Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Transformation Invariance in Pattern Recognition-Tangent Distance and Tangent Propagation
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Probabilistic visual learning for object detection
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
On the Use of SDF-Type Filters for Distortion Invariant Image Location
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Feature space trajectory methods for active object recognition
Feature space trajectory methods for active object recognition
IEEE Transactions on Image Processing
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Synthetic discriminant functions have been used to locate objects irrespective of distortions and to estimate the extent of the distortion. It was recognized from the beginning that accurate estimates are only possible provided the training set is constructed carefully. In this paper, we obtain conditions that will ensure the accuracy of the estimates. The conditions also suggest efficient ways of constructing the training sets and the results are extended to a wide class SDF-type filters. The theoretical results are illustrated with (idealized) examples and are also applied to the more realistic problem of accurate facial location.