Jannik Boll Nielsen

On optimal, minimal BRDF sampling for reflectance acquisition

The bidirectional reflectance distribution function (BRDF) is critical for rendering, and accurate material representation requires data-driven reflectance models. However, isotropic BRDFs are 3D functions, and measuring the reflectance of a flat sample can require a million incident and outgoing direction pairs, making the use of measured BRDFs impractical. In this paper, we address the problem of reconstructing a measured BRDF from a limited number of samples. We present a novel mapping of the BRDF space, allowing for extraction of descriptive principal components from measured databases, such as the MERL BRDF database. We optimize for the best sampling directions, and explicitly provide the optimal set of incident and outgoing directions in the Rusinkiewicz parameterization for n = {1, 2, 5, 10, 20} samples. Based on the principal components, we describe a method for accurately reconstructing BRDF data from these limited sets of samples. We validate our results on the MERL BRDF database, including favorable comparisons to previous sets of industry-standard sampling directions, as well as with BRDF measurements of new flat material samples acquired with a gantry system. As an extension, we also demonstrate how this method can be used to find optimal sampling directions when imaging a sphere of a homogeneous material; in this case, only two images are often adequate for high accuracy.

Minimal BRDF sampling for two-shot near-field reflectance acquisition

We develop a method to acquire the BRDF of a homogeneous flat sample from only two images, taken by a near-field perspective camera, and lit by a directional light source. Our method uses the MERL BRDF database to determine the optimal set of lightview pairs for data-driven reflectance acquisition. We develop a mathematical framework to estimate error from a given set of measurements, including the use of multiple measurements in an image simultaneously, as needed for acquisition from near-field setups. The novel error metric is essential in the near-field case, where we show that using the condition-number alone performs poorly. We demonstrate practical near-field acquisition of BRDFs from only one or two input images. Our framework generalizes to configurations like a fixed camera setup, where we also develop a simple extension to spatially-varying BRDFs by clustering the materials.

Addressing grazing angle reflections in Phong models

The Phong illumination model is used extensively as it is simple with few parameters. It is however often challenging to fit such a single lobed model to the bidirectional reflectance distribution function (BRDF) of a real material, especially at grazing angles (Fig. 1). The fitting issues are in shortcomings of the model, in choosing error function, and in initial guess sensitivity [Matusik et al. 2003]. In previous work [Ngan et al. 2005], these issues were bypassed by using two specular lobes, by ignoring very grazing angles (>80°), and, in cases of unsatisfactory fitting quality, by manually restarting the fitting procedure with a different initial guess. In this work, we also fit Phong models to the BRDFs measured by Matusik et al. [2003], but we focus on the difficult grazing angles. Our result is a new Phong variant that fits better to a broader range of materials, and, for this model, we address the above-mentioned fitting issues.

VirtualTable: a projection augmented reality game

VirtualTable is a projection augmented reality installation where users are engaged in an interactive tower defense game. The installation runs continuously and is designed to attract people to a table, which the game is projected onto. Any number of players can join the game for an optional period of time. The goal is to prevent the virtual stylized soot balls, spawning on one side of the table, from reaching the cheese. To stop them, the players can place any kind of object on the table, that then will become part of the game. Depending on the object, it will become either a wall, an obstacle for the soot balls, or a tower, that eliminates them within a physical range. The number of enemies is dependent on the number of objects in the field, forcing the players to use strategy and collaboration and not the sheer number of objects to win the game.

Computer Aided Identification of Motion Disturbances Related to Parkinson’s Disease

We present a framework for assessing which types of simple movement tasks are most discriminative between healthy controls and Parkinson’s patients. We collected movement data in a game-like environment, where we used the Microsoft Kinect sensor for tracking the user’s joints. We recruited 63 individuals for the study, of whom 30 had been diagnosed with Parkinson’s disease. A physician evaluated all participants on movement-related rating scales, e.g., elbow rigidity. The participants also completed the game task, moving their arms through a specific pattern. We present an innovative approach for data acquisition in a game-like environment, and we propose a novel method, sparse ordinal regression, for predicting the severity of motion disorders from the data.

An Image-Based Method for Objectively Assessing Injection Moulded Plastic Quality

In high volume productions based on casting processes, like high-pressure die casting (HPDC) or injection moulding, there is a wide range of variables that affect the end quality of produced parts. These variables include production parameters (temperature, pressure, mixture), and external factors (humidity, temperature, etc.). With this many variables it is a challenge to maintain a stable output quality, wherefore massive amounts of resources are spent on quality assurance (QA) of produced parts. Currently, this QA is done manually through visual inspection. We demonstrate how a multispectral imaging system can be used to automatically rate the quality of a produced part using an autocorrelation and a Fourier-based method. These methods are compared with human rankings and achieve good correlations on a variety of samples.

A Variational Study on BRDF Reconstruction in a Structured Light Scanner

Time-efficient acquisition of reflectance behavior together with surface geometry is a challenging problem. In this study, we investigate the impact of system parameter uncertainties when incorporating a data-driven BRDF reconstruction approach into the standard pipeline of a structured light scanning system. The parameters investigated include geometric detail of scanned objects; vertex positions and normals; and position and intensity of light sources. To have full control of uncertainties, experiments are carried out in a simulated environment, mimicking an actual structured light scanning setup. Results show that while uncertainties in vertex positions and normals have a high impact on the quality of reconstructed BRDFs, object geometry and light source properties have very little influence on the reconstructed BRDFs. With this analysis, practitioners now have insight in the tolerances required for accurate BRDF acquisition to work.

Virtual reality inspection and painting with measured BRDFs

This is a virtual reality (VR) painting application that enables the user to paint on 3D models with real measured materials, much like in the physical world. A scanned physical object can be imported into the VR application, and the user can paint on the surface of the object with a virtual hand-controlled paint brush. The user is presented with several paint buckets, each containing a material known from the physical world. These materials are measured bidirectional reflectance distribution functions (BRDFs) of real physical materials. The materials and objects present in VR are thus represented as they would be in the physical world, and the user can control both the environment lighting and a single light source. The application enables analog artists to apply their skills directly on a digital model and it enables engineers to directly inspect BRDFs in a fast and intuitive way. Figure 1 is a screenshot from the application showing models that have been painted with BRDFs.

Photon rectify: undistort any footage on the timeline

Action cameras have allowed footage from previously unseen points of view, drones allow for innovative aerial shots, which a few years ago, were either impossible or required a helicopter, and finally DSLR video and lens adaptors have made any lens available for video production. These advances provide especially low-budget movie productions with completely new flexibility and potential.

Scene reassembly after multimodal digitization and pipeline evaluation using photorealistic rendering

Transparent objects require acquisition modalities that are very different from the ones used for objects with more diffuse reflectance properties. Digitizing a scene where objects must be acquired with different modalities requires scene reassembly after reconstruction of the object surfaces. This reassembly of a scene that was picked apart for scanning seems unexplored. We contribute with a multimodal digitization pipeline for scenes that require this step of reassembly. Our pipeline includes measurement of bidirectional reflectance distribution functions and high dynamic range imaging of the lighting environment. This enables pixelwise comparison of photographs of the real scene with renderings of the digital version of the scene. Such quantitative evaluation is useful for verifying acquired material appearance and reconstructed surface geometry, which is an important aspect of digital content creation. It is also useful for identifying and improving issues in the different steps of the pipeline. In this work, we use it to improve reconstruction, apply analysis by synthesis to estimate optical properties, and to develop our method for scene reassembly.