Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparison of Face Detection Algorithms
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
A survey of skin-color modeling and detection methods
Pattern Recognition
Face recognition from a single image per person: A survey
Pattern Recognition
A Component-based Framework for Face Detection and Identification
International Journal of Computer Vision
2D and 3D face recognition: A survey
Pattern Recognition Letters
Fast Asymmetric Learning for Cascade Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition
Computer Vision and Image Understanding
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Human face detection plays a major role in face recognition systems and has gained much attention in recent years. Various methods were proposed to detect faces in different orientations. The aim of this paper is to introduce a comparative study of four detection methods regarding the detection rate. These methods are: SMQT Features and SNOW Classifier (SFSC) method, Efficient and Rank Deficient Face Detection (ERDFD) method, Gabor-Feature Extraction and Neural Network (GFENN) method and An efficient face candidates selector Features (EFCSF) method.The experimental results of the methods have been performed on the wild data set (FDDB) using MatLab 7.9. SFSC method achieved higher detection rate.