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01-Applied Mathematics & Information Sciences
An International Journal
               
 
 
 
 
 
 
 
 
 
 
 
 

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Volumes > Volume 7 > No. 2L

 
   

Fast Implementation of Scale Invariant Feature Transform Based on CUDA

PP: 717-722
Author(s)
Meng Lu,
Abstract
Scale-invariant feature transform (SIFT) was an algorithm in computer vision to detect and describe local features in images. Due to its excellent performance, SIFT was widely used in many applications, but the implementation of SIFT was complicated and time-consuming. To solve this problem, this paper presented a novel acceleration algorithm for SIFT implementation based on Compute Unified Device Architecture (CUDA). In the algorithm, all the steps of SIFT were specifically distributed and implemented by CPU or GPU, accroding to the stepís characteristics or demandings, to make full use of computational resources. Experiments showed that compared with the traditional implementation of SIFT, this paperís acceleration algorithm can greatly increase computation speed and save implementation time. Furthermore, the acceleration ratio had linear relation with the number of SIFT keypoints.

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