Sensation-based photo cropping

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Sensation-based photo cropping

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International Multimedia Conference archive
Proceedings of the seventeen ACM international conference on Multimedia table of contents

Beijing, China

SESSION: Short papers session 2: content analysis and HCM table of contents

Pages 669-672

Year of Publication: 2009

ISBN:978-1-60558-608-3

Authors

Masashi Nishiyama	The University of Tokyo, Tokyo, Japan
Takahiro Okabe	The University of Tokyo, Tokyo, Japan
Yoichi Sato	The University of Tokyo, Tokyo, Japan
Imari Sato	National Institute of Informatics, Tokyo, Japan

Sponsor

SIGMULTIMEDIA: ACM Special Interest Group on Multimedia

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 13, Downloads (12 Months): 13, Citation Count: 0

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ABSTRACT

This paper proposes a novel method for automatically cropping a photo using a quality classifier that assesses whether the cropped region is agreeable to users. We statistically build this quality classifier using large photo collections available on websites where people manually insert quality scores to photos. We first trim the original image and then decide on the candidates for cropping. We find the cropped region with the highest quality score by applying the quality classifier to the candidates. Current automatic photo cropping techniques search for attention grabbing regions that consist of salient pixels from the original photo. They are not always pleasant to users because they do not take into account the quality of the cropped region. Our method with the quality classifier outperforms a state-of-the-art method that takes into consideration only the user's attention for automatic photo cropping.

REFERENCES

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