Characterization for High Dynamic Range Imaging

In this paper we present a new practical camera characterization technique to improve color accuracy in high dynamic range (HDR) imaging. Camera characterization refers to the process of mapping device‐dependent signals, such as digital camera RAW images, into a well‐defined color space. This is a well‐understood process for low dynamic range (LDR) imaging and is part of most digital cameras — usually mapping from the raw camera signal to the sRGB or Adobe RGB color space. This paper presents an efficient and accurate characterization method for high dynamic range imaging that extends previous methods originally designed for LDR imaging. We demonstrate that our characterization method is very accurate even in unknown illumination conditions, effectively turning a digital camera into a measurement device that measures physically accurate radiance values — both in terms of luminance and color — rivaling more expensive measurement instruments.     

Predicting Display Visibility Under Dynamically Changing Lighting Conditions

Display devices, more than ever, are finding their ways into electronic consumer goods as a result of recent trends in providing more functionality and user interaction. Combined with the new developments in display technology towards higher reproducible luminance range, the mobility and variation in capability of display devices are constantly increasing. Consequently, in real life usage it is now very likely that the display emission to be distorted by spatially and temporally varying reflections, and the observer's visual system to be not adapted to the particular display that she is viewing at that moment. The actual perception of the display content cannot be fully understood by only considering steady-state illumination and adaptation conditions. We propose an objective method for display visibility analysis formulating the problem as a full-reference image quality assessment problem, where the display emission under "ideal" conditions is used as the reference for real-life conditions. Our work includes a human visual system model that accounts for maladaptation and temporal recovery of sensitivity. As an example application we integrate our method to a global illumination simulator and analyze the visibility of a car interior display under realistic lighting conditions.     

Compressive Dual Photography

The accurate measurement of the light transport characteristics of a complex scene is an important goal in computer graphics and has applications in relighting and dual photography. However, since the light transport data sets are typically very large, much of the previous research has focused on adaptive algorithms that capture them efficiently. In this work, we propose a novel, non-adaptive algorithm that takes advantage of the compressibility of the light transport signal in a transform domain to capture it with less acquisitions than with standard approaches. To do this, we leverage recent work in the area of compressed sensing, where a signal is reconstructed from a few samples assuming that it is sparse in a transform domain. We demonstrate our approach by performing dual photography and relighting by using a much smaller number of acquisitions than would normally be needed. Because our algorithm is not adaptive, it is also simpler to implement than many of the current approaches.     

Distortion Optimization based Image Completion from a Large Displacement View

We present a new image completion method based on an additional large displacement view (LDV) of the same scene for faithfully repairing large missing regions on the target image in an automatic way. A coarse‐to‐fine distortion correction algorithm is proposed to minimize the perspective distortion in the corresponding parts for the common scene regions on the LDV image. First, under the assumption of a planar scene, the LDV image is warped according to a homography to generate the initial correction result. Second, the residual distortions in the common known scene regions are revealed by means of a mismatch detection mechanism and relaxed by energy optimization of overlap correspondences, with the expectations of color constancy and displacement field smoothness. The fundamental matrix for the two views is then computed based on the reliable correspondence set. Third, under the constraints of epipolar geometry, displacement field smoothness and color consistency of the neighboring pixels, the missing pixels are orderly restored according to a specially defined repairing priority function. We finally eliminate the ghost effect between the repaired region and its surroundings by Poisson image blending. Experimental results demonstrate that our method outperforms recent state‐of‐the‐art image completion methods for repairing large missing area with complex structure information.     

Motion Deblurring from a Single Image using Circular Sensor Motion

Image blur caused by object motion attenuates high frequency content of images, making post‐capture deblurring an ill‐posed problem. The recoverable frequency band quickly becomes narrower for faster object motion as high frequencies are severely attenuated and virtually lost. This paper proposes to translate a camera sensor circularly about the optical axis during exposure, so that high frequencies can be preserved for a wide range of in‐plane linear object motion in any direction within some predetermined speed. That is, although no object may be photographed sharply at capture time, differently moving objects captured in a single image can be deconvolved with similar quality. In addition, circular sensor motion is shown to facilitate blur estimation thanks to distinct frequency zero patterns of the resulting motion blur point‐spread functions. An analysis of the frequency characteristics of circular sensor motion in relation to linear object motion is presented, along with deconvolution results for photographs captured with a prototype camera.     

Contrast Restoration by Adaptive Countershading

The ABSTRACT is to be in fully-justified italicized text, between two horizontal lines, in one-column format, below the author and affiliation information. Use the word “Abstract” as the title, in 9-point Times, boldface type, left-aligned to the text, initially capitalized. The abstract is to be in 9-point, single-spaced type. The abstract may be up to 3 inches (7.62 cm) long. Leave one blank line after the abstract, then add the subject categories according to the ACM Classification Index (see http://www.acm.org/class/1998/ ).     

Parallel Blue‐noise Sampling by Constrained Farthest Point Optimization

We describe a fast sampling algorithm for generating uniformly‐distributed point patterns with good blue noise characteristics. The method, based on constrained farthest point optimization, is provably optimal and may be easily parallelized, resulting in an algorithm whose performance/quality tradeoff is superior to other state‐of‐the‐art approaches.     

Motion based Painterly Rendering

Previous painterly rendering techniques normally use image gradients for deciding stroke orientations. Image gradients are good for expressing object shapes, but difficult to express the flow or movements of objects. In real painting, the use of brush strokes corresponding to the actual movement of objects allows viewers to recognize objects' motion better and thus to have an impression of the dynamic. In this paper, we propose a novel painterly rendering algorithm to express dynamic objects based on their motion information. We first extract motion information (magnitude, direction, standard deviation) of a scene from a set of consecutive image sequences from the same view. Then the motion directions are used for determining stroke orientations in the regions with significant motions, and image gradients determine stroke orientations where little motion is observed. Our algorithm is useful for realistically and dynamically representing moving objects. We have applied our algorithm for rendering landscapes. We could segment a scene into dynamic and static regions, and express the actual movement of dynamic objects using motion based strokes.     

Free Form Incident Light Fields

This paper presents methods for photo‐realistic rendering using strongly spatially variant illumination captured from real scenes. The illumination is captured along arbitrary paths in space using a high dynamic range, HDR, video camera system with position tracking. Light samples are rearranged into 4‐D incident light fields (ILF) suitable for direct use as illumination in renderings. Analysis of the captured data allows for estimation of the shape, position and spatial and angular properties of light sources in the scene. The estimated light sources can be extracted from the large 4D data set and handled separately to render scenes more efficiently and with higher quality. The ILF lighting can also be edited for detailed artistic control.     

Agile Spectrum Imaging: Programmable Wavelength Modulation for Cameras and Projectors

We advocate the use of quickly‐adjustable, computer‐controlled color spectra in photography, lighting and displays. We present an optical relay system that allows mechanical or electronic color spectrum control and use it to modify a conventional camera and projector. We use a diffraction grating to disperse the rays into different colors, and introduce a mask (or LCD/DMD) in the optical path to modulate the spectrum. We analyze the trade‐offs and limitations of this design, and demonstrate its use in a camera, projector and light source. We propose applications such as adaptive color primaries, metamer detection, scene contrast enhancement, photographing fluorescent objects, and high dynamic range photography using spectrum modulation.     

Genuinity Signatures: Designing Signatures for Verifying 3D Object Genuinity

3D computer graphics models and digitally-controlled manufacturing have come together to enable the design, visualization, simulation, and automated creation of complex 3D objects. In our work, we propose and implement a framework for designing computer graphics objects and digitally manufacturing them such that no adversary can make imitations or counterfeit copies of the physical object, even if the adversary has a large number of original copies of the object, knowledge of the original object design, and has manufacturing precision that is comparable to or superior to that of the legitimate creator of the object. Our approach is to design and embed a signature on the surface of the object which acts as a certificate of genuinity of the object. The signature is detectable by a signature-reading device, based on methods in computer graphics and computer vision, which contains some of the secret information that was used when marking the physical object. Further, the compromise of a signature-reading device by an adversary who is able to extract all its secrets, does not enable the adversary to create counterfeit objects that fool other readers, thereby still enabling reliable copy detection. We implemented a prototype of our scheme end-to-end, including the production of the physical object and the genuinity-testing device.     

Object-Space Visibility Ordering for Point-Based and Volume Rendering

This paper presents a method to accelerate algorithms that need a correct and complete visibility ordering of their data for rendering. The technique works by pre‐sorting primitives in object‐space using three lists (one for each axis: X, Y and Z), and then combining the lists using graphics hardware by rendering each list to a texture and merging the textures in the end. We validate our algorithm by applying it to the splatting technique using several types of rendering, including point‐based rendering and volume rendering. We also detail our hardware implementation for volume rendering using point sprites.     

Freehand HDR Imaging of Moving Scenes with Simultaneous Resolution Enhancement

Despite their high popularity, common high dynamic range (HDR) methods are still limited in their practical applicability: They assume that the input images are perfectly aligned, which is often violated in practise. Our paper does not only free the user from this unrealistic limitation, but even turns the missing alignment into an advantage: By exploiting the multiple exposures, we can create a super‐resolution image. The alignment step is performed by a modern energy‐based optic flow approach that takes into account the varying exposure conditions. Moreover, it produces dense displacement fields with subpixel precision. As a consequence, our approach can handle arbitrary complex motion patterns, caused by severe camera shake and moving objects. Additionally, it benefits from several advantages over existing strategies: (i) It is robust under outliers (noise, occlusions, saturation problems) and allows for sharp discontinuities in the displacement field. (ii) The alignment step neither requires camera calibration nor knowledge of the exposure times. (iii) It can be efficiently implemented on CPU and GPU architectures. After the alignment is performed, we use the obtained subpixel accurate displacement fields as input for an energy‐based, joint super‐resolution and HDR (SR‐HDR) approach. It introduces robust data terms and anisotropic smoothness terms in the SR‐HDR literature. Our experiments with challenging real world data demonstrate that these novelties are pivotal for the favourable performance of our approach.     

MultiClusterTree: Interactive Visual Exploration of Hierarchical Clusters in Multidimensional Multivariate Data

Visual analytics of multidimensional multivariate data is a challenging task because of the difficulty in understanding metrics in attribute spaces with more than three dimensions. Frequently, the analysis goal is not to look into individual records but to understand the distribution of the records at large and to find clusters of records with similar attribute values. A large number of (typically hierarchical) clustering algorithms have been developed to group individual records to clusters of statistical significance. However, only few visualization techniques exist for further exploring and understanding the clustering results. We propose visualization and interaction methods for analyzing individual clusters as well as cluster distribution within and across levels in the cluster hierarchy. We also provide a clustering method that operates on density rather than individual records. To not restrict our search for clusters, we compute density in the given multidimensional multivariate space. Clusters are formed by areas of high density. We present an approach that automatically computes a hierarchical tree of high density clusters. To visually represent the cluster hierarchy, we present a 2D radial layout that supports an intuitive understanding of the distribution structure of the multidimensional multivariate data set. Individual clusters can be explored interactively using parallel coordinates when being selected in the cluster tree. Furthermore, we integrate circular parallel coordinates into the radial hierarchical cluster tree layout, which allows for the analysis of the overall cluster distribution. This visual representation supports the comprehension of the relations between clusters and the original attributes. The combination of the 2D radial layout and the circular parallel coordinates is used to overcome the overplotting problem of parallel coordinates when looking into data sets with many records. We apply an automatic coloring scheme based on the 2D radial layout of the hierarchical cluster tree encoding hue, saturation, and value of the HSV color space. The colors support linking the 2D radial layout to other views such as the standard parallel coordinates or, in case data is obtained from multidimensional spatial data, the distribution in object space.     

Efficient and Adaptive Rendering of 2-D Continuous Scatterplots

We extend the rendering technique for continuous scatterplots to allow for a broad class of interpolation methods within the spatial grid instead of only linear interpolation. To do this, we propose an approach that projects the image of a cell from the spatial domain to the scatterplot domain. We approximate this image using either the convex hull or an axis-aligned rectangle that forms a tight fit of the projected points. In both cases, the approach relies on subdivision in the spatial domain to control the approximation error introduced in the scatterplot domain. Acceleration of this algorithm in homogeneous regions of the spatial domain is achieved using an octree hierarchy. The algorithm is scalable and adaptive since it allows us to balance computation time and scatterplot quality. We evaluate and discuss the results with respect to accuracy and computational speed. Our methods are applied to examples of 2-D transfer function design.     

Comprehensive Facial Performance Capture

We present a system for recording a live dynamic facial performance, capturing highly detailed geometry and spatially varying diffuse and specular reflectance information for each frame of the performance. The result is a reproduction of the performance that can be rendered from novel viewpoints and novel lighting conditions, achieving photorealistic integration into any virtual environment. Dynamic performances are captured directly, without the need for any template geometry or static geometry scans, and processing is completely automatic, requiring no human input or guidance. Our key contributions are a heuristic for estimating facial reflectance information from gradient illumination photographs, and a geometry optimization framework that maximizes a principled likelihood function combining multi‐view stereo correspondence and photometric stereo, using multi‐resolution belief propagation. The output of our system is a sequence of geometries and reflectance maps, suitable for rendering in off‐the‐shelf software. We show results from our system rendered under novel viewpoints and lighting conditions, and validate our results by demonstrating a close match to ground truth photographs.     

Visual Boosting in Pixel‐based Visualizations

Pixel‐based visualizations have become popular, because they are capable of displaying large amounts of data and at the same time provide many details. However, pixel‐based visualizations are only effective if the data set is not sparse and the data distribution not random. Single pixels – no matter if they are in an empty area or in the middle of a large area of differently colored pixels – are perceptually difficult to discern and may therefore easily be missed. Furthermore, trends and interesting passages may be camouflaged in the sea of details. In this paper we compare different approaches for visual boosting in pixel‐based visualizations. Several boosting techniques such as halos, background coloring, distortion, and hatching are discussed and assessed with respect to their effectiveness in boosting single pixels, trends, and interesting passages. Application examples from three different domains (document analysis, genome analysis, and geospatial analysis) show the general applicability of the techniques and the derived guidelines.     

Creating Fluid Animation from a Single Image using Video Database

We present a method for synthesizing fluid animation from a single image, using a fluid video database. The user inputs a target painting or photograph of a fluid scene along with its alpha matte that extracts the fluid region of interest in the scene. Our approach allows the user to generate a fluid animation from the input image and to enter a few additional commands about fluid orientation or speed. Employing the database of fluid examples, the core algorithm in our method then automatically assigns fluid videos for each part of the target image. Our method can therefore deal with various paintings and photographs of a river, waterfall, fire, and smoke. The resulting animations demonstrate that our method is more powerful and efficient than our prior work.     

Automatic Conversion of Mesh Animations into Skeleton-based Animations

Recently, it has become increasingly popular to represent animations not by means of a classical skeleton‐based model, but in the form of deforming mesh sequences. The reason for this new trend is that novel mesh deformation methods as well as new surface based scene capture techniques offer a great level of flexibility during animation creation. Unfortunately, the resulting scene representation is less compact than skeletal ones and there is not yet a rich toolbox available which enables easy post‐processing and modification of mesh animations. To bridge this gap between the mesh‐based and the skeletal paradigm, we propose a new method that automatically extracts a plausible kinematic skeleton, skeletal motion parameters, as well as surface skinning weights from arbitrary mesh animations. By this means, deforming mesh sequences can be fully‐automatically transformed into fullyrigged virtual subjects. The original input can then be quickly rendered based on the new compact bone and skin representation, and it can be easily modified using the full repertoire of already existing animation tools.