doi:10.1016/B978-0-12-810493-4.00008-0Lüthi, MarcelM. Lu¨thi, A. Forster, T. Gerig, and T. Vetter. Shape mod- eling using gaussian process morphable models. Statistical Shape and Deformation Analysis: Methods, Implementation and Applications, page 165, 2017....
In Section 4.3 the fitting process is applied to the task of face recognition. 4.1. Model construction The construction of the GM-3DMM is described in three parts. First we introduce a Gaussian mixture distribution and discuss how this concept relates to morphable models. Then we describe how ...
Project Page of Combining 3D Morphable Models: A Large scale Face-and-Head Model - [CVPR 2019] shape pattern matrix regression point gaussian mesh registration pca eigenvectors principal covariance deformation bfm combined nicp morphable corresponding eigenspace lyhm Updated Dec 16, 2019 MATLAB daniel...
2401.08140——ProvNeRF: Modeling per Point Provenance in NeRFs as a Stochastic Process 神经辐射场(NeRFs)在各种应用中变得流行。然而,它们在稀疏视图设置中面临挑战,缺乏来自体积渲染的足够约束。从稀疏和不受限制的相机中重建和理解3D场景是经典计算机视觉中长期存在的问题,有着各种各样的应用。尽管最近的工作已经...
(3DGS) as an explicit 3D representation. This method enables easier illumination control and improved editability. Central to our approach is the Editable Gaussian Head (EG-Head) model, which combines a 3D Morphable Model (3DMM) with texture maps, allowing precise expression control and flexible...
This combination facilitates photorealistic rendering while allowing for precise animation control via the underlying parametric model, e.g., through expression transfer from a driving sequence or by manually changing the morphable model parameters. We parameterize each splat by a local coordinate frame ...
In this paper, we propose a generalization of SSMs, called Gaussian Process Morphable Models (GPMMs). We model the shape variations with a Gaussian process, which we represent using the leading components of its Karhunen-Loeve expansion. To compute the expansion, we make use of an approximation...
Gaussian Process Morphable Models (GPMMs) unify a variety of non-rigid deformation models for surface and image registration. Deformation models, such as B-splines, radial basis functions, and PCA models are defined as a probability distribution using a Gaussian process. The method depends heavily ...
We propose a framework to synthetically generate co-registered and paired 3D volume data using Gaussian process morphable models constructed from a single matching pair of multi-modal 3D image volumes. We demonstrate the application of the framework for matching pairs of CT and MR 3D image volume ...
In this paper, we develop a statistical shape modelling process capable of estimating the volume and orientation of in-situ blocks using Guassian Process Morphable Modelling. Characteristic block shapes for a slope have been identified from samples collected in a catchment ditch and modelled to ...