Local gradient increasing pattern for facial expression recognition
This paper presents a new facial descriptor for facial expression recognition based on the Local Gradient Increasing Pattern (LGIP). A LGIP feature is to encode the intensity increasing trends in eight directions at each pixel using eight binary bits, and then a decimal code is assigned to describe...
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| Main Authors: | , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/101782 http://hdl.handle.net/10220/12971 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | This paper presents a new facial descriptor for facial expression recognition based on the Local Gradient Increasing Pattern (LGIP). A LGIP feature is to encode the intensity increasing trends in eight directions at each pixel using eight binary bits, and then a decimal code is assigned to describe the over-all increasing trend. The facial descriptor is generated from grid-based regional LGIP histograms. Subsequently, Support Vector Machine classifier is used for multi-class expression classification. Extensive experiments using Cohn-Kanade and Jaffe databases show that the LGIP based descriptor outperforms other related algorithms. |
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