Saliency-enhanced image aesthetics class prediction

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 glob...

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Bibliographic Details
Published in2009 16th IEEE International Conference on Image Processing (ICIP) pp. 997 - 1000
Main Authors Lai-Kuan Wong, Kok-Lim Low
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2009
Subjects
Aesthetics
classification
Classification algorithms
Content based retrieval
Data mining
Feature extraction
Image color analysis
Image retrieval
Information analysis
Photography
saliency
Support vector machines
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Summary: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.
ISBN:9781424456536
1424456533
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2009.5413825