BUBL: An effective region labeling tool using a hexagonal lattice

Publikation: Bidrag til tidsskrift › Konferenceartikel › Forskning › fagfællebedømt

Standard

BUBL : An effective region labeling tool using a hexagonal lattice. / Galleguillos, Carolina; Faymonville, Peter; Belongie, Serge.

I: 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009, 2009, s. 2072-2079.

Publikation: Bidrag til tidsskrift › Konferenceartikel › Forskning › fagfællebedømt

Harvard

Galleguillos, C, Faymonville, P & Belongie, S 2009, 'BUBL: An effective region labeling tool using a hexagonal lattice', 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009, s. 2072-2079. https://doi.org/10.1109/ICCVW.2009.5457536

APA

Galleguillos, C., Faymonville, P., & Belongie, S. (2009). BUBL: An effective region labeling tool using a hexagonal lattice. 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009, 2072-2079. https://doi.org/10.1109/ICCVW.2009.5457536

Vancouver

Galleguillos C, Faymonville P, Belongie S. BUBL: An effective region labeling tool using a hexagonal lattice. 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009. 2009;2072-2079. https://doi.org/10.1109/ICCVW.2009.5457536

Author

Galleguillos, Carolina ; Faymonville, Peter ; Belongie, Serge. / BUBL : An effective region labeling tool using a hexagonal lattice. I: 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009. 2009 ; s. 2072-2079.

Bibtex

@inproceedings{9195768c5b9848dca21a29be7516d22e,
title = "BUBL: An effective region labeling tool using a hexagonal lattice",
abstract = "We propose a data labeling tool that permits accurate labeling of images using less time and effort. Our tool, BUBL, uses a hexagonal grid with a variable size tiling for accurate labeling of object contours. The hexagonal lattice is superimposed by a bubble wrap interface in order to make the labeling task enjoyable. The resulting label mask is represented by a Gaussian kernel density estimator which provides accurate bounding contours, even for objects that include hollow regions. Furthermore, multiple annotations from different users are collected for every image, making it possible to {"}hint{"} a partial labeling so the user can finish labeling in less time. We show accuracy results by simulating the application of our labeling tool for the MSRC dataset and to a subset data set of Caltech-101.",
author = "Carolina Galleguillos and Peter Faymonville and Serge Belongie",
year = "2009",
doi = "10.1109/ICCVW.2009.5457536",
language = "English",
pages = "2072--2079",
journal = "2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009",
note = "2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009 ; Conference date: 27-09-2009 Through 04-10-2009",

}

RIS

TY - GEN

T1 - BUBL

T2 - 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

AU - Galleguillos, Carolina

AU - Faymonville, Peter

AU - Belongie, Serge

PY - 2009

Y1 - 2009

N2 - We propose a data labeling tool that permits accurate labeling of images using less time and effort. Our tool, BUBL, uses a hexagonal grid with a variable size tiling for accurate labeling of object contours. The hexagonal lattice is superimposed by a bubble wrap interface in order to make the labeling task enjoyable. The resulting label mask is represented by a Gaussian kernel density estimator which provides accurate bounding contours, even for objects that include hollow regions. Furthermore, multiple annotations from different users are collected for every image, making it possible to "hint" a partial labeling so the user can finish labeling in less time. We show accuracy results by simulating the application of our labeling tool for the MSRC dataset and to a subset data set of Caltech-101.

AB - We propose a data labeling tool that permits accurate labeling of images using less time and effort. Our tool, BUBL, uses a hexagonal grid with a variable size tiling for accurate labeling of object contours. The hexagonal lattice is superimposed by a bubble wrap interface in order to make the labeling task enjoyable. The resulting label mask is represented by a Gaussian kernel density estimator which provides accurate bounding contours, even for objects that include hollow regions. Furthermore, multiple annotations from different users are collected for every image, making it possible to "hint" a partial labeling so the user can finish labeling in less time. We show accuracy results by simulating the application of our labeling tool for the MSRC dataset and to a subset data set of Caltech-101.

UR - http://www.scopus.com/inward/record.url?scp=77953217348&partnerID=8YFLogxK

U2 - 10.1109/ICCVW.2009.5457536

DO - 10.1109/ICCVW.2009.5457536

M3 - Conference article

AN - SCOPUS:77953217348

SP - 2072

EP - 2079

JO - 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

JF - 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

Y2 - 27 September 2009 through 4 October 2009

ER -

ID: 302048797