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
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;
Conference_Titel :
Applications of Computer Vision (WACV), 2012 IEEE Workshop on
Conference_Location :
Breckenridge, CO
Print_ISBN :
978-1-4673-0233-3
Electronic_ISBN :
1550-5790
DOI :
10.1109/WACV.2012.6163033