DocumentCode :
3019415
Title :
The effective resolution of correlation filters applied to natural scenes
Author :
Vidal-Naquet, Michel ; Tanifuji, Manabu
Author_Institution :
Brain Sci. Inst., Saitama
fYear :
2007
fDate :
17-22 June 2007
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, we measure the responses of image patches, used as filters, on different image ensembles and examine how the responses are affected by reducing the resolution of the image ensembles. By comparing the set of responses obtained at high and reduced resolutions, we find that for the ensembles of natural and object images (cars), there is a limit resolution of about 15times15 and 10times10 pixels, respectively, beyond which the filter responses are significantly affected by resolution reduction. We support the result by a simple theoretical analysis based on image ensemble statistics. There are two consequences to this result. First, it provides a natural working resolution, determined solely from the image ensemble statistics, to which higher resolution templates can be reduced without losing a significant amount of information. This can be used, in particular, to reduce the search space for useful visual features in many applications. Secondly, in contrast to many studies, it suggests that features that are more complex than Gabor patches can be effectively used as first layer filters and combined in order to represent more complex shapes and appearances.
Keywords :
Gabor filters; image resolution; natural scenes; statistical analysis; Gabor patches; correlation filters; first layer filters; image ensemble statistics; image patch responses; image resolution; natural image ensembles; natural scenes; object image ensembles; resolution reduction; visual features; Convolution; Gabor filters; Image analysis; Image resolution; Layout; Pixel; Shape; Statistical analysis; Statistics; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Conference_Location :
Minneapolis, MN
ISSN :
1063-6919
Print_ISBN :
1-4244-1179-3
Electronic_ISBN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2007.383368
Filename :
4270366
Link To Document :
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