Combining holistic and object-based approaches for scene classification

Zenghai CHEN, Zheru CHI, Hong FU, Dagan FENG

Research output: Chapter in Book/Report/Conference proceedingChapters

2 Citations (Scopus)

Abstract

There are two main approaches for scene classification: holistic and object-based. Holistic approach is good at representing scenes with simple content. However, since it does not take into account the internal object relationship, holistic approach does not well characterize complex scenes with multiple objects. By contrast, object-based approach estimates the scene class by analyzing the object co-occurrence information, as a result of which it is advantageous in characterizing scenes with complex content. But object-based approach is not good at classifying simple scenes. In this paper, we combine holistic and object-based approaches for scene classification. The proposed combinatory approach is able to take advantages of the two approaches. Several state-of-the-art holistic and object-based approaches are compared. The experiments conducted on a widely-used scene dataset demonstrate the superiors performance of the combinatory approach. Copyright © 2012 IEEE.
Original languageEnglish
Title of host publicationISCID 2012: 2012 Fifth International Symposium on Computational Intelligence and Design
Place of PublicationLos Alamitos
PublisherIEEE Computer Society
Pages65-68
Volume1
ISBN (Electronic)9780769548111
ISBN (Print)9781467326469
DOIs
Publication statusPublished - 2012

Citation

Chen, Z., Chi, Z., Fu, H., & Feng, D. (2012). Combining holistic and object-based approaches for scene classification. In ISCID 2012: 2012 Fifth International Symposium on Computational Intelligence and Design (Vol. 1, pp 65-68). Los Alamitos: IEEE Computer Society.

Keywords

  • Scene classification
  • Holistic approach
  • Object-based approach
  • Spatial pyramid matching (SPM)
  • CENTRIST

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