Isosurface Similarity Maps

In this paper, we introduce the concept of isosurface similarity maps for the visualization of volume data. Iso‐surface similarity maps present structural information of a volume data set by depicting similarities between individual isosurfaces quantified by a robust information‐theoretic measure. Unlike conventional histograms, they are not based on the frequency of isovalues and/or derivatives and therefore provide complementary information. We demonstrate that this new representation can be used to guide transfer function design and visualization parameter specification. Furthermore, we use isosurface similarity to develop an automatic parameter‐free method for identifying representative isovalues. Using real‐world data sets, we show that isosurface similarity maps can be a useful addition to conventional classification techniques.     

Real‐Time Temporal‐Coherent Color Contrast Enhancement for Dichromats

We present an automatic image‐recoloring technique for enhancing color contrast for dichromats whose computational cost varies linearly with the number of input pixels. Our approach can be efficiently implemented on GPUs, and we show that for typical image sizes it is up to two orders of magnitude faster than the current state‐of‐the‐art technique. Unlike previous approaches, ours preserve temporal coherence and, therefore, is suitable for video recoloring. We demonstrate the effectiveness of our technique by integrating it into a visualization system and showing, for the first time, real‐time high‐quality recolored visualizations for dichromats.     

Scalable Programmable Motion Effects on GPUs

We present an efficient and scalable system that enables programmable motion effects on GPUs. Our system is based on the framework proposed by Schmid et al. [ [SSBG10] ] that extends the concept of a surface shader to that of a programmable motion effect. While capable of expressing a variety of motion depiction styles, the execution of motion effect programs requires global knowledge about all portions of an object's surface that passes in front of a pixel during an arbitrarily long period of time, resulting in extremely high memory usage and significantly restricting the degree of parallelism of typical GPU rendering algorithms that parallelize computations over pixels in each frame of animations. To address this problem, we design our system to process multiple frames of a pixel in parallel. This new parallelization approach enables better utilization of GPU memory and also makes it possible to design an efficient out‐of‐core algorithm required in rendering real‐world animations. We also develop an analytical visibility algorithm to resolve depth conflicts of objects, reducing the required temporal resampling rate and further exposing parallelism. Experiments show that we are able to handle very large scenes and improve runtime performance up to an order of magnitude.     

Re‐Compositable Panoramic Selfie with Robust Multi‐Frame Segmentation and Stitching

It is a challenging task for ordinary users to capture selfies with a good scene composition, given the limited freedom to position the camera. Creative hardware (e.g., selfie sticks) and software (e.g., panoramic selfie apps) solutions have been proposed to extend the background coverage of a selife, but to achieve a perfect composition on the spot when the selfie is captured remains to be difficult. In this paper, we propose a system that allows the user to shoot a selfie video by rotating the body first, then produce a final panoramic selfie image with user‐guided scene composition as postprocessing. Our key technical contribution is a fully Automatic, robust multi‐frame segmentation and stitching framework that is tailored towards the special characteristics of selfie images. We analyze the sparse feature points and employ a spatial‐temporal optimization for bilayer feature segmentation, which leads to more reliable background alignment than previous image stitching techniques. The sparse classification is then propagated to all pixels to create dense foreground masks for person‐background composition. Finally, based on a user‐selected foreground position, our system uses content‐preserving warping to produce a panoramic seflie with minimal distortion to the face region. Experimental results show that our approach can reliably generate high quality panoramic selfies, while a simple combination of previous image stitching and segmentation approaches often fails.     

Real‐time Depth of Field Rendering via Dynamic Light Field Generation and Filtering

We present a new algorithm for efficient rendering of high‐quality depth‐of‐field (DoF) effects. We start with a single rasterized view (reference view) of the scene, and sample the light field by warping the reference view to nearby views. We implement the algorithm using NVIDIA's CUDA to achieve parallel processing, and exploit the atomic operations to resolve visibility when multiple pixels warp to the same image location. We then directly synthesize DoF effects from the sampled light field. To reduce aliasing artifacts, we propose an image‐space filtering technique that compensates for spatial undersampling using MIP mapping. The main advantages of our algorithm are its simplicity and generality. We demonstrate interactive rendering of DoF effects in several complex scenes. Compared to existing methods, ours does not require ray tracing and hence scales well with scene complexity.     

Per‐Vertex Defocus Blur for Stochastic Rasterization

We present user‐controllable and plausible defocus blur for a stochastic rasterizer. We modify circle of confusion coefficients per vertex to express more general defocus blur, and show how the method can be applied to limit the foreground blur, extend the in‐focus range, simulate tilt‐shift photography, and specify per‐object defocus blur. Furthermore, with two simplifying assumptions, we show that existing triangle coverage tests and tile culling tests can be used with very modest modifications. Our solution is temporally stable and handles simultaneous motion blur and depth of field.     

Practical Real‐Time Lens‐Flare Rendering

We present a practical real‐time approach for rendering lens‐flare effects. While previous work employed costly ray tracing or complex polynomial expressions, we present a coarser, but also significantly faster solution. Our method is based on a first‐order approximation of the ray transfer in an optical system, which allows us to derive a matrix that maps lens flare‐producing light rays directly to the sensor. The resulting approach is easy to implement and produces physically‐plausible images at high framerates on standard off‐the‐shelf graphics hardware.     

Topological Landscape Ensembles for Visualization of Scalar‐Valued Functions

Visual representation techniques enable perception and exploration of scientific data. Following the topological landscapes metaphor of Weber et al., we provide a new algorithm for visualizing scalar functions defined on simply connected domains of arbitrary dimension. For a potentially high dimensional scalar field, our algorithm produces a collection of, in some sense complete, two‐dimensional terrain models whose contour trees and corresponding topological persistences are identical to those of the input scalar field. The algorithm exactly preserves the volume of each region corresponding to an arc in the contour tree. We also introduce an efficiently computable metric on terrain models we generate. Based on this metric, we develop a tool that can help the users to explore the space of possible terrain models.     

Interactive High‐Quality Visualization of Higher‐Order Finite Elements

Higher‐order finite element methods have emerged as an important discretization scheme for simulation. They are increasingly used in contemporary numerical solvers, generating a new class of data that must be analyzed by scientists and engineers. Currently available visualization tools for this type of data are either batch oriented or limited to certain cell types and polynomial degrees. Other approaches approximate higher‐order data by resampling resulting in trade‐offs in interactivity and quality. To overcome these limitations, we have developed a distributed visualization system which allows for interactive exploration of non‐conforming unstructured grids, resulting from space‐time discontinuous Galerkin simulations, in which each cell has its own higher‐order polynomial solution. Our system employs GPU‐based raycasting for direct volume rendering of complex grids which feature non‐convex, curvilinear cells with varying polynomial degree. Frequency‐based adaptive sampling accounts for the high variations along rays. For distribution across a GPU cluster, the initial object‐space partitioning is determined by cell characteristics like the polynomial degree and is adapted at runtime by a load balancing mechanism. The performance and utility of our system is evaluated for different aeroacoustic simulations involving the propagation of shock fronts.     

Two‐Colored Pixels

In this paper we show how to use two‐colored pixels as a generic tool for image processing. We apply two‐colored pixels as a basic operator as well as a supporting data structure for several image processing applications. Traditionally, images are represented by a regular grid of square pixels with one constant color each. In the two‐colored pixel representation, we reduce the image resolution and replace blocks of N × N pixels by one square that is split by a (feature) line into two regions with constant colors. We show how the conversion of standard mono‐colored pixel images into two‐colored pixel images can be computed efficiently by applying a hierarchical algorithm along with a CUDA‐based implementation. Two‐colored pixels overcome some of the limitations that classical pixel representations have, and their feature lines provide minimal geometric information about the underlying image region that can be effectively exploited for a number of applications. We show how to use two‐colored pixels as an interactive brush tool, achieving realtime performance for image abstraction and non‐photorealistic filtering. Additionally, we propose a realtime solution for image retargeting, defined as a linear minimization problem on a regular or even adaptive two‐colored pixel image. The concept of two‐colored pixels can be easily extended to a video volume, and we demonstrate this for the example of video retargeting.     

Interactive Learning for Point‐Cloud Motion Segmentation

Segmenting a moving foreground (fg) from its background (bg) is a fundamental step in many Machine Vision and Computer Graphics applications. Nevertheless, hardly any attempts have been made to tackle this problem in dynamic 3D scanned scenes. Scanned dynamic scenes are typically challenging due to noise and large missing parts. Here, we present a novel approach for motion segmentation in dynamic point‐cloud scenes designed to cater to the unique properties of such data. Our key idea is to augment fg/bg classification with an active learning framework by refining the segmentation process in an adaptive manner. Our method initially classifies the scene points as either fg or bg in an un‐supervised manner. This, by training discriminative RBF‐SVM classifiers on automatically labeled, high‐certainty fg/bg points. Next, we adaptively detect unreliable classification regions (i.e. where fg/bg separation is uncertain), locally add more training examples to better capture the motion in these areas, and re‐train the classifiers to fine‐tune the segmentation. This not only improves segmentation accuracy, but also allows our method to perform in a coarse‐to‐fine manner, thereby efficiently process high‐density point‐clouds. Additionally, we present a unique interactive paradigm for enhancing this learning process, by using a manual editing tool. The user explicitly edits the RBF‐SVM decision borders in unreliable regions in order to refine and correct the classification. We provide extensive qualitative and quantitative experiments on both real (scanned) and synthetic dynamic scenes.     

Intrinsic Images by Clustering

Decomposing an input image into its intrinsic shading and reflectance components is a long‐standing ill‐posed problem. We present a novel algorithm that requires no user strokes and works on a single image. Based on simple assumptions about its reflectance and luminance, we first find clusters of similar reflectance in the image, and build a linear system describing the connections and relations between them. Our assumptions are less restrictive than widely‐adopted Retinex‐based approaches, and can be further relaxed in conflicting situations. The resulting system is robust even in the presence of areas where our assumptions do not hold. We show a wide variety of results, including natural images, objects from the MIT dataset and texture images, along with several applications, proving the versatility of our method.     

Video Painting via Motion Layer Manipulation

Temporal coherence is an important problem in Non‐Photorealistic Rendering for videos. In this paper, we present a novel approach to enhance temporal coherence in video painting. Instead of painting on video frame, our approach first partitions the video into multiple motion layers, and then places the brush strokes on the layers to generate the painted imagery. The extracted motion layers consist of one background layer and several object layers in each frame. Then, background layers from all the frames are aligned into a panoramic image, on which brush strokes are placed to paint the background in one‐shot. The strokes used to paint object layers are propagated frame by frame using smooth transformations defined by thin plate splines. Once the background and object layers are painted, they are projected back to each frame and blent to form the final painting results. Thanks to painting a single image, our approach can completely eliminate the flickering in background, and temporal coherence on object layers is also significantly enhanced due to the smooth transformation over frames. Additionally, by controlling the painting strokes on different layers, our approach is easy to generate painted video with multi‐style. Experimental results show that our approach is both robust and efficient to generate plausible video painting.     

Adaptive Cross‐sections of Anatomical Models

Medical illustrations have been used for a long time for teaching and communicating information for diagnosis or surgery planning. Illustrative visualization systems create methods and tools that adapt traditional illustration techniques to enhance the result of renderings. Clipping the volume is a popular operation in volume rendering for inspecting the inner parts, though it may remove some information of the context that is worth preserving. In this paper we present a new editing technique based on the use of clipping planes, direct structure extrusion, and illustrative methods, which preserves the context by adapting the extruded region to the structures of interest of the volumetric model. We will show that users may interactively modify the clipping plane and edit the structures to highlight, in order to easily create the desired result. Our approach works with segmented volume models and non‐segmented ones. In the last case, a local segmentation is performed on‐the‐fly. We will demonstrate the efficiency and utility of our method.     

Contrast‐aware Halftoning

This paper proposes two variants of a simple but efficient algorithm for structure‐preserving halftoning. Our algorithm extends Floyd‐Steinberg error diffusion; the goal of our extension is not only to produce good tone similarity but also to preserve structure and especially contrast, motivated by our intuition that human perception is sensitive to contrast. By enhancing contrast we attempt to preserve and enhance structure also. Our basic algorithm employs an adaptive, contrast‐aware mask. To enhance contrast, darker pixels should be more likely to be chosen as black pixels while lighter pixels should be more likely to be set as white. Therefore, when the positive error is diffused to nearby pixels in a mask, the dark pixels absorb less error and the light pixels absorb more. Conversely, negative error is distributed preferentially to dark pixels. We also propose using a mask with values that drop off steeply from the centre, intended to promote good spatial distribution. It is a very fast method whose speed mainly depends on the size of the mask. But this method suffers from distracting patterns. We then propose a variant on the basic idea which overcomes the first algorithm's shortcomings while maintaining its advantages through a priority‐aware scheme. Rather than proceeding in random or raster order, we sort the image first; each pixel is assigned a priority based on its up‐to‐date distance to black or to white, and pixels with extreme intensities are processed earlier. Since we use the same mask strategy as before, we promote good spatial distribution and high contrast. We use tone similarity, structure similarity, and contrast similarity to validate our algorithm. Comparisons with recent structure‐aware algorithms show that our method gives better results without sacrificing speed.     

A Dynamic Noise Primitive for Coherent Stylization

We present a new solution for temporal coherence in non‐photorealistic rendering (NPR) of animations. Given the conflicting goals of preserving the 2D aspect of the style and the 3D scene motion, any such solution is a tradeoff. We observe that primitive‐based methods in NPR can be seen as texture‐based methods when using large numbers of primitives, leading to our key insight, namely that this process is similar to sparse convolution noise in procedural texturing. Consequently, we present a new primitive for NPR based on Gabor noise, that preserves the 2D aspect of noise, conveys the 3D motion of the scene, and is temporally continuous. We can thus use standard techniques from procedural texturing to create various styles, which we show for interactive NPR applications. We also present a user study to evaluate this and existing solutions, and to provide more insight in the trade‐off implied by temporal coherence. The results of the study indicate that maintaining coherent motion is important, but also that our new solution provides a good compromise between the 2D aspect of the style and 3D motion.     

ProbExplorer: Uncertainty‐guided Exploration and Editing of Probabilistic Medical Image Segmentation

In this paper, we develop an interactive analysis and visualization tool for probabilistic segmentation results in medical imaging. We provide a systematic approach to analyze, interact and highlight regions of segmentation uncertainty. We introduce a set of visual analysis widgets integrating different approaches to analyze multivariate probabilistic field data with direct volume rendering. We demonstrate the user's ability to identify suspicious regions (e.g. tumors) and correct the misclassification results using a novel uncertainty‐based segmentation editing technique. We evaluate our system and demonstrate its usefulness in the context of static and time‐varying medical imaging datasets.     

Perceptually‐motivated Real‐time Temporal Upsampling of 3D Content for High‐refresh‐rate Displays

High‐refresh‐rate displays (e. g., 120 Hz) have recently become available on the consumer market and quickly gain on popularity. One of their aims is to reduce the perceived blur created by moving objects that are tracked by the human eye. However, an improvement is only achieved if the video stream is produced at the same high refresh rate (i. e. 120 Hz). Some devices, such as LCD TVs, solve this problem by converting low‐refresh‐rate content (i. e. 50 Hz PAL) into a higher temporal resolution (i. e. 200 Hz) based on two‐dimensional optical flow. In our approach, we will show how rendered three‐dimensional images produced by recent graphics hardware can be up‐sampled more efficiently resulting in higher quality at the same time. Our algorithm relies on several perceptual findings and preserves the naturalness of the original sequence. A psychophysical study validates our approach and illustrates that temporally up‐sampled video streams are preferred over the standard low‐rate input by the majority of users. We show that our solution improves task performance on high‐refresh‐rate displays.     

A Salience‐based Quality Metric for Visualization

Salience detection is a principle mechanism to facilitate visual attention. A good visualization guides the observer's attention to the relevant aspects of the representation. Hence, the distribution of salience over a visualization image is an essential measure of the quality of the visualization. We describe a method for computing such a metric for a visualization image in the context of a given dataset. We show how this technique can be used to analyze a visualization's salience, improve an existing visualization, and choose the best representation from a set of alternatives. The usefulness of this proposed metric is illustrated using examples from information visualization, volume visualization and flow visualization.     

Stroke‐guided Image Synthesis for Skeletal Structure Editing

Creating variations of an image object is an important task, which usually requires manipulating the skeletal structure of the object. However, most existing methods (such as image deformation) only allow for stretching the skeletal structure of an object: modifying skeletal topology remains a challenge. This paper presents a technique for synthesizing image objects with different skeletal structures while respecting to an input image object. To apply this technique, a user firstly annotates the skeletal structure of the input object by specifying a number of strokes in the input image, and draws corresponding strokes in an output domain to generate new skeletal structures. Then, a number of the example texture pieces are sampled along the strokes in the input image and pasted along the strokes in the output domain with their orientations. The result is obtained by optimizing the texture sampling and seam computation. The proposed method is successfully used to synthesize challenging skeletal structures, such as skeletal branches, and a wide range of image objects with various skeletal structures, to demonstrate its effectiveness.