[1]GAO Yan-yu,YIN Yi-xin.Application of the DempsterShafer theory to affective image annotation[J].CAAI Transactions on Intelligent Systems,2010,5(6):534-539.
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Application of the DempsterShafer theory to affective image annotation

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 5 Number of periods: 2010 6 Page number: 534-539 Column: 学术论文—人工智能基础 Public date: 2010-12-25
Title:
Application of the DempsterShafer theory to affective image annotation
Author(s):
GAO Yan-yu;  YIN Yi-xin
School of Information Engineering, University of Science & Technology Beijing, Beijing 100083, China
Keywords:
DempsterShafer theory;  affective image annotation;  affective factor;  hierarchical semantics
CLC:
TP391.4
DOI:
-
Abstract:
Affective image annotation involves labeling an image with adjectives, so that those labels reflect the user’s emotional understanding of the image. The lowlevel visual features and the image semantic content are two decisive factors in the user’s emotional understanding of an image, while image content recognition is highly uncertain and affective understanding is strongly subjective. In the following study, the DempsterShafer theory was applied to represent the visual image characteristics and to model the uncertainty reasoning from those decisive factors to affective understanding. In response to the semantic recognition error, the uncertainty range of image contents to each affective factor was enlarged and a prototype affective annotation system was built to automatically label natural scenic images. Experimental results show that the DempsterShafer theory is promising for ambiguous annotation, and enlarging the uncertainty range is helpful for improving annotation precision.
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