
Proceedings Paper
Assessing photographer competence using face statisticsFormat | Member Price | Non-Member Price |
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Paper Abstract
The rapid growth of photo sharing websites has resulted in some new problems around the management of a large (and
quickly increasing) number of photographers with different needs and usage characteristics. Despite significant advances
in the field of computer vision, little has been done to leverage these technologies for photographer understanding and
management, partly due to the high computational cost of extracting application-specific image features. Recently robust
multi-view face detection technologies have been widely adopted by many photo sharing sites. This affords a limited but
"standard" pre-computed set of face features to tackle these administrative problems in large scale settings. In this paper
we present a principled statistical model to alleviate one such administrative task - the automatic analysis of
photographer competency given only face detection results on a set of their photos. The model uses summary statistics to
estimate the probability a given individual belongs to a population of high competence photographers over against a
second population of lower competence photographers. Using this model, we have achieved high classification accuracy
(respectively 84.3% and 90.9%) on two large image datasets. We discuss an application of this approach to assist in
managing a photo-sharing website.
Paper Details
Date Published: 10 February 2010
PDF: 9 pages
Proc. SPIE 7540, Imaging and Printing in a Web 2.0 World; and Multimedia Content Access: Algorithms and Systems IV, 75400P (10 February 2010); doi: 10.1117/12.838351
Published in SPIE Proceedings Vol. 7540:
Imaging and Printing in a Web 2.0 World; and Multimedia Content Access: Algorithms and Systems IV
Theo Gevers; Qian Lin; Raimondo Schettini; Zhigang Fan; Cees Snoek, Editor(s)
PDF: 9 pages
Proc. SPIE 7540, Imaging and Printing in a Web 2.0 World; and Multimedia Content Access: Algorithms and Systems IV, 75400P (10 February 2010); doi: 10.1117/12.838351
Show Author Affiliations
Darryl Greig, Hewlett-Packard Labs. (United Kingdom)
Yuli Gao, Hewlett-Packard Labs. (United States)
Published in SPIE Proceedings Vol. 7540:
Imaging and Printing in a Web 2.0 World; and Multimedia Content Access: Algorithms and Systems IV
Theo Gevers; Qian Lin; Raimondo Schettini; Zhigang Fan; Cees Snoek, Editor(s)
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