Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Probabilistic Modeling of Local Appearance and Spatial Relationships for Object Recognition
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Finding faces in cluttered scenes using random labeled graph matching
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Support vector machines: training and applications
Support vector machines: training and applications
Learning and example selection for object and pattern detection
Learning and example selection for object and pattern detection
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Face recognition: component-based versus global approaches
Computer Vision and Image Understanding - Special issue on Face recognition
PEBL: Web Page Classification without Negative Examples
IEEE Transactions on Knowledge and Data Engineering
A Component-based Framework for Face Detection and Identification
International Journal of Computer Vision
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We describe a component based face detection system trained only on positive examples. On the first layer, SVM classifiers detect predetermined rectangular portions of faces in gray scale images. On the second level, histogram based classifiers judge the pattern using only the positions of maximization of the first level classifiers. Novel aspects of our approach are: a) using selected parts of the positive pattern as negative training for component classifiers, b) The use of pair wise correlation between facial component positions to bias classifier outputs and achieve superior component localization.