Recognizing image "style" and activities in video using local features and naive Bayes

Research output: Contribution to journalArticlepeer-review


The goal of this paper is to offer a framework for classification of images and video according to their "type", or "style" - a problem which is hard to define, but easy to illustrate; for example, identifying an artist by the style of his/her painting, or determining the activity in a video sequence. The paper offers a simple classification paradigm based on local properties of spatial or spatio-temporal blocks. The learning and classification are based on the naive Bayes classifier. A few experimental results are presented.

Original languageEnglish
Pages (from-to)2913-2922
Number of pages10
JournalPattern Recognition Letters
Issue number16
StatePublished - Dec 2003

Bibliographical note

Funding Information:
This research was supported by The Israel Science Foundation (grant no. 591/00-10.5).


  • Activity detection
  • Image style
  • Naive Bayes
  • Texture

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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