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Real Time 3D Facial Movement Tracking Using a Monocular Camera.

Yanchao Dong¹, Yanming Wang², Jiguang Yue³

¹School of Electronics and Information Engineering, Tongji University, Caoan Road 4800, Shanghai 201804, China. dongyanchao@tongji.edu.cn.

Sensors (Basel, Switzerland)

|July 28, 2016

Summary

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This summary is machine-generated.

This study introduces a real-time 3D facial movement tracking system using a single camera. The robust framework accurately estimates 3D face pose and local facial animations like eyelid and mouth movements.

Area of Science:

Computer Vision
Biomedical Engineering
Human-Computer Interaction

Background:

Accurate 3D facial movement tracking is crucial for applications like virtual reality, animation, and medical diagnostics.
Existing methods often require multiple cameras or controlled environments, limiting their real-world applicability.

Purpose of the Study:

To develop a robust, real-time 3D facial movement tracking framework using a monocular camera.
To accurately estimate 3D face pose and detailed facial animations, including eyelid and mouth movements.

Main Methods:

Utilizes Discriminative Shape Regression for 2D facial feature point localization.
Fuses 2D image data with a 3D face model via Extended Kalman Filter for 3D movement estimation.
Employs an alternating optimization strategy for automatic adaptation to different individuals.

Keywords:

3D facial movement HCI eyelid facial animation facial feature points

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Main Results:

Demonstrates reliable 3D facial movement tracking across diverse poses and illumination conditions.
Achieves high accuracy, with tracking errors of 1 mm for eyelid and 2 mm for mouth movements at real face scale.
The framework provides dependable tracking data suitable for expression analysis and mental state inference.

Conclusions:

The proposed monocular framework offers a robust and accurate solution for real-time 3D facial movement tracking.
Its ability to adapt to individuals and perform under varying conditions makes it highly practical for various applications.
The system's precision supports advanced analyses of facial expressions and inferring mental states.