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

Authors:
Daniel Keren
Affiliations:
Department of Computer Science, University of Haifa, Haifa 31905, Israel
Venue:
Pattern Recognition Letters
Year:
2003

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Abstract

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.