Model-based object pose in 25 lines of code
International Journal of Computer Vision - Special issue: image understanding research at the University of Maryland
Object Pose: The Link between Weak Perspective,Paraperspective, and Full Perspective
International Journal of Computer Vision
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active Appearance Models Revisited
International Journal of Computer Vision
Head Pose Estimation by Nonlinear Manifold Learning
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Multi-View AAM Fitting and Camera Calibration
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
The effect of texture representations on AAM performance
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Large head movement tracking using sift-based registration
Proceedings of the 15th international conference on Multimedia
Journal of Cognitive Neuroscience
Head Pose Estimation in Computer Vision: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Enhanced local texture feature sets for face recognition under difficult lighting conditions
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Head pose estimation using stereo vision for human-robot interaction
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
A robust head pose estimation system for uncalibrated monocular videos
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
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In this paper we focus on the task of fully automatic real-time face 3D pose estimation, both person independent and calibration free. We developed a complete system, which is capable of self initializing, estimates the pose robustly and detects failure of tracking. As a first contribution, we describe the initialization step, which does not rely on any user interaction. As a second contribution we detail a robust tracking methodology, capable of dealing with fast user motion and varying lighting conditions. This includes improvement on both the matching error metric and the search algorithms. We show how the choice of the texture representation can strongly influence the stability of the pose estimation. We finally evaluate the performance of the system on realistic videos. The results show that the proposed method is both adaptable to different users and robust to lighting changes.