Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Multimodal Shape Tracking with Point Distribution Models
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Pedestrian Detection Using Wavelet Templates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A Mixed-State Condensation Tracker with Automatic Model-Switching
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Robust Real-Time Face Detection
International Journal of Computer Vision
Face detection and tracking in a video by propagating detection probabilities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Human Pose Detection Using Randomized Hierarchical Cascades of Rejectors
International Journal of Computer Vision
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This paper presents a new system for recognition, tracking and pose estimation of people in video sequences. It is based on the wavelet transform from the upper body part and uses Support Vector Machines (SVM) for classification. Recognition is carried out hierarchically by first recognizing people and then individual characters. The characteristic features that best discriminate one person from another are learned automatically. Tracking is solved via a particle filter that utilizes the SVM output and a first order kinematic model to obtain a robust scheme that successfully handles occlusion, different poses and camera zooms. For pose estimation a collection of SVM classifiers is evaluated to detect specific, learned poses.