Please use this identifier to cite or link to this item: https://doi.org/10.1145/2467696.2467730
Title: Constructing an anonymous dataset from the personal digital photo libraries of Mac app store users
Authors: Gozali, J.P.
Kan, M.-Y. 
Sundaram, H.
Keywords: Crowd-sourcing
Data collection
Ground truth
Personal digital library
Photography
Issue Date: 2013
Source: Gozali, J.P.,Kan, M.-Y.,Sundaram, H. (2013). Constructing an anonymous dataset from the personal digital photo libraries of Mac app store users. Proceedings of the ACM/IEEE Joint Conference on Digital Libraries : 305-308. ScholarBank@NUS Repository. https://doi.org/10.1145/2467696.2467730
Abstract: Personal digital photo libraries embody a large amount of information useful for research into photo organization, photo layout, and development of novel photo browser features. Even when anonymity can be ensured, amassing a sizable dataset from these libraries is still difficult due to the visibility and cost that would be required from such a study. We explore using the Mac App Store to reach more users to collect data from such personal digital photo libraries. More specifically, we compare and discuss how it differs from common data collection methods, e.g. Amazon Mechanical Turk, in terms of time, cost, quantity, and design of the data collection application. We have collected a large, openly available photo feature dataset using this manner. We illustrate the types of data that can be collected. In 60 days, we collected data from 20,778 photo sets (473,772 photos). Our study with the Mac App Store suggests that popular application distribution channels is a viable means to acquire massive data collections for researchers. Copyright © 2013 by the Association for Computing Machinery, Inc. (ACM).
Source Title: Proceedings of the ACM/IEEE Joint Conference on Digital Libraries
URI: http://scholarbank.nus.edu.sg/handle/10635/78068
ISBN: 9781450320764
ISSN: 15525996
DOI: 10.1145/2467696.2467730
Appears in Collections:Staff Publications

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