Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Large Scale Image Annotations on Amazon Mechanical Turk

Subhransu Maji

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2011-79
July 1, 2011

http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-79.pdf

We describe our experience with collecting roughly 250, 000 image annotations on Amazon Mechanical Turk (AMT). The annotations we collected range from location of keypoints and figure ground masks of various object categories, 3D pose estimates of head and torsos of people in images and attributes like gender, race, type of hair, etc. We describe the setup and strategies we adopted to automatically approve and reject the annotations, which becomes important for large scale annotations. These annotations were used to train algorithms for detection, segmentation, pose estimation, action recognition and attribute recognition of people in images.


BibTeX citation:

@techreport{Maji:EECS-2011-79,
    Author = {Maji, Subhransu},
    Title = {Large Scale Image Annotations on Amazon Mechanical Turk},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {2011},
    Month = {Jul},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-79.html},
    Number = {UCB/EECS-2011-79},
    Abstract = {We describe our experience with collecting roughly 250, 000 image annotations on Amazon Mechanical Turk (AMT). The annotations we collected range from location of keypoints and figure ground masks of various object categories, 3D pose estimates of head and torsos of people in images and attributes like gender, race, type of hair, etc. We describe the setup and strategies we adopted to automatically approve and reject the annotations, which becomes important for large scale annotations. These annotations were used to train algorithms for detection, segmentation, pose estimation, action recognition and attribute recognition of people in images.}
}

EndNote citation:

%0 Report
%A Maji, Subhransu
%T Large Scale Image Annotations on Amazon Mechanical Turk
%I EECS Department, University of California, Berkeley
%D 2011
%8 July 1
%@ UCB/EECS-2011-79
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-79.html
%F Maji:EECS-2011-79