Real-time High Resolution Fusion of Depth Maps on GPU

A system for live high quality surface reconstruction using a single moving depth camera on a commodity hardware is presented. High accuracy and real-time frame rate is achieved by utilizing graphics hardware computing capabilities via OpenCL and by using sparse data structure for volumetric surface representation. Depth sensor pose is estimated by combining serial texture registration algorithm with iterative closest points algorithm (ICP) aligning obtained depth map to the estimated scene model. Aligned surface is then fused into the scene. Kalman filter is used to improve fusion quality. Truncated signed distance function (TSDF) stored as block-based sparse buffer is used to represent surface. Use of sparse data structure greatly increases accuracy of scanned surfaces and maximum scanning area. Traditional GPU implementation of volumetric rendering and fusion algorithms were modified to exploit sparsity to achieve desired performance. Incorporation of texture registration for sensor pose estimation and Kalman filter for measurement integration improved accuracy and robustness of scanning process

A new isosurface extraction method on arbitrary grids

The development of interface-capturing methods (such as level-set, phase-field or volume of fluid (VOF) methods) for arbitrary 3D grids has further highlighted the need for more accurate and efficient interface reconstruction procedures. In this work, we propose a new method for the extraction of isosurfaces on arbitrary polyhedra that can be used with advantage for this purpose. The isosurface is extracted from volume fractions by a general polygon tracing procedure, which is valid for convex or non-convex geometries, even with non-planar faces. The proposed method, which can be considered as an extension of the marching cubes technique, produces consistent results even for ambiguous situations in polyhedra of arbitrary shape. To show the reproducibility of the results presented in this work, we provide the open source library isoap, which has been developed to implement the proposed method and includes test programs to demonstrate the successful extraction of isosurfaces on several grids with polyhedral cells of different types. We present results obtained not only for isosurface extraction from discrete volume fractions resulting from a volume of fluid method, but also from data sets obtained from implicit mathematical functions and signed distances to scanned surfaces. The improvement provided by the proposed method for the extraction of isosurfaces in arbitrary grids will also be very useful in other fields, such as CFD visualization or medical imaging.The authors gratefully acknowledge the support of the Spanish Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación and FEDER through projects DPI2017-87826-C2-1-P and DPI2017-87826-C2-2-P

Crease surfaces: from theory to extraction and application to diffusion tensor MRI

Crease surfaces are two-dimensional manifolds along which a scalar field assumes a local maximum (ridge) or a local minimum (valley) in a constrained space. Unlike isosurfaces, they are able to capture extremal structures in the data. Creases have a long tradition in image processing and computer vision, and have recently become a popular tool for visualization. When extracting crease surfaces, degeneracies of the Hessian (i.e., lines along which two eigenvalues are equal), have so far been ignored. We show that these loci, however, have two important consequences for the topology of crease surfaces: First, creases are bounded not only by a side constraint on eigenvalue sign, but also by Hessian degeneracies. Second, crease surfaces are not in general orientable. We describe an efficient algorithm for the extraction of crease surfaces which takes these insights into account and demonstrate that it produces more accurate results than previous approaches. Finally, we show that DT-MRI streamsurfaces, which were previously used for the analysis of planar regions in diffusion tensor MRI data, are mathematically ill-defined. As an example application of our method, creases in a measure of planarity are presented as a viable substitute

Analysis of (iso)surface reconstructions: Quantitative metrics and methods

Due to sampling processes volumetric data is inherently discrete and most often knowledge of the underlying continuous model is not available. Surface rendering techniques attempt to reconstruct the continuous model, using isosurfaces, from the discrete data. Therefore, it natural to ask how accurate the reconstructed isosurfaces are with respect to the underlying continuous model. A reconstructed isosurface may look impressive when rendered ( photorealism ), but how well does it reflect reality ( physical realism )?;The users of volume visualization packages must be aware of the short-comings of the algorithms used to produce the images so that they may properly interpret, and interact with, what they see. However, very little work has been done to quantify the accuracy of volumetric data reconstructions. Most analysis to date has been qualitative. Qualitative analysis uses simple visual inspection to determine whether characteristics, known to exist in the real world object, are present in the rendered image. Our research suggests metrics and methods for quantifying the physical realism of reconstructed isosurfaces.;Physical realism is a many faceted notion. In fact, a different metric could be defined for each physical property one wishes to consider. We have defined four metrics--Global Surface Area Preservation (GSAP), Volume Preservation (VP), Point Distance Preservation (PDP), and Isovalue Preservation (IVP). We present experimental results for each of these metrics and discuss their validity with respect to those results.;We also present the Reconstruction Quantification (sub)System (RQS). RQS provides a flexible framework for measuring physical realism. This system can be embedded in existing visualization systems with little modification of the system itself. Two types of analysis can be performed; reconstruction analysis and algorithm analysis. Reconstruction analysis allows users to determine the accuracy of individual surface reconstructions. Algorithm analysis, on the other hand, allows developers of visualization systems to determine the efficacy of the visualization system based on several reconstructions

Model-Based Visualization for Intervention Planning

Computer support for intervention planning is often a two-stage process: In a first stage, the relevant segmentation target structures are identified and delineated. In a second stage, image analysis results are employed for the actual planning process. In the first stage, model-based segmentation techniques are often used to reduce the interaction effort and increase the reproducibility. There is a similar argument to employ model-based techniques for the visualization as well. With increasingly more visualization options, users have many parameters to adjust in order to generate expressive visualizations. Surface models may be smoothed with a variety of techniques and parameters. Surface visualization and illustrative rendering techniques are controlled by a large set of additional parameters. Although interactive 3d visualizations should be flexible and support individual planning tasks, appropriate selection of visualization techniques and presets for their parameters is needed. In this chapter, we discuss this kind of visualization support. We refer to model-based visualization to denote the selection and parameterization of visualization techniques based on \u27a priori knowledge concerning visual perception, shapes of anatomical objects and intervention planning tasks

Doctor of Philosophy

dissertationIn this dissertation, we advance the theory and practice of verifying visualization algorithms. We present techniques to assess visualization correctness through testing of important mathematical properties. Where applicable, these techniques allow us to distinguish whether anomalies in visualization features can be attributed to the underlying physical process or to artifacts from the implementation under verification. Such scientific scrutiny is at the heart of verifiable visualization - subjecting visualization algorithms to the same verification process that is used in other components of the scientific pipeline. The contributions of this dissertation are manifold. We derive the mathematical framework for the expected behavior of several visualization algorithms, and compare them to experimentally observed results in the selected codes. In the Computational Science & Engineering community CS&E, this technique is know as the Method of Manufactured Solution (MMS). We apply MMS to the verification of geometrical and topological properties of isosurface extraction algorithms, and direct volume rendering. We derive the convergence of geometrical properties of isosurface extraction techniques, such as function value and normals. For the verification of topological properties, we use stratified Morse theory and digital topology to design algorithms that verify topological invariants. In the case of volume rendering algorithms, we provide the expected discretization errors for three different error sources. The results of applying the MMS is another important contribution of this dissertation. We report unexpected behavior for almost all implementations tested. In some cases, we were able to find and fix bugs that prevented the correctness of the visualization algorithm. In particular, we address an almost 2 0 -year-old bug with the core disambiguation procedure of Marching Cubes 33, one of the first algorithms intended to preserve the topology of the trilinear interpolant. Finally, an important by-product of this work is a range of responses practitioners can expect to encounter with the visualization technique under verification