DocumentCode
2605389
Title
Efficient Non-Maximum Suppression
Author
Neubeck, Alexander ; Van Gool, Luc
Author_Institution
Comput. Vision Lab., ETH Zurich
Volume
3
fYear
0
fDate
0-0 0
Firstpage
850
Lastpage
855
Abstract
In this work we scrutinize a low level computer vision task - non-maximum suppression (NMS) - which is a crucial preprocessing step in many computer vision applications. Especially in real time scenarios, efficient algorithms for such preprocessing algorithms, which operate on the full image resolution, are important. In the case of NMS, it seems that merely the straightforward implementation or slight improvements are known. We show that these are far from being optimal, and derive several algorithms ranging from easy-to-implement to highly-efficient
Keywords
computer vision; image resolution; computer vision; image resolution; nonmaximum suppression; Application software; Computer vision; Data mining; Filters; Gas insulated transmission lines; Image reconstruction; Image resolution; Image texture analysis; Object recognition; Pixel;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location
Hong Kong
ISSN
1051-4651
Print_ISBN
0-7695-2521-0
Type
conf
DOI
10.1109/ICPR.2006.479
Filename
1699659
Link To Document