Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/66223
Title: Smile detection in the wild with hierarchical visual feature
Authors: Li, J
Chen, J
Chi, Z 
Keywords: Gabor filters
Gabor-HOG
HOG
Smile detection
Issue Date: 2016
Publisher: IEEE Computer Society
Source: Proceedings - International Conference on Image Processing, ICIP, 2016, v. 2016-August, 7532435, p. 639-643 How to cite?
Abstract: Smile detection in the wild is an interesting and challenging problem. This paper presents an efficient approach with hierarchical visual feature to handle this problem. In our approach, Gabor filters with multi-scale, multi-orientation are first applied to extract facial textures namely Gabor faces from the input face image. After this, Histograms of Oriented Gradients (HOG) are employed to encode these extracted Gabor faces to capture and characterize the facial appearance characteristics. We further adopt a pooling strategy to transform the multiple HOG features into a global visual feature called Gabor-Hog. Finally, SVM is trained to perform the classification. The experiments conducted on the GENKI4K database show that the proposed visual feature is robust to distinguish a smile face from a no-smile face. Our method also achieves a promising performance compared with the other state-of-the-art methods.
Description: 23rd IEEE International Conference on Image Processing, ICIP 2016, Phoenix, US, 25-28 September 2016
URI: http://hdl.handle.net/10397/66223
ISBN: 9781467399616
ISSN: 1522-4880
DOI: 10.1109/ICIP.2016.7532435
Appears in Collections:Conference Paper

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