Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active shape models—their training and application
Computer Vision and Image Understanding
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Robust Face Detection Using the Hausdorff Distance
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Robust Real-Time Face Detection
International Journal of Computer Vision
Fast and Accurate Facial Pose Estimation by Aligning a 3D Appearance Model
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
3D Alignment of Face in a Single Image
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Real-time eye blink detection with GPU-based SIFT tracking
CRV '07 Proceedings of the Fourth Canadian Conference on Computer and Robot Vision
Automatic feature localisation with constrained local models
Pattern Recognition
Simultaneous eye tracking and blink detection with interactive particle filters
EURASIP Journal on Advances in Signal Processing
Real Time Feature Based 3-D Deformable Face Tracking
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Locating Facial Features and Pose Estimation Using a 3D Shape Model
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Using 3d models for real-time facial feature tracking, pose estimation, and expression monitoring
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
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We investigate several methods of integrating facial actions into a 3D head model for 2D image search. The model on which the investigation is based has a neutral expression with eyes open, and our modifications enable the model to change expression and close the eyes. We show that the novel approach of using separate identity and action models during search gives better results than a combined-model strategy. This enables monitoring of head and feature movements in difficult real-world video sequences, which show large pose variation, occlusion, and variable lighting within and between frames. This should enable the identification of critical situations such as tiredness and inattention and we demonstrate the potential of our system by linking model parameters to states such as eyes closed and mouth open. We also present evidence that restricting the model parameters to a subspace close to the identity of the subject improves results.