Submitted to CVPR November 1996 Parametrized Structure from Motion for 3D Adaptive Feedback Tracking of Faces Tony S. Jebara and Alex Pentland Media Laboratory, Massachusetts Institute of Technology Cambridge, MA 02139 November 28th, 1996 Abstract A real-time system is described for automatically detecting, modeling and tracking faces in 3D. A closed loop approach is proposed which utilizes str...

3D Human face models have been widely used in applications such as facial animation, video compressiodcoding, augmented reality, head tracking, facial expression recognition, human action recognition, and face recognition. Modeling human faces provides a potential solution to identifying faces with variations in illumination, pose, and facial expression. We propose a method of modeling human fa...

The paper presents several novel 3D image analysis algorithms, applied towards the segmentation and modeling of faces and hands. These are subsequently used to build a face-based authentication system and a system for humancomputer interaction based on static and dynamic gestures. The system relies on an active stereo sensor that uses a structured light approach to obtain 3D information. In thi...

The paper presents a novel framework to 3D face recognition that exploits region covariance matrices (RCMs), Gaussian mixture models (GMMs) and support vector machine (SVM) classifiers. The proposed framework first combines several 3D face representations at the feature level using RCM descriptors and then derives low-dimensional feature vectors from the computed descriptors with the unscented ...

This paper presents a completely automated 3D facial feature tracking system using 2D+3D image sequences recorded by a real-time 3D sensor. It is based on local feature detectors constrained by a 3D shape model, using techniques that make it robust under pose and partial occlusion. Several experiments conducted under relatively non-controlled conditions demonstrate the accuracy and robustness o...

A real-time system is described for automatically detecting, modeling and tracking faces in 3D. A closed loop approach is proposed which utilizes structure from motion to generate a 3D model of a face and then feed back the estimated structure to constrain feature tracking in the next frame. The system initializes by using skin classi cation, symmetry operations, 3D warping and eigenfaces to nd...

Morphable face models have proven to be an effective tool for 3D face modeling and face recognition, but the extension to 3D face scans with expressions is still a challenge. The two main difficulties are (1) how to build a new morphable face model that deals with expressions, and (2) how to fit this morphable face model automatically to new 3D face scans with unknown expressions. This work pre...

Applications related to game technology, law-enforcement, security, medicine or biometrics are becoming increasingly important, which, combined with the proliferation of three-dimensional (3D) scanning hardware, have made that 3D face recognition is now becoming a promising and feasible alternative to 2D face methods. The main advantage of 3D data, when compared with traditional 2D approaches, ...

The performances of most existing face recognition systems suffer from facial expressions. Unfortunately, there is not yet a satisfactory solution. Therefore, the main focus of this thesis is on expression-invariant face recognition algorithms. In this thesis, we first propose a 2D face recognition algorithm by separately modeling geometry and texture information in a face image. The effect of ...