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Saliency-enhanced image aesthetics class prediction

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2 Author(s)
Lai-Kuan Wong ; Nat. Univ. of Singapore, Singapore, Singapore ; Kok-Lim Low

We present a saliency-enhanced method for the classification of professional photos and snapshots. First, we extract the salient regions from an image by utilizing a visual saliency model. We assume that the salient regions contain the photo subject. Then, in addition to a set of discriminative global image features, we extract a set of salient features that characterize the subject and depict the subject-background relationship. Our high-level perceptual approach produces a promising 5-fold cross-validation (5-CV) classification accuracy of 78.8%, significantly higher than existing approaches that concentrate mainly on global features.

Published in:

Image Processing (ICIP), 2009 16th IEEE International Conference on

Date of Conference:

7-10 Nov. 2009