Marc Droske

Weta Digital Ltd. | WETA · Rendering

We present manifold next event estimation (MNEE), a specialised technique for Monte Carlo light transport simulation to render refractive caustics by connecting surfaces to light sources (next event estimation) across transmissive interfaces. We employ correlated sampling by means of a perturbation strategy to explore all half vectors in the case o...

A level set formulation of Willmore flow is derived using the gradient flow perspective. Starting from single embedded surfaces and the corresponding gradient flow, the metric is generalized to sets of level set surfaces using the identification of normal velocities and variations of the level set function in time via the level set equation. This a...

We present a spectral rendering technique that offers a compelling set of advantages over existing approaches. The key idea is to propagate energy along paths for a small, constant number of changing wavelengths. The first of these, the hero wavelength, is randomly sampled for each path, and all directional sampling is solely based on it. The addit...

Multimodal image registration significantly benefits from previous denoising and structure segmentation and vice versa. In particular combined information of different image modalities makes segmentation significantly more robust. Indeed, fundamental tasks in image processing are highly interdependent. A variational approach is presented, which com...

Flow and transport phenomena occurring within serpentine microchannels are analyzed for both two- and three-dimensional curvilinear configurations A variational method for nonrigid registration of multimodal image data is presented. A suitable deformation will be determined via the minimization of a morphological, i.e., contrast invariant, matchin...

Monte Carlo methods have been widely adopted in physics-based rendering. A key property of a Monte Carlo estimator is its variance, which dictates the convergence rate of the estimator. In this paper, we devise a mathematical formulation for derivatives of rendering variance with respect to not only scene parameters (e.g., surface roughness) but al...

We present a Monte Carlo path tracing technique to sample extended next event estimation contributions in participating media: we consider one additional scattering vertex on the way to the next event, accounting for focused blur, resulting in visually interesting image features. Our technique is tailored to thin homogeneous media with strongly for...

Particles are widely used in movie production rendering for various different effects. Blobbies (aka metaballs) are a very useful primitive to bridge the intermediate regime between the bulk of a fluid and fast-moving spray particles as well as providing geometric variation to droplets. The use of anisotropy allows one to represent thin line struct...

We present Optimised Path Space Regularisation (OPSR), a novel regularisation technique for forward path tracing algorithms. Our regularisation controls the amount of roughness added to materials depending on the type of sampled paths and trades a small error in the estimator for a drastic reduction of variance in difficult paths, including indirec...

In the past few years the movie industry has switched over from stochastic rasterisation approaches to using physically based light transport simulation: path tracing in production has become ubiquitous across studios. The new approach came with undisputed advantages such as consistent lighting, progressive previews, and fresh code bases. But also...

The Manuka rendering architecture has been designed in the spirit of the classic reyes rendering architecture: to enable the creation of visually rich computer generated imagery for visual effects in movie production. Following in the footsteps of reyes over the past 30 years, this means supporting extremely complex geometry, texturing, and shading...

A system, method, and computer program product are provided for deterministically simulating light transport. In use, all pairs of non-negative integers are enumerated (e.g. in a predetermined order). Additionally, for each of the enumerated pairs of non-negative integers, an associated pair of a query point and a photon is identified by: identifyi...

A system, method, and computer program product are provided for hierarchical photon mapping. In use, photons and query locations are generated. Additionally, a bounding volume of the query locations is determined. Further, a set of the photons inside of the bounding volume is determined. It is then determined whether the set of photons and query lo...

The simulation of light transport often involves specular and transmis-sive surfaces, which are modeled by functions that are not square integrable. How-ever, in many practical cases unbiased Monte Carlo methods are not able to handle such functions efficiently and consistent Monte Carlo methods are applied. Based on quasi-Monte Carlo integration,...

We introduce two fourth-order regularization methods that remove geometric noise without destroying significant geometric features. These methods leverage ideas from image denoising and simplification of high contrast images in which piecewise ane functions are preserved up to infinitesimally small transition zones. We combine the regularization te...

Traditionally, different image processing tasks are mainly considered on their own. The main aim of this paper is a combination of registration, i.e., the spatial alignment of images and egmentation, i.e., the recognition of edges and object contours in images. A proper registration depends on a good initial segmentation and vice versa. In this pap...

Many problems in imaging are actually inverse problems. One reason for this is that conditions and parameters of the physical processes underlying the actual image acquisition are usually not known. Examples for this are the inhomogeneities of the magnetic field in magnetic resonance imaging (MRI) leading to nonlinear deformations of the anatomic s...

This paper presents a new algorithm based on the Mumford-Shah model for simultaneously detecting the edge features of two images and jointly estimating a consistent set of transformations to match them. Compared to the current asymmetric methods in the literature, this fully symmetric method allows one to determine one-to-one correspondences betwee...

The estimation of optical flow fields from image sequences is incorporated in a Mumford–Shah approach for image denoising and edge detection. Possibly noisy image sequences are considered as input and a piecewise smooth image intensity, a piecewise smooth motion field, and a joint discontinuity set are obtained as minimizers of the functional. The...

The estimation of optical flow fields from image sequences is incor- porated in a Mumford-Shah approach for image denoising and edge detection. Possibly noisy image sequences are considered as input and a piecewise smooth image intensity, a piecewise smooth motion field, and a joint discontinuity set are obtained as minimizers of the functional. Th...

The estimation of optical flow fields from image sequences is incorporated in a Mumford-Shah approach for image denoising and edge detection. Possibly noisy image sequences are considered as input and a piecewise smooth image intensity, a piecewise smooth motion field, and a joint discontinuity set are obtained as minimizers of the functional. The...

RESUMEN RESUMEN A new method for nonrigid registration of multimodal images is presented. Due to the large interdependence of segmentation and registration, the approach is based on simultaneous segmentation and edge alignment . The two processes are directly coupled and thus benefit from using complementary information of the entire underlying d...

In this paper we propose a new symmetrical framework that solves image denoising, edge detection and non{rigid image registration simultaneously. This framework is based on the Ambrosio{Tortorelli ap- proximation of the Mumford{Shah model. The optimization of a global functional leads to decomposing the image into a piecewise{smooth rep- resentativ...

,Institut f篓ur Mathematik, Gerhard-Mercator Universit篓at Duisburg, Lotharstra?e 63/65, 47048 Duisburg, Germany {clarenz|droske|rumpf}@math. uni-duisburg. de.,Lehrstuhl f篓ur Mathematische Optimierung, Mathematisches Institut, Heinrich-Heine Universit篓at D篓usseldorf, Universit篓atsstra?e 1, D-40225 D篓usseldorf, Germany. henn@am. uni-duesseldorf. de,Le...

Establishing a correspondence between two surfaces is a basic ingredient in many geometry processing applications. Existing approaches, which attempt to match two meshes directly in 3D, can be cumbersome to implement and it is often hard to produce accurate results in a reasonable amount of time. In this paper, we present a new variational method f...

Meaningful segmentation of intracranial lesions can be of assistance for planning open navigated microneurosurgical procedures, as well as for radiotherapy. Meaningful segmentation, however, may be hampered by lack of computational power. The respective segmentation method should be based on state-of-the-art mathematical tools, and it should be sui...

Most finite element, or finite volume software is built around a fixed mesh data structure. Therefore, each software package can only be used efficiently for a relatively narrow class of applications. For example, implementations supporting unstructured meshes allow the approximation of complex geometries but are in general much slower and require...

Most finite element, or finite volume software is built around a fixed mesh data structure. Therefore, each software package can only be used efficiently for a relatively narrow class of applications. For example, implementations supporting unstructured meshes allow the approximation of complex geometries but are in general much slower and require...

This thesis treats different methods and theoretical aspects of the calculus of variations and their applications in image processing, especially those in which gradient flows for the minimization of the variational problems are used. The focus lies on geometrical methods for image registration, as well as numerical methods for computing the soluti...

The presented image registration method uses a regularized gradient flow to correlate the intensities in two images. Thereby, an energy functional is successively minimized by descending along its regularized gradient. The gradient flow formulation makes use of a robust multi-scale regularization, an efficient multi-grid solver and an effective tim...

A fast multiscale and multigrid method for the matching of images in 2D and 3D is presented. Especially in medical imaging this problem - denoted as the registration problem - is of fundamental importance in the handling of images from multiple image modalities or of image time series. The paper restricts to the simplest matching energy to be minim...

We present a novel variational method to nonrigid registration of multimodal data. A suitable deformation will be determined via the minimization of a morphological, i.e., contrast invariant, matching functional along with an appropriate regularization energy. Here we want to give special focus on the practical issues involving scale-space methods,...

The analysis of image time series requires a correlation of the information between two images. The gradient flow registration is a method for correlating this information by successively minimizing an appropriate energy along its gradient. A graphics hardware implementation of this approach to image registration is presented. The gradient flow for...

INTRODUCTION Given two images f , f R, where# and d = 2, 3, we would like to determine a deformation # which maps# onto# and maps grey values in the first image f 1 via a deformation # to grey values at the deformed position in the second image f 2 such that f 1 f 2 . We consider # as a perturbation of the identity 1I which means 1I + u = #. To opt...

A variational method to non rigid registration of multimodal image data is presented. A suitable deformation will be determined via the minimization of a morphological, i.e., contrast invariant, matching functional along with an appropriate regularization energy.

The analysis of image time series requires a correlation of the information between two images. The gradient flow registration is a method for correlating this information by successively minimizing an appropriate energy along its gradient A graphics hardware implementation of this approach to image registration is presented. The gradient flow form...

A variational method to non rigid registration of multi-modal image data is presented. A suitable deformation will be determined via the minimization of a morphological, i.e., contrast invariant, matching functional along with an appropriate regularization energy. The aim is to correlate the morphologies of a template and a reference image under th...

An e#cient adaptive multigrid level set method for front propagation purposes in three dimensional medical image processing and segmentation is presented. It is able to deal with non sharp segment boundaries. A flexible, interactive modulation of the front speed depending on various boundary and regularization criteria ensure this goal. E#ciency is...

An efficient adaptive multigrid level set method for front propagation purposes in three dimensional medical image segmentation is presented. It is able to deal with non sharp segment boundaries. A flexible, interactive modulation of the front speed depending on various boundary and regularization criteria ensure this goal. Efficiency is due to a g...

A two-handed 3D styling system for free-form surfaces in a table-like Virtual Environment, the Responsive Workbench (RWB)TM, is described. Intuitive curve and surface deformation tools based on variational modeling and interaction techniques adapted to 3D VR modeling applications are proposed. The user draws curves (cubic B-splines) directly in the...

Segmentation is an essential ingredient in a wide range of image processing tasks and a building block of many visualization environ- ments. Many known segmentation techniques suer from being computationally exhaustive and thus decreasing interactivity, especially when considering volume data sets. Multilevel methods have proved to be a powerful ma...

Joint denoising and anisotropy estimation: original image, anisotropic cartoon and estimated orientation. Abstract We propose a new approach for the extraction of cartoons from 2D aerial images. Particularly in city areas, these images are mainly character-ized by rectangular geometries of locally vary-ing orientation. The presented method is based...