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Visual Tracking by Local Superpixel Matching with Markov Random Field Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Visual BFI: An Exploratory Study for Image-Based Personality Test

Authors : Jitao Sang, Huaiwen Zhang, Changsheng Xu

Published in: Advances in Multimedia Information Processing - PCM 2016

Publisher: Springer International Publishing

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Abstract

This paper positions and explores the topic of image-based personality test. Instead of responding to text-based questions, the subjects will be provided a set of “choose-your-favorite-image” visual questions. With the image options of each question belonging to the same concept, the subjects’ personality traits are estimated by observing their preferences of images under several unique concepts. The solution to design such an image-based personality test consists of concept-question identification and image-option selection. We have presented a preliminary framework to regularize these two steps in this exploratory study. A demo version of the designed image-based personality test is available at http://​www.​visualbfi.​org/​. Subjective as well as objective evaluations have demonstrated the feasibility of accurately estimation the personality of subjects in limited round of visual questions.

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Footnotes
1
For those concepts favored by more than 104 users, 104 random users are selected to construct the sample set for this concept. We fix the sample number as 104 to facilitate the performance comparison with solutions in the next section.
 
2
In practical implementation, we can select images from different clusters to design several versions of questionnaires.
 
3
Note that the subjects were never given their personality test results from text-based BFI-10 or BFI-44 to avoid the interaction effect of different tests.
 
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Metadata
Title
Visual BFI: An Exploratory Study for Image-Based Personality Test
Authors
Jitao Sang
Huaiwen Zhang
Changsheng Xu
Copyright Year
2016
Book
Advances in Multimedia Information Processing - PCM 2016

Print ISBN: 978-3-319-48889-9

Electronic ISBN: 978-3-319-48890-5

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-48890-5_10