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A statistical software package for image data analysis in marketing

 
: Böttcher, Thomas; Baier, Daniel; Naundorf, Robert

:

Lausen, B. ; Gesellschaft für Klassifikation:
Data science, learning by latent structures, and knowledge discovery : Selected papers presented during the European Conference on Data Analysis (ECDA 2013), Luxembourg, 10-12 July 2013
Berlin: Springer, 2015 (Studies in classification, data analysis and knowledge organization)
ISBN: 978-3-662-44982-0 (Print)
ISBN: 978-3-662-44983-7 (Online)
ISBN: 3-662-44982-X
S.217-227
European Conference on Data Analysis (ECDA) <1, 2013, Luxembourg>
Englisch
Konferenzbeitrag
Fraunhofer FIT ()

Abstract
The strongly growing number of available images reveals a great opportunity for a new age in the field of statistical analysis. Today, several thousand digital images are taken and published every day but not used for marketing purposes. Common statistical tools like SPSS, SAS, R, MATLAB, or RapidMiner still provide none or insufficient image processing packages. In this paper we introduce IMADAC, a statistical software in expansion of Naundorf et al. (Computer science reports. Institute of Computer Science, Brandenburg University of Technology, Cottbus, 2012) and Zellhöfer et al. (Proceedings of the 2nd ACM international conference on multimedia retrieval, ICMR ’12, pp. 59–60, 2012). IMADAC, designed for experts as well as users without image processing background, combines statistical analysis on both, common statistical data (e.g., age or gender) and image processing methods. This paper demonstrates the usage of low level image features for statistical purposes (e.g., clustering or multi-dimensional scaling). To improve marketing analysis results, we further show how to combine image features with other statistical data and how it can be done in a graphical user interface (GUI).

: http://publica.fraunhofer.de/dokumente/N-408827.html