Study on Implementing Optical Flow and Digital Communications on FPGAs and GPUs
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Variational optic flow on the Sony PlayStation 3
Journal of Real-Time Image Processing
Real-time medical video processing, enabled by hardware accelerated correlations
Journal of Real-Time Image Processing
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In this study, the implementation of an image processing technique on Compute Unified Device Architecture (CUDA) is discussed. CUDA is a new hardware and software architecture developed by NVIDIA Corporation for the generalpurpose computation on graphics processing units. CUDA features an on-chip shared memory with very fast general read and write access, which enables threads in a block to share their data effectively. CUDA also provides a userfriendly development environment through an extension to the C programming language. This study focused on CUDA implementation of a representative optical flow computation proposed by Horn and Schunck in 1981. Their method produces the dense displacement field and has a straightforward processing procedure. A CUDA implementation of Horn and Schunck's method is proposed and investigated based on simulation results.