Object Recognition Robust Under Translations, Deformations, and Changes in Background
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
An analytic solution for the pose determination of human faces from a monocular image
Pattern Recognition Letters
Digital Image Processing
Tracking and Learning Graphs and Pose on Image Sequences of Faces
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Fusion of 2D Face Alignment and 3D Head Pose Estimation for Robust and Real-Time Performance
RATFG-RTS '99 Proceedings of the International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems
A Fuzzy-Theory-Based Face Detector
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
A hierarchical neural network for human face detection
Pattern Recognition
Robust detection of outliers for projection-based face recognition methods
Multimedia Tools and Applications
Vector quantization segmentation for head pose estimation
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
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This paper presents a novel method for automatic estimation of the poses/degrees of human faces. The proposed system consists of two main parts. The first part is the searching of potentials face regions that are gotten from the isosceles-triangle criteria based on the rules of "the combination of two eyes and one mouth". The second part of the proposed system is the performing the task of pose verification by utilitizing face weighting mask function, direction weighting mask function, and pose weighting mask function.The proposed face poses/degrees classification system can also determine the poses of multiple faces. Experimental results demonstrate that an approximately 99% success rate is achieved and the relative false estimation rate is very low.