Automatic extraction of face-features
Pattern Recognition Letters
Applied multivariate statistical analysis
Applied multivariate statistical analysis
The nature of statistical learning theory
The nature of statistical learning theory
Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Learning for View-Based Human Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fast and Accurate Face Detector Based on Neural Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Face Detection
International Journal of Computer Vision
Convolutional Face Finder: A Neural Architecture for Fast and Robust Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition/detection by probabilistic decision-based neural network
IEEE Transactions on Neural Networks
Human motion modeling using multivision
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
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We present an effective and real-time face detection method based on Principal Component Analysis (PCA) and Support Vector Machines (SVMs). We extract simple Haar-like features from training images that consist of face and non-face images, reinterpret the features with PCA, and select useful ones from the large number of extracted features. With the selected features, we construct a face detector using an SVM appropriate for binary classification. The face detector is not affected by the size of a training dataset in a significant way, so that it works well with a small quantity of training data. It also shows a sufficiently fast detection speed for it to be practical for real-time face detection.