Scalable geometric hashing on MasPar machines

Author

Khokhar, Ashfaq A. ; Prasanna, Viktor K. ; Kim, Hyoung J.

Author_Institution

Dept. of EE-Syst., Univ. of Southern California, Los Angeles, CA, USA

fYear

1993

fDate

15-17 Jun 1993

Firstpage

594

Lastpage

595

Abstract

Scalable data parallel algorithms for geometric hashing are presented. Implementations of the proposed algorithms are performed on MasPar MP-1/MP-2. New parallel algorithms are designed and mapped onto MP-1/MP-2. These techniques significantly improve upon the number of processors employed while achieving superior time performance. The authors´ implementations run on a P processor machine, such that 1⩽P⩽S, where S is the number of feature points in the scene. The results show that a probe of the recognition phase for a scene consisting of 1024 feature points takes less than 50 ms on a 1-K processor MP-1/MP-2

Keywords

file organisation; image recognition; parallel algorithms; parallel machines; MasPar MP-1/MP-2; MasPar machines; feature points; recognition phase; scalable data parallel algorithms; scalable geometric hashing; Algorithm design and analysis; Histograms; Layout; Machine vision; Object recognition; Parallel algorithms; Probes; Routing; Solid modeling; Spatial databases; Voting;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on

Conference_Location

New York, NY

ISSN

1063-6919

Print_ISBN

0-8186-3880-X

Type

conf

DOI

10.1109/CVPR.1993.341069

Filename

341069