A Scene Image is Nonmutually Exclusive-A Fuzzy Qualitative Scene Understanding

Ambiguity or uncertainty is a pervasive element of many real-world decision-making processes. Variation in decisions is a norm in this situation when the same problem is posed to different subjects. Psychological and metaphysical research has proven that decision making by humans is subjective. It i...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems 2014-12, Vol.22 (6), p.1541-1556
Main Authors: Chern Hong Lim, Risnumawan, Anhar, Chee Seng Chan
Format: Article
Language:English
Subjects:
Categories
Computer vision
Decision making
Decisions
Fuzzy
Fuzzy logic
fuzzy qualitative reasoning
Fuzzy set theory
Fuzzy systems
Histograms
multilabel classification
pattern recognition
scene understanding
Testing
Training
Training data
Uncertainty
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Summary:Ambiguity or uncertainty is a pervasive element of many real-world decision-making processes. Variation in decisions is a norm in this situation when the same problem is posed to different subjects. Psychological and metaphysical research has proven that decision making by humans is subjective. It is influenced by many factors such as experience, age, background, etc. Scene understanding is one of the computer vision problems that fall into this category. Conventional methods relax this problem by assuming that scene images are mutually exclusive; therefore, they focus on developing different approaches to perform the binary classification tasks. In this paper, we show that scene images are nonmutually exclusive and propose the fuzzy qualitative rank classifier (FQRC) to tackle the aforementioned problems. The proposed FQRC provides a ranking interpretation instead of binary decision. Evaluations in terms of qualitative and quantitative measurements using large numbers and challenging public scene datasets have shown the effectiveness of our proposed method in modeling the nonmutually exclusive scene images.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2014.2298233