A scene image is nonmutually exclusive-a fuzzy qualitative scene understanding

Chern Hong Lim, Anhar Risnumawan, Chee Seng Chan

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number6704299
Pages (from-to)1541-1556
Number of pages16
JournalIEEE Transactions on Fuzzy Systems
Volume22
Issue number6
DOIs
Publication statusPublished - Dec 2014
Externally publishedYes

Keywords

  • Computer vision
  • fuzzy qualitative reasoning
  • multilabel classification
  • pattern recognition
  • scene understanding

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