Spatially Enhanced Local Binary Patterns for Face Detection and Recognition in Mobile Device Applications
Face detection and recognition has been very popular topics. Recently, its applications for mobile devices have gained tremendous attention due to the rapid expansion of the market. Although numerous techniques exist for face detection and recognition, only a few solve realistic challenges under th...
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| Language: | en_ca |
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2013
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| Online Access: | http://hdl.handle.net/1807/43339 |
| Summary: | Face detection and recognition has been very popular topics. Recently, its applications for mobile devices have gained tremendous attention due to the rapid expansion of the market.
Although numerous techniques exist for face detection and recognition, only a few solve realistic challenges under the mobile device application environment. In this thesis, we propose an automatic face authentication system including both face detection and recognition components for mobile device applications by using spatially enhanced Local Binary Patterns (LBP) feature extraction.
The first contribution is to propose a fast and accurate face detector by using LBP features and its spatially enhanced variant. The simplicity of LBP ensures low computational complexity and spatially enhanced LBP achieves high accuracy.
The second contribution is to propose color based spatially enhanced LBP features for face recognition. The proposed features achieve high accuracy by extracting complementary information from color channels and spatial correlations between LBP features. |
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