From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Active Appearance Models
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Pose Invariant Face Recognition
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
SFS Based View Synthesis for Robust Face Recognition
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Robust Real-Time Face Detection
International Journal of Computer Vision
Active Appearance Models Revisited
International Journal of Computer Vision
Block Selection in the Local Appearance-based Face Recognition Scheme
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Pose Normalization for Local Appearance-Based Face Recognition
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Open-Set Face Recognition-Based Visitor Interface System
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
Generic vs. person specific active appearance models
Image and Vision Computing
General pose face recognition using frontal face model
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Face recognition for web-scale datasets
Computer Vision and Image Understanding
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In this paper, a robust real-world video based open-set face recognition system is presented. This system is designed for general small-scale convenience applications, which can be used for providing customized services. In the developed prototype, the system identifies a person in question and conveys customized information according to the identity. Since it does not require any cooperation of the users, the robustness of the system can be easily affected by the confounding factors. To overcome the pose problem, we generated frontal view faces with a tracked 2D face model. We also employed a distance metric to assess the quality of face model tracking. A local appearance-based face representation was used to make the system robust against local appearance variations. We evaluated the system's performance on a face database which was collected in front of an office. The experimental results on this database show that the developed system is able to operate robustly under real-world conditions.