VIAN: A Visual Annotation Tool for Film Analysis

While color plays a fundamental role in film design and production, existing solutions for film analysis in the digital humanities address perceptual and spatial color information only tangentially. We introduce VIAN, a visual film annotation system centered on the semantic aspects of film color analysis. The tool enables expert‐assessed labeling, curation, visualization and Classification of color features based on their perceived context and aesthetic quality. It is the first of its kind that incorporates foreground‐background information made possible by modern deep learning segmentation methods. The proposed tool seamlessly integrates a multimedia data management system, so that films can undergo a full color‐oriented analysis pipeline.     

LOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualization

Visualization of large vector line data is a core task in geographic and cartographic systems. Vector maps are often displayed at different cartographic generalization levels, traditionally by using several discrete levels-of-detail (LODs). This limits the generalization levels to a fixed and predefined set of LODs, and generally does not support smooth LOD transitions. However, fast GPUs and novel line rendering techniques can be exploited to integrate dynamic vector map LOD management into GPU-based algorithms for locally-adaptive line simplification and real-time rendering. We propose a new technique that interactively visualizes large line vector datasets at variable LODs. It is based on the Douglas-Peucker line simplification principle, generating an exhaustive set of line segments whose specific subsets represent the lines at any variable LOD. At run time, an appropriate and view-dependent error metric supports screen-space adaptive LOD levels and the display of the correct subset of line segments accordingly. Our implementation shows that we can simplify and display large line datasets interactively. We can successfully apply line style patterns, dynamic LOD selection lenses, and anti-aliasing techniques to our line rendering.     

Polarization bistability in tuned, external-grating diode lasers

Spectral domains showing polarization-wavelength hysteresis regions up to 0.3 nm wide were observed when the emission frequency of a diode laser having a nearly polarization-independent confinement factor was tuned in a simple external cavity with grating. In these regions the laser emits in a stable single mode with either TE or TM polarization, depending on whether the region was entered from lower or higher wavelengths. We explain the observed phenomenon on the basis of nonlinear gain saturation between TE and TM polarization     

Piecewise‐planar Reconstruction of Multi‐room Interiors with Arbitrary Wall Arrangements

Reconstructing the as‐built architectural shape of building interiors has emerged in recent years as an important and challenging research problem. An effective approach must be able to faithfully capture the architectural structures and separate permanent components from clutter (e.g. furniture), while at the same time dealing with defects in the input data. For many applications, higher‐level information on the environment is also required, in particular the shape of individual rooms. To solve this ill‐posed problem, state‐of‐the‐art methods assume constrained input environments with a 2.5D or, more restrictively, a Manhattan‐world structure, which significantly restricts their applicability in real‐world settings. We present a novel pipeline that allows to reconstruct general 3D interior architectures, significantly increasing the range of real‐world architectures that can be reconstructed and labeled by any interior reconstruction method to date. Our method finds candidate permanent components by reasoning on a graph‐based scene representation, then uses them to build a 3D linear cell complex that is partitioned into separate rooms through a multi‐label energy minimization formulation. We demonstrate the effectiveness of our method by applying it to a variety of real‐world and synthetic datasets and by comparing it to more specialized state‐of‐the‐art approaches.     

Compressed progressive meshes

Most systems that support visual interaction with 3D models use shape representations based on triangle meshes. The size of these representations imposes limits on applications for which complex 3D models must be accessed remotely. Techniques for simplifying and compressing 3D models reduce the transmission time. Multiresolution formats provide quick access to a crude model and then refine it progressively. Unfortunately, compared to the best nonprogressive compression methods, previously proposed progressive refinement techniques impose a significant overhead when the full resolution model must be downloaded. The CPM (compressed progressive meshes) approach proposed here eliminates this overhead. It uses a new technique, which refines the topology of the mesh in batches, which each increase the number of vertices by up to 50 percent. Less than an amortized total of 4 bits per triangle encode where and how the topological refinements should be applied. We estimate the position of new vertices from the positions of their topological neighbors in the less refined mesh using a new estimator that leads to representations of vertex coordinates that are 50 percent more compact than previously reported progressive geometry compression techniques     

Interactive multiscale tensor reconstruction for multiresolution volume visualization

Large scale and structurally complex volume datasets from high-resolution 3D imaging devices or computational simulations pose a number of technical challenges for interactive visual analysis. In this paper, we present the first integration of a multiscale volume representation based on tensor approximation within a GPU-accelerated out-of-core multiresolution rendering framework. Specific contributions include (a) a hierarchical brick-tensor decomposition approach for pre-processing large volume data, (b) a GPU accelerated tensor reconstruction implementation exploiting CUDA capabilities, and (c) an effective tensor-specific quantization strategy for reducing data transfer bandwidth and out-of-core memory footprint. Our multiscale representation allows for the extraction, analysis and display of structural features at variable spatial scales, while adaptive level-of-detail rendering methods make it possible to interactively explore large datasets within a constrained memory footprint. The quality and performance of our prototype system is evaluated on large structurally complex datasets, including gigabyte-sized micro-tomographic volumes.     

A unified particle model for fluid–solid interactions

We present a new method for the simulation of melting and solidification in a unified particle model. Our technique uses the Smoothed Particle Hydrodynamics (SPH) method for the simulation of liquids, deformable as well as rigid objects, which eliminates the need to define an interface for coupling different models. Using this approach, it is possible to simulate fluids and solids by only changing the attribute values of the underlying particles. We significantly changed a prior elastic particle model to achieve a flexible model for melting and solidification. By using an SPH approach and considering a new definition of a local reference shape, the simulation of merging and splitting of different objects, as may be caused by phase change processes, is made possible. In order to keep the system stable even in regions represented by a sparse set of particles we use a special kernel function for solidification processes. Additionally, we propose a surface reconstruction technique based on considering the movement of the center of mass to reduce rendering errors in concave regions. The results demonstrate new interaction effects concerning the melting and solidification of material, even while being surrounded by liquids. Copyright © 2007 John Wiley & Sons, Ltd.     

Efficient reduction of point data sets for surface splatting using geometry and color attributes

Surface splat, one of the point-based rendering primitives, has offered a powerful alternative to triangle meshes when it comes to the rendering of highly complex objects due to its potential for high-performance and high-quality rendering. Recently, the technological advance of 3D scanners has made it possible to acquire color as well as geometry data of highly complex objects with very high speed and accuracy. However, scanning and acquisition systems often produce surfaces that are much more dense than actually required for the intended application. Therefore, reduction of point data set is necessary to further process the model. Although many efficient sampling methods for point-based surfaces have been proposed to reduce the complexity of geometric models, none of these has taken into account color, which is fundamental for achieving a high quality visual appearance. Therefore, we propose an efficient sampling method of point data sets for surface splatting which uses both geometry and color attributes. Our proposed method converts a dense set of point samples into a sparse set of object space splats. It successfully approximates of the original model within a given geometric and color error. In order to measure color differences between point samples with consistency, the color error tolerance is evaluated in a CIELAB uniform color space.     

State-of-the-art in Automatic 3D Reconstruction of Structured Indoor Environments

Creating high-level structured 3D models of real-world indoor scenes from captured data is a fundamental task which has important applications in many fields. Given the complexity and variability of interior environments and the need to cope with noisy and partial captured data, many open research problems remain, despite the substantial progress made in the past decade. In this survey, we provide an up-to-date integrative view of the field, bridging complementary views coming from computer graphics and computer vision. After providing a characterization of input sources, we define the structure of output models and the priors exploited to bridge the gap between imperfect sources and desired output. We then identify and discuss the main components of a structured reconstruction pipeline, and review how they are combined in scalable solutions working at the building level. We finally point out relevant research issues and analyze research trends.