Soylent grid: It's made of people!

Research output: Contribution to conference › Paper › Research › peer-review

Standard

Soylent grid : It's made of people! / Steinbach, Stephan; Rabaud, Vincent; Belongie, Serge.

2007. Paper presented at 2007 IEEE 11th International Conference on Computer Vision, ICCV, Rio de Janeiro, Brazil.

Research output: Contribution to conference › Paper › Research › peer-review

Harvard

Steinbach, S, Rabaud, V & Belongie, S 2007, 'Soylent grid: It's made of people!', Paper presented at 2007 IEEE 11th International Conference on Computer Vision, ICCV, Rio de Janeiro, Brazil, 14/10/2007 - 21/10/2007. https://doi.org/10.1109/ICCV.2007.4409122

APA

Steinbach, S., Rabaud, V., & Belongie, S. (2007). Soylent grid: It's made of people!. Paper presented at 2007 IEEE 11th International Conference on Computer Vision, ICCV, Rio de Janeiro, Brazil. https://doi.org/10.1109/ICCV.2007.4409122

Vancouver

Steinbach S, Rabaud V, Belongie S. Soylent grid: It's made of people!. 2007. Paper presented at 2007 IEEE 11th International Conference on Computer Vision, ICCV, Rio de Janeiro, Brazil. https://doi.org/10.1109/ICCV.2007.4409122

Author

Steinbach, Stephan ; Rabaud, Vincent ; Belongie, Serge. / Soylent grid : It's made of people!. Paper presented at 2007 IEEE 11th International Conference on Computer Vision, ICCV, Rio de Janeiro, Brazil.

Bibtex

@conference{5eb9e08b04074b579f75417d927e51c0,
title = "Soylent grid: It's made of people!",
abstract = "The ground truth labeling of an image dataset is a task that often requires a large amount of human time and labor. We present an infrastructure for distributed human labeling that can exploit the modularity of common vision problems involving segmentation and recognition. We present the different elements of this infrastructure in detail, in particular the different vision Human Computational Tasks (HCTs) and Machine Computable Tasks (MCTs). We also discuss the impact of such a system on internet security vs. the current state of the art. Finally, we present our prototype implementation of such a system, named SOYLENT GRID, on typical problems.",
author = "Stephan Steinbach and Vincent Rabaud and Serge Belongie",
year = "2007",
doi = "10.1109/ICCV.2007.4409122",
language = "English",
note = "2007 IEEE 11th International Conference on Computer Vision, ICCV ; Conference date: 14-10-2007 Through 21-10-2007",

}

RIS

TY - CONF

T1 - Soylent grid

T2 - 2007 IEEE 11th International Conference on Computer Vision, ICCV

AU - Steinbach, Stephan

AU - Rabaud, Vincent

AU - Belongie, Serge

PY - 2007

Y1 - 2007

N2 - The ground truth labeling of an image dataset is a task that often requires a large amount of human time and labor. We present an infrastructure for distributed human labeling that can exploit the modularity of common vision problems involving segmentation and recognition. We present the different elements of this infrastructure in detail, in particular the different vision Human Computational Tasks (HCTs) and Machine Computable Tasks (MCTs). We also discuss the impact of such a system on internet security vs. the current state of the art. Finally, we present our prototype implementation of such a system, named SOYLENT GRID, on typical problems.

AB - The ground truth labeling of an image dataset is a task that often requires a large amount of human time and labor. We present an infrastructure for distributed human labeling that can exploit the modularity of common vision problems involving segmentation and recognition. We present the different elements of this infrastructure in detail, in particular the different vision Human Computational Tasks (HCTs) and Machine Computable Tasks (MCTs). We also discuss the impact of such a system on internet security vs. the current state of the art. Finally, we present our prototype implementation of such a system, named SOYLENT GRID, on typical problems.

UR - http://www.scopus.com/inward/record.url?scp=51049098928&partnerID=8YFLogxK

U2 - 10.1109/ICCV.2007.4409122

DO - 10.1109/ICCV.2007.4409122

M3 - Paper

AN - SCOPUS:51049098928

Y2 - 14 October 2007 through 21 October 2007

ER -

ID: 302051846