Automatic Interpretation and Coding of Face Images Using Flexible Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection From Color Images Using a Fuzzy Pattern Matching Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Preprocessing of face images: detection of features and pose normalization
Computer Vision and Image Understanding
Looking at People: Sensing for Ubiquitous and Wearable Computing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Incremental Learning Algorithm for Face Recognition
ECCV '02 Proceedings of the International ECCV 2002 Workshop Copenhagen on Biometric Authentication
DESEO: An Active Vision System for Detection, Tracking and Recognition
ICVS '99 Proceedings of the First International Conference on Computer Vision Systems
GD: A Measure Based on Information Theory for Attribute Selection
IBERAMIA '98 Proceedings of the 6th Ibero-American Conference on AI: Progress in Artificial Intelligence
A Comparison of Face/Non-face Classifiers
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
A Mobile Robot That Recognizes People
TAI '95 Proceedings of the Seventh International Conference on Tools with Artificial Intelligence
Neural network-based face detection
Neural network-based face detection
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This paper describes an approach for detection of frontal faces in real time (20-35Hz) for further processing. This approach makes use of a combination of previous detection tracking and color for selecting interest areas. On those areas, later facial features such as eyes, nose and mouth are searched based on geometric tests, appearance verification, temporal and spatial coherence. The system makes use of very simple techniques applied in a cascade approach, combined and coordinated with temporal information for improving performance. This module is a component of a complete system designed for detection, tracking and identification of individuals [1].