Path‐space Motion Estimation and Decomposition for Robust Animation Filtering

Renderings of animation sequences with physics‐based Monte Carlo light transport simulations are exceedingly costly to generate frame‐by‐frame, yet much of this computation is highly redundant due to the strong coherence in space, time and among samples. A promising approach pursued in prior work entails subsampling the sequence in space, time, and number of samples, followed by image‐based spatio‐temporal upsampling and denoising. These methods can provide significant performance gains, though major issues remain: firstly, in a multiple scattering simulation, the final pixel color is the composite of many different light transport phenomena, and this conflicting information causes artifacts in image‐based methods. Secondly, motion vectors are needed to establish correspondence between the pixels in different frames, but it is unclear how to obtain them for most kinds of light paths (e.g. an object seen through a curved glass panel). To reduce these ambiguities, we propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths. Each component is accompanied by motion vectors and other auxiliary features such as reflectance and surface normals. The motion vectors of specular paths are computed using a temporal extension of manifold exploration and the remaining components use a specialized variant of optical flow. Our experiments show that this decomposition leads to significant improvements in three image‐based applications: denoising, spatial upsampling, and temporal interpolation.     

Time‐Series Plots Integrated in Parallel‐Coordinates Displays

We present a natural extension of two‐dimensional parallel‐coordinates plots for revealing relationships in time‐dependent multi‐attribute data by building on the idea that time can be considered as the third dimension. A time slice through the visualization represents a certain point in time and can be viewed as a regular parallel‐coordinates display. A vertical slice through one of the axes of the parallel‐coordinates display would show a time‐series plot. For a focus‐and‐context Integration of both views, we embed time‐series plots between two adjacent axes of the parallel‐coordinates plot. Both time‐series plots are drawn using a pseudo three‐dimensional perspective with a single vanishing point. An independent parallel‐coordinates panel that connects the two perspectively displayed time‐series plots can move forward and backward in time to reveal changes in the relationship between the time‐dependent attributes. The visualization of time‐series plots in the context of the parallel‐coordinates plot facilitates the exploration of time‐related aspects of the data without the need to switch to a separate display. We provide a consistent set of tools for selecting and contrasting subsets of the data, which are important for various application domains.     

Reduced Aggregate Scattering Operators for Path Tracing

Aggregate scattering operators (ASOs) describe the overall scattering behavior of an asset (i.e., an object or volume, or collection thereof) accounting for all orders of its internal scattering. We propose a practical way to precompute and compactly store ASOs and demonstrate their ability to accelerate path tracing. Our approach is modular avoiding costly and inflexible scene‐dependent precomputation. This is achieved by decoupling light transport within and outside of each asset, and precomputing on a per‐asset level. We store the internal transport in a reduced‐dimensional subspace tailored to the structure of the asset geometry, its scattering behavior, and typical illumination conditions, allowing the ASOs to maintain good accuracy with modest memory requirements. The precomputed ASO can be reused across all instances of the asset and across multiple scenes. We augment ASOs with functionality enabling multi‐bounce importance sampling, fast short‐circuiting of complex light paths, and compact caching, while retaining rapid progressive preview rendering. We demonstrate the benefits of our ASOs by efficiently path tracing scenes containing many instances of objects with complex inter‐reflections or multiple scattering.     

Linkless Octree Using Multi‐Level Perfect Hashing

The standard C/C++ implementation of a spatial partitioning data structure, such as octree and quadtree, is often inefficient in terms of storage requirements particularly when the memory overhead for maintaining parent‐to‐child pointers is significant with respect to the amount of actual data in each tree node. In this work, we present a novel data structure that implements uniform spatial partitioning without storing explicit parent‐to‐child pointer links. Our linkless tree encodes the storage locations of subdivided nodes using perfect hashing while retaining important properties of uniform spatial partitioning trees, such as coarse‐to‐fine hierarchical representation, efficient storage usage, and efficient random accessibility. We demonstrate the performance of our linkless trees using image compression and path planning examples.     

Gradient‐Preserving Color Transfer

Color transfer is an image processing technique which can produce a new image combining one source image's contents with another image's color style. While being able to produce convincing results, however, Reinhard et al.'s pioneering work has two problems—mixing up of colors in different regions and the fidelity problem. Many local color transfer algorithms have been proposed to resolve the first problem, but the second problem was paid few attentions. In this paper, a novel color transfer algorithm is presented to resolve the fidelity problem of color transfer in terms of scene details and colors. It's well known that human visual system is more sensitive to local intensity differences than to intensity itself. We thus consider that preserving the color gradient is necessary for scene fidelity. We formulate the color transfer problem as an optimization problem and solve it in two steps—histogram matching and a gradient‐preserving optimization. Following the idea of the fidelity in terms of color and gradient, we also propose a metric for objectively evaluating the performance of example‐based color transfer algorithms. The experimental results show the validity and high fidelity of our algorithm and that it can be used to deal with local color transfer.     

Interactive Cover Design Considering Physical Constraints

We developed an interactive system to design a customized cover for a given three‐dimensional (3D) object such as a camera, teapot, or car. The system first computes the convex hull of the input geometry. The user segments it into several cloth patches by drawing on the 3D surface. This paper provides two technical contributions. First, it introduces a specialized flattening algorithm for cover patches. It makes each two‐dimensional edge in the flattened pattern equal to or longer than the original 3D edge; a smaller patch would fail to cover the object, and a larger patch would result in extra wrinkles. Second, it introduces a mechanism to verify that the user‐specified opening would be large enough for the object to be removed. Starting with the initial configuration, the system virtually “pulls” the object out of the cover while avoiding excessive stretching of cloth patches. We used the system to design real covers and confirmed that it functions as intended.     

Content‐Aware Automatic Photo Enhancement

Automatic photo enhancement is one of the long‐standing goals in image processing and computational photography. While a variety of methods have been proposed for manipulating tone and colour, most automatic methods used in practice, operate on the entire image without attempting to take the content of the image into account. In this paper, we present a new framework for automatic photo enhancement that attempts to take local and global image semantics into account. Specifically, our content‐aware scheme attempts to detect and enhance the appearance of human faces, blue skies with or without clouds and underexposed salient regions. A user study was conducted that demonstrates the effectiveness of the proposed approach compared to existing auto‐enhancement tools.     

Visualizing Group Structures in Graphs: A Survey

Graph visualizations encode relationships between objects. Abstracting the objects into group structures provides an overview of the data. Groups can be disjoint or overlapping, and might be organized hierarchically. However, the underlying graph still needs to be represented for analyzing the data in more depth. This work surveys research in visualizing group structures as part of graph diagrams. A particular focus is the explicit visual encoding of groups, rather than only using graph layout to indicate groups implicitly. We introduce a taxonomy of visualization techniques structuring the field into four main categories: visual node attributes vary properties of the node representation to encode the grouping, juxtaposed approaches use two separate visualizations, superimposed techniques work with two aligned visual layers, and embedded visualizations tightly integrate group and graph representation. The derived taxonomies for group structure and visualization types are also applied to group visualizations of edges. We survey group‐only, group–node, group–edge and group–network tasks that are described in the literature as use cases of group visualizations. We discuss results from evaluations of existing visualization techniques as well as main areas of application. Finally, we report future challenges based on interviews we conducted with leading researchers of the field.     

Spatial Adjacency Maps for Translucency Simulation under General Illumination

Rendering translucent materials in real time is usually done by using surface diffusion and/or (translucent) shadow maps. The downsides of these approaches are, that surface diffusion cannot handle translucency effects that show up when rendering thin objects, and that translucent shadow maps are only available for point light sources. Furthermore, translucent shadow maps introduce limitations to shadow mapping techniques exploiting the same maps. In this paper we present a novel approach for rendering translucent materials at interactive frame rates. Our approach allows for an efficient calculation of translucency with native support for general illumination conditions, especially area and environment lighting, at high accuracy. The proposed technique's only parameter is the used diffusion profile, and thus it works out of the box without any parameter tuning. Furthermore, it can be used in combination with any existing surface diffusion techniques to add translucency effects. Our approach introduces Spatial Adjacency Maps that depend on precalculations to be done for fixed meshes. We show that these maps can be updated in real time to also handle deforming meshes and that our results are of superior quality as compared to other well known real‐time techniques for rendering translucency.