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Multimedia Tools and Applications

, Volume 74, Issue 20, pp 8893–8905 | Cite as

Ontology-based inference system for adaptive object recognition

  • Sung-Kwan KangEmail author
  • Kyung-Yong Chung
  • Jung-Hyun Lee
Article

Abstract

This paper presents a statistical ontology approach for adaptive object recognition in a situation-variant environment. We propose a context model based on statistical ontology that is concentrated on object recognition. Due to the effects of illumination on a supreme obstinate designing context-sensitive recognition system, we focused on designing a context-variant system using statistical ontology. Ontology, a collection of concepts and their interrelationships, provides an abstract view of an application domain. Researchers produce ontologies in order to understand and explain underlying principles and environmental factors. In this paper, we propose an ontology-based inference system for adaptive object recognition. The proposed method utilizes context ontology, context modeling, context adaptation, and context categorization to design the ontology based on illumination criteria for surveillance. After selecting the proper ontology domain, a set of actions is selected that produces better performance in that domain. We also carried out extensive experiments on these concepts in the area of object recognition in a dynamic changing environment, achieving enormous success that will enable us to proceed with our basic concepts.

Keywords

Object recognition Context-awareness Context modeling Inference 

Notes

Acknowledgment

This work was supported by the Korea Foundation for the Advancement of Science & Creativity (KOFAC), and funded by the Korean Government (MOE).

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Sung-Kwan Kang
    • 1
    Email author
  • Kyung-Yong Chung
    • 2
  • Jung-Hyun Lee
    • 3
  1. 1.HCI Laboratory, Department of Computer and Information EngineeringInha UniversityIncheonSouth Korea
  2. 2.School of Computer Information EngineeringSangji UniversityWonju-siSouth Korea
  3. 3.Department of Computer and Information EngineeringInha UniversityIncheonSouth Korea

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