Saliency-enhanced image aesthetics class prediction


Wong, Lai-Kuan and Low, Kok-Lim (2009) Saliency-enhanced image aesthetics class prediction. In: 16th IEEE International Conference on Image Processing (ICIP), 2009. IEEE, pp. 997-1000. ISBN 978-1-4244-5653-6

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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.

Item Type: Book Section
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 13 Nov 2013 02:30
Last Modified: 13 Nov 2013 02:30


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