Stochastic Analysis of Scale-Space Smoothing
Åström, Karl LU
and Heyden, Anders
LU
(1996)
13th International Conference on Pattern Recognition, (ICPR 1996)
2.
p.305-309
- Abstract
- In the high-level operations of computer vision it is taken for granted that image features have been reliably detected. This paper addresses the problem of feature extraction by scale-space methods. This paper is based on two key ideas: to investigate the stochastic properties of scale-space representations, and to investigate the interplay between discrete and continuous images. These investigations are then used to predict the stochastic properties of sub-pixel feature detectors
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/787192
- author
- Åström, Karl
LU
and Heyden, Anders
LU
- organization
- publishing date
- 1996
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- computer vision, correlation methods, feature extraction, interpolation, smoothing methods, stochastic processes
- host publication
- 13th International Conference on Pattern Recognition
- volume
- 2
- pages
- 305 - 309
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 13th International Conference on Pattern Recognition, (ICPR 1996)
- conference location
- Vienna, Austria
- conference dates
- 1996-08-25 - 1996-08-29
- external identifiers
-
- scopus:84898833093
- ISBN
- 0 8186 7282 X
- DOI
- 10.1109/ICPR.1996.546838
- language
- English
- LU publication?
- yes
- id
- 4c302050-491d-4fa3-a267-4299b6bad9d5 (old id 787192)
- alternative location
- http://ieeexplore.ieee.org/iel3/3995/11503/00546838.pdf?tp=&arnumber=546838&isnumber=11503
- date added to LUP
- 2016-04-04 10:35:16
- date last changed
- 2023-09-06 06:40:18
@inproceedings{4c302050-491d-4fa3-a267-4299b6bad9d5,
abstract = {{In the high-level operations of computer vision it is taken for granted that image features have been reliably detected. This paper addresses the problem of feature extraction by scale-space methods. This paper is based on two key ideas: to investigate the stochastic properties of scale-space representations, and to investigate the interplay between discrete and continuous images. These investigations are then used to predict the stochastic properties of sub-pixel feature detectors}},
author = {{Åström, Karl and Heyden, Anders}},
booktitle = {{13th International Conference on Pattern Recognition}},
isbn = {{0 8186 7282 X}},
keywords = {{computer vision; correlation methods; feature extraction; interpolation; smoothing methods; stochastic processes}},
language = {{eng}},
pages = {{305--309}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Stochastic Analysis of Scale-Space Smoothing}},
url = {{http://dx.doi.org/10.1109/ICPR.1996.546838}},
doi = {{10.1109/ICPR.1996.546838}},
volume = {{2}},
year = {{1996}},
}