Recognition of Digits in Hydrographic Maps: Binary Versus Topographic Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analysis and Synthesis of Facial Image Sequences Using Physical and Anatomical Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generating 3D views of facial expressions from frontal face video based on topographic analysis
Proceedings of the 12th annual ACM international conference on Multimedia
EyeKeys: A Real-Time Vision Interface Based on Gaze Detection from a Low-Grade Video Camera
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 10 - Volume 10
Editorial: special issue: eye detection and tracking
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Real time eye tracking for human computer interfaces
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Generic vs. person specific active appearance models
Image and Vision Computing
A biometric database with rotating head videos and hand- drawn face sketches
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
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Dynamic modeling of facial appearances and sight directions are demanded for HCI and multimedia applications. Traditional approaches for face tracking and eye tracking from 2D videos do not involve explicit facial modeling. In this paper, we propose to use an explicit 3D model to model the dynamic facial appearance as well as the eye shape to estimate the viewing direction. We apply active appearance models for local region tracking, and use a scale-space topographic representation for frame model instantiation. The individualized 3D models across video sequences allow us to estimate the iris viewing orientation dynamlically. The proposed framework has been realized and tested in a person-independent fashion for AAM tracking and model instantiation using a single camera.