DocumentCode
3473140
Title
Tools for richer crowd source image annotations
Author
Little, Joshua ; Abrams, Austin ; Pless, Robert
Author_Institution
Washington Univ. in St. Louis, St. Louis, MO, USA
fYear
2012
fDate
9-11 Jan. 2012
Firstpage
369
Lastpage
374
Abstract
Crowd-sourcing tools such as Mechanical Turk are popular for annotation of large scale image data sets. Typically, these annotations consist of bounding boxes or coarse outlines of objects, in order to keep the interface as simple as possible and to respect browser constraints. However, as most browsers now contain functionality to quickly process images and render shapes to the browser through JavaScript, better annotations can feasibly be generated through the browser given an easy-to-use interface. In this paper, we develop a suite of annotation tools for high-fidelity object contouring and 3D pose working within the limitation that, to be accessible to most Mechanical Turk users, the tools must be available through browsers with no plug-ins or extra downloads. We show comparative results exploring the annotation accuracy relative to existing annotation tools.
Keywords
Java; image processing; shape recognition; 3D pose working; JavaScript; Mechanical Turk; bounding boxes; browser constraints; coarse outlines; crowd sourcing tools; image data sets; image shapes; render shapes; richer crowd source image annotations; Estimation; Humans; Image edge detection; Image segmentation; Mice; Shape; Three dimensional displays;
fLanguage
English
Publisher
ieee
Conference_Titel
Applications of Computer Vision (WACV), 2012 IEEE Workshop on
Conference_Location
Breckenridge, CO
ISSN
1550-5790
Print_ISBN
978-1-4673-0233-3
Electronic_ISBN
1550-5790
Type
conf
DOI
10.1109/WACV.2012.6163033
Filename
6163033
Link To Document