Stochastic modeling western paintings for effective classification

  • Authors:

  • Jialie Shen

  • Affiliations:

  • School of Information Systems, Singapore Management University, 80 Stamford Road, Singapore 178902, Singapore

  • Venue:
  • Pattern Recognition
  • Year:
  • 2009

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Abstract

As one of the most important cultural heritages, classical western paintings have always played a special role in human live and been applied for many different purposes. While image classification is the subject of a plethora of related publications, relatively little attention has been paid to automatic categorization of western classical paintings which could be a key technique of modern digital library, museums and art galleries. This paper studies automatic classification on large western painting image collection. We propose a novel framework to support automatic classification on large western painting image collections. With this framework, multiple visual features can be integrated effectively to improve the accuracy of identification process significantly. We also evaluate our method and its competitors based on a large image collection. A careful study on the empirical results indicates the approach enjoys great superiority over the state-of-the-art approaches in different aspects.