Optimizing Visual Vocabularies Using Soft Assignment Entropies
Kuang, Yubin LU ; Åström, Karl LU
; Kopp, Lars
LU
; Oskarsson, Magnus
LU
and Byröd, Martin
LU
(2011)
10th Asian Conference on Computer Vision (ACCV 2010), 2010
6495.
p.255-268
- Abstract
- The state of the art for large database object retrieval in images is based on quantizing descriptors of interest points into visual words. High similarity between matching image representations (as bags of words) is based upon the assumption that matched points in the two images end up in similar words in hard assignment or in similar representations in soft assignment techniques. In this paper we study how ground truth correspondences can be used to generate better visual vocabularies. Matching of image patches can be done e.g. using deformable models or from estimating 3D geometry. For optimization of the vocabulary, we propose minimizing the entropies of soft assignment of points. We base our clustering on hierarchical k-splits. The... (More)
- The state of the art for large database object retrieval in images is based on quantizing descriptors of interest points into visual words. High similarity between matching image representations (as bags of words) is based upon the assumption that matched points in the two images end up in similar words in hard assignment or in similar representations in soft assignment techniques. In this paper we study how ground truth correspondences can be used to generate better visual vocabularies. Matching of image patches can be done e.g. using deformable models or from estimating 3D geometry. For optimization of the vocabulary, we propose minimizing the entropies of soft assignment of points. We base our clustering on hierarchical k-splits. The results from our entropy based clustering are compared with hierarchical k-means. The vocabularies have been tested on real data with decreased entropy and increased true positive rate, as well as better retrieval performance. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1689426
- author
- Kuang, Yubin
LU
; Åström, Karl
LU
; Kopp, Lars
LU
; Oskarsson, Magnus
LU
and Byröd, Martin
LU
- organization
- publishing date
- 2011
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Lecture Notes in Computer Science
- volume
- 6495
- pages
- 14 pages
- publisher
- Springer
- conference name
- 10th Asian Conference on Computer Vision (ACCV 2010), 2010
- conference location
- Queenstown, New Zealand
- conference dates
- 2010-11-08 - 2010-11-12
- external identifiers
-
- wos:000298617900021
- scopus:79952500541
- ISSN
- 0302-9743
- 1611-3349
- ISBN
- 978-3-642-19281-4 (print)
- 978-3-642-19282-1(online)
- DOI
- 10.1007/978-3-642-19282-1
- language
- English
- LU publication?
- yes
- id
- 288b4328-921f-48c1-ba08-ad9a62a791be (old id 1689426)
- date added to LUP
- 2016-04-01 10:08:38
- date last changed
- 2024-01-06 08:46:18
@inproceedings{288b4328-921f-48c1-ba08-ad9a62a791be,
abstract = {{The state of the art for large database object retrieval in images is based on quantizing descriptors of interest points into visual words. High similarity between matching image representations (as bags of words) is based upon the assumption that matched points in the two images end up in similar words in hard assignment or in similar representations in soft assignment techniques. In this paper we study how ground truth correspondences can be used to generate better visual vocabularies. Matching of image patches can be done e.g. using deformable models or from estimating 3D geometry. For optimization of the vocabulary, we propose minimizing the entropies of soft assignment of points. We base our clustering on hierarchical k-splits. The results from our entropy based clustering are compared with hierarchical k-means. The vocabularies have been tested on real data with decreased entropy and increased true positive rate, as well as better retrieval performance.}},
author = {{Kuang, Yubin and Åström, Karl and Kopp, Lars and Oskarsson, Magnus and Byröd, Martin}},
booktitle = {{Lecture Notes in Computer Science}},
isbn = {{978-3-642-19281-4 (print)}},
issn = {{0302-9743}},
language = {{eng}},
pages = {{255--268}},
publisher = {{Springer}},
title = {{Optimizing Visual Vocabularies Using Soft Assignment Entropies}},
url = {{https://lup.lub.lu.se/search/files/1599268/1689432.pdf}},
doi = {{10.1007/978-3-642-19282-1}},
volume = {{6495}},
year = {{2011}},
}