Overview of approaches for accelerating scale invariant feature detection algorithm

Author

Zhang, Jing ; Sang, Hongshi ; Shen, Xubang

Author_Institution

Nat. Key Lab. of Sci. & Technol. on Multi-spectral Inf. Process., Huazhong Univ. of Sci. & Technol., Wuhan, China

fYear

2011

fDate

15-17 April 2011

Firstpage

585

Lastpage

589

Abstract

SIFT (Scale Invariant Feature Transform) is one of most popular approach for feature detection and matching. Many parallelized algorithms have been proposed to accelerate SIFT to apply into real-time systems. This paper divides the researches into three different categories, that is, optimizing parallel algorithms based on general purpose multi-core processors, designing customized multi-core processor dedicated for SIFT and implementing SIFT based FPGA (Field Programmable Gate Arrays). Overview of the three type researches and analysis of task-level parallelism are presented in this paper.

Keywords

feature extraction; field programmable gate arrays; image matching; multiprocessing systems; parallel algorithms; transforms; FPGA; feature matching; field programmable gate array; general purpose multicore processor; parallelized algorithm; real-time system; scale invariant feature detection algorithm; scale invariant feature transform; task-level parallelism; Feature extraction; Field programmable gate arrays; Multicore processing; Parallel algorithms; Pixel; FPGA; GPU; SIFT;

fLanguage

English

Publisher

ieee

Conference_Titel

Electric Information and Control Engineering (ICEICE), 2011 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-8036-4

Type

conf

DOI

10.1109/ICEICE.2011.5778312

Filename

5778312