Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
FloatBoost Learning and Statistical Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reliable and Fast Tracking of Faces under Varying Pose
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Robust Estimation of Background for Fixed Cameras
CIC '06 Proceedings of the 15th International Conference on Computing
CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships
Multi- and single view multiperson tracking for smart room environments
CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships
PittPatt face detection and tracking for the CLEAR 2006 evaluation
CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships
Feature-centric evaluation for efficient cascaded object detection
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Kalman tracking with target feedback on adaptive background learning
MLMI'06 Proceedings of the Third international conference on Machine Learning for Multimodal Interaction
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Visual tracking and recognition using appearance-adaptive models in particle filters
IEEE Transactions on Image Processing
The AIT 3D Audio / Visual Person Tracker for CLEAR 2007
Multimodal Technologies for Perception of Humans
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This paper describes the AIT system for 2D face tracking and the results obtained in the CLEAR 2007 evaluations. The system is based on the complementary operation of a set of face detectors and a deterministic tracker based on color. To minimize false positives, the system is applied on the body regions provided by a stochastic body tracker, and utilizes a detection validation scheme based on color and texture modeling of the faces.