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Title: Implementing wide baseline matching algorithms on a graphics processing unit.

Wide baseline matching is the state of the art for object recognition and image registration problems in computer vision. Though effective, the computational expense of these algorithms limits their application to many real-world problems. The performance of wide baseline matching algorithms may be improved by using a graphical processing unit as a fast multithreaded co-processor. In this paper, we present an implementation of the difference of Gaussian feature extractor, based on the CUDA system of GPU programming developed by NVIDIA, and implemented on their hardware. For a 2000x2000 pixel image, the GPU-based method executes nearly thirteen times faster than a comparable CPU-based method, with no significant loss of accuracy.
Authors:
; ; ;
Publication Date:
OSTI Identifier:
921737
Report Number(s):
SAND2007-6301
TRN: US200806%%21
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Research Org:
Sandia National Laboratories
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ACCURACY; ALGORITHMS; COMPUTER GRAPHICS; IMPLEMENTATION; PERFORMANCE; PATTERN RECOGNITION; Gaussian processes.; Computer vision.; Visual texture recognition.; Pattern recognition.