Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Face Detection Using the Hausdorff Distance
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Facial Asymmetry Quantification for Expression Invariant Human Identification
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Journal of Cognitive Neuroscience
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This paper presents a new approach to human face orientation detection. We start the work with establishing a frequency domain model to analyze the orientation distribution of the oriented patterns in an image, according to the power spectrum of its bi-valued image. This model is derived from the perspective of the rendering rules in classical computer graphics. On the assumptions of the crossed distribution rule and symmetry rule of facial textures, we use the model above to define a series of measurements, called power spectrum based measurements, to quickly determine the orientation of a human face. The experimental results on MIT, ORL and BioID face databases demonstrate our approach is effective and promising.