Book ChapterDOI
Elastically Adaptive Deformable Models
Dimitris N. Metaxas,Ioannis A. Kakadiaris +1 more
- pp 550-559
TLDR
A novel technique for the automatic adaptation of a deformable model's elastic parameters within a Kalman filter frame-work for shape estimation applications by augmenting the state equations of an extendedKalman filter to incorporate these additional variables and take into account the noise in the data.Abstract:
We present a novel technique for the automatic adaptation of a deformable model's elastic parameters within a Kalman filter frame-work for shape estimation applications. The novelty of the technique is that the model's elastic parameters are not constant, but time varying. The model for the elastic parameter variation depends on the local error of fit and the rate of change of the error of fit. By augmenting the state equations of an extended Kalman filter to incorporate these additional variables and take into account the noise in the data, we are able to significantly improve the quality of the shape estimation. Therefore, the model's elastic parameters are initialized always to the same value and they subsequently modified depending on the data and the noise distribution. In addition, we demonstrate how this technique can be parallelized in order to increase its efficiency. We present several experiments to demonstrate the effectiveness of our method.read more
Citations
More filters
Journal ArticleDOI
Three-Dimensional Face Recognition in the Presence of Facial Expressions: An Annotated Deformable Model Approach
Ioannis A. Kakadiaris,G. Passalis,George Toderici,Mohammed N. Murtuza,Yunliang Lu,Nikos Karampatziakis,Theoharis Theoharis +6 more
TL;DR: This paper presents the computational tools and a hardware prototype for 3D face recognition and presents the results on the largest known, and now publicly available, face recognition grand challenge 3D facial database consisting of several thousand scans.
Journal ArticleDOI
Bilinear Models for 3-D Face and Facial Expression Recognition
TL;DR: An elastically deformable model algorithm that establishes correspondence among a set of faces is proposed first and then bilinear models that decouple the identity and facial expression factors are constructed, enabling face recognition invariant to facial expressions and facialexpression recognition with unknown identity.
Journal ArticleDOI
3-D Face Detection, Landmark Localization, and Registration Using a Point Distribution Model
P. Nair,Andrea Cavallaro +1 more
TL;DR: An accurate and robust framework for detecting and segmenting faces, localizing landmarks, and achieving fine registration of face meshes based on the fitting of a facial model based on a 3-D Point Distribution Model that is fitted without relying on texture, pose, or orientation information is presented.
Proceedings ArticleDOI
Evaluation of 3D Face Recognition in the presence of facial expressions: an Annotated Deformable Model approach
TL;DR: This work uses wavelet analysis to extract a compact biometric signature of selected localized face areas using an annotated face model, allowing for rapid comparisons on either a global or a per area basis.
Journal ArticleDOI
Tracking Vertex Flow and Model Adaptation for Three-Dimensional Spatiotemporal Face Analysis
TL;DR: This paper presents an effective approach for establishing vertex correspondences using a tracking-model-based approach for vertex registration, coarse-to-fine model adaptation, and vertex motion trajectory (called vertex flow) estimation and applies a spatial-temporal face model descriptor for facial expression classification based on dynamic 3-D model sequences.
References
More filters
Journal ArticleDOI
Snakes : Active Contour Models
TL;DR: This work uses snakes for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest, and uses scale-space continuation to enlarge the capture region surrounding a feature.
Book
The finite element method
TL;DR: In this article, the methodes are numeriques and the fonction de forme reference record created on 2005-11-18, modified on 2016-08-08.
Book
Spline models for observational data
TL;DR: In this paper, a theory and practice for the estimation of functions from noisy data on functionals is developed, where convergence properties, data based smoothing parameter selection, confidence intervals, and numerical methods are established which are appropriate to a number of problems within this framework.
Book
Applied Optimal Estimation
TL;DR: This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the subject more from an engineering than a mathematical orientation, and the theory and practice of optimal estimation is presented.
Journal ArticleDOI
On active contour models and balloons
TL;DR: A model of deformation which solves some of the problems encountered with the original method of energy-minimizing curves and makes the curve behave like a balloon which is inflated by an additional force.