Accelerated Optical Flow Function Algorithm Using Compute Unified Device Architecture
Copyright policy )Accelerated Optical Flow Function Algorithm Using Compute Unified Device Architecture
AbstractThis paper describes sum of absolute differences (SAD) algorithm to calculate optical flow function. This algorithm is used for optical flow estimation between two frames of colored photo image. The algorithm is combined with parallel processing, modern general purpose Compute Unified Device Architecture (CUDA) Graphic Processing Unit (GPU) to reduce significantly the time consumption of computation of using traditional Central Processing Unit (CPU). This algorithm is tested on real world colored photo image sequences. The performance in term of time consumption of algorithm using parallel processing (using GPU) is then compared to serial processing (using CPU).
optical flow, parallel processing, Compute Unified Device Architecture (CUDA), Graphic Processing Unit (GPU), Sum of Absolute Differences (SAD), Engineering(all)
optical flow, parallel processing, Compute Unified Device Architecture (CUDA), Graphic Processing Unit (GPU), Sum of Absolute Differences (SAD), Engineering(all)
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).1 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!