Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using the Discrete Cosine Transform
International Journal of Computer Vision - Special issue: Research at McGill University
Probabilistic Methods for Finding People
International Journal of Computer Vision
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
Robust Face Tracking Using Color
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Robust Real-Time Face Detection
International Journal of Computer Vision
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The aim of our project is to design an algorithm for counting people in public transport vehicles such as buses by processing images from surveillance cameras' video streams. This article presents a method of detection and tracking of multiple faces in a video by using a model of first and second order local moments. The three essential steps of our system are skin color modeling, probabilistic shape modeling and bayesian detection and tracking. An iterative process is used to estimate the position and shape of multiple faces in images, and to track them in video streams.