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.     

Reinterpretable Imager: Towards Variable Post‐Capture Space,Angle and Time Resolution in Photography

We describe a novel multiplexing approach to achieve tradeoffs in space, angle and time resolution in photography. We explore the problem of mapping useful subsets of time‐varying 4D lightfields in a single snapshot. Our design is based on using a dynamic mask in the aperture and a static mask close to the sensor. The key idea is to exploit scene‐specific redundancy along spatial, angular and temporal dimensions and to provide a programmable or variable resolution tradeoff among these dimensions. This allows a user to reinterpret the single captured photo as either a high spatial resolution image, a refocusable image stack or a video for different parts of the scene in post‐processing. A lightfield camera or a video camera forces a‐priori choice in space‐angle‐time resolution. We demonstrate a single prototype which provides flexible post‐capture abilities not possible using either a single‐shot lightfield camera or a multi‐frame video camera. We show several novel results including digital refocusing on objects moving in depth and capturing multiple facial expressions in a single photo.     

Adaptive Image‐Space Sampling for Gaze‐Contingent Real‐time Rendering

With ever‐increasing display resolution for wide field‐of‐view displays—such as head‐mounted displays or 8k projectors—shading has become the major computational cost in rasterization. To reduce computational effort, we propose an algorithm that only shades visible features of the image while cost‐effectively interpolating the remaining features without affecting perceived quality. In contrast to previous approaches we do not only simulate acuity falloff but also introduce a sampling scheme that incorporates multiple aspects of the human visual system: acuity, eye motion, contrast (stemming from geometry, material or lighting properties), and brightness adaptation. Our sampling scheme is incorporated into a deferred shading pipeline to shade the image's perceptually relevant fragments while a pull‐push algorithm interpolates the radiance for the rest of the image. Our approach does not impose any restrictions on the performed shading. We conduct a number of psycho‐visual experiments to validate scene‐ and task‐independence of our approach. The number of fragments that need to be shaded is reduced by 50 % to 80 %. Our algorithm scales favorably with increasing resolution and field‐of‐view, rendering it well‐suited for head‐mounted displays and wide‐field‐of‐view projection.     

Efficient Multi‐image Correspondences for On‐line Light Field Video Processing

Light field videos express the entire visual information of an animated scene, but their shear size typically makes capture, processing and display an off‐line process, i. e., time between initial capture and final display is far from real‐time. In this paper we propose a solution for one of the key bottlenecks in such a processing pipeline, which is a reliable depth reconstruction possibly for many views. This is enabled by a novel correspondence algorithm converting the video streams from a sparse array of off‐the‐shelf cameras into an array of animated depth maps. The algorithm is based on a generalization of the classic multi‐resolution Lucas‐Kanade correspondence algorithm from a pair of images to an entire array. Special inter‐image confidence consolidation allows recovery from unreliable matching in some locations and some views. It can be implemented efficiently in massively parallel hardware, allowing for interactive computations. The resulting depth quality as well as the computation performance compares favorably to other state‐of‐the art light field‐to‐depth approaches, as well as stereo matching techniques. Another outcome of this work is a data set of light field videos that are captured with multiple variants of sparse camera arrays.     

Silhouette‐Aware Warping for Image‐Based Rendering

Image‐based rendering (IBR) techniques allow capture and display of 3D environments using photographs. Modern IBR pipelines reconstruct proxy geometry using multi‐view stereo, reproject the photographs onto the proxy and blend them to create novel views. The success of these methods depends on accurate 3D proxies, which are difficult to obtain for complex objects such as trees and cars. Large number of input images do not improve reconstruction proportionally; surface extraction is challenging even from dense range scans for scenes containing such objects. Our approach does not depend on dense accurate geometric reconstruction; instead we compensate for sparse 3D information by variational image warping. In particular, we formulate silhouette‐aware warps that preserve salient depth discontinuities. This improves the rendering of difficult foreground objects, even when deviating from view interpolation. We use a semi‐automatic step to identify depth discontinuities and extract a sparse set of depth constraints used to guide the warp. Our framework is lightweight and results in good quality IBR for previously challenging environments.     

A Single Image Representation Model for Efficient Stereoscopic Image Creation

Computer graphics is one of the most efficient ways to create a stereoscopic image. The process of stereoscopic CG generation is, however, still very inefficient compared to that of monoscopic CG generation. Despite that stereo images are very similar to each other, they are rendered and manipulated independently. Additional requirements for disparity control specific to stereo images lead to even greater inefficiency. This paper proposes a method to reduce the inefficiency accompanied in the creation of a stereoscopic image. The system automatically generates an optimized single image representation of the entire visible area from both cameras. The single image can be easily manipulated with conventional techniques, as it is spatially smooth and maintains the original shapes of scene objects. In addition, a stereo image pair can be easily generated with an arbitrary disparity setting. These convenient and efficient features are achieved by the automatic generation of a stereo camera pair, robust occlusion detection with a pair of Z‐buffers, an optimization method for spatial smoothness, and stereo image pair generation with a non‐linear disparity adjustment. Experiments show that our technique dramatically improves the efficiency of stereoscopic image creation while preserving the quality of the results.     

An Intuitive Interface for Interactive High Quality Image‐Based Modeling

We present the design of an interactive image‐based modeling tool that enables a user to quickly generate detailed 3D models with texture from a set of calibrated input images. Our main contribution is an intuitive user interface that is entirely based on simple 2D painting operations and does not require any technical expertise by the user or difficult pre‐processing of the input images. One central component of our tool is a GPU‐based multi‐view stereo reconstruction scheme, which is implemented by an incremental algorithm, that runs in the background during user interaction so that the user does not notice any significant response delay.     

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.     

Exposure Fusion for Time‐Of‐Flight Imaging

This work deals with the problem of automatically choosing the correct exposure (or integration) time for time‐of‐flight depth image capturing. We apply methods known from high dynamic range imaging to combine depth images taken with differing integration times in order to produce high quality depth maps. We evaluate the quality of these depth maps by comparing the performance in reconstruction of planar textured patches and in the 3D reconstruction of an indoor scene. Our solution is fast enough to capture the images at interactive frame rates and also flexible to deal with any amount of exposures.     

Crack‐free rendering of dynamically tesselated B‐rep models

We propose a versatile pipeline to render B‐Rep models interactively, precisely and without rendering‐related artifacts such as cracks. Our rendering method is based on dynamic surface evaluation using both tesselation and ray‐casting, and direct GPU surface trimming. An initial rendering of the scene is performed using dynamic tesselation. The algorithm we propose reliably detects then fills up cracks in the rendered image. Crack detection works in image space, using depth information, while crack‐filling is either achieved in image space using a simple classification process, or performed in object space through selective ray‐casting. The crack filling method can be dynamically changed at runtime. Our image space crack filling approach has a limited runtime cost and enables high quality, real‐time navigation. Our higher quality, object space approach results in a rendering of similar quality than full‐scene ray‐casting, but is 2 to 6 times faster, can be used during navigation and provides accurate, reliable rendering. Integration of our work with existing tesselation‐based rendering engines is straightforward.     

Turning a Digital Camera into an Absolute 2D Tele‐Colorimeter

We present a simple and effective technique for absolute colorimetric camera characterization, invariant to changes in exposure/aperture and scene irradiance, suitable in a wide range of applications including image‐based reflectance measurements, spectral pre‐filtering and spectral upsampling for rendering, to improve colour accuracy in high dynamic range imaging. Our method requires a limited number of acquisitions, an off‐the‐shelf target and a commonly available projector, used as a controllable light source, other than the reflected radiance to be known. The characterized camera can be effectively used as a 2D tele‐colorimeter, providing the user with an accurate estimate of the distribution of luminance and chromaticity in a scene, without requiring explicit knowledge of the incident lighting power spectra. We validate the approach by comparing our estimated absolute tristimulus values (XYZ data in ) with the measurements of a professional 2D tele‐colorimeter, for a set of scenes with complex geometry, spatially varying reflectance and light sources with very different spectral power distribution.     

Interactive Pixel‐Accurate Free Viewpoint Rendering from Images with Silhouette Aware Sampling

We present an integrated, fully GPU‐based processing pipeline to interactively render new views of arbitrary scenes from calibrated but otherwise unstructured input views. In a two‐step procedure, our method first generates for each input view a dense proxy of the scene using a new multi‐view stereo formulation. Each scene proxy consists of a structured cloud of feature aware particles which automatically have their image space footprints aligned to depth discontinuities of the scene geometry and hence effectively handle sharp object boundaries and occlusions. We propose a particle optimization routine combined with a special parameterization of the view space that enables an efficient proxy generation as well as robust and intuitive filter operators for noise and outlier removal. Moreover, our generic proxy generation allows us to flexibly handle scene complexities ranging from small objects up to complete outdoor scenes. The second phase of the algorithm combines these particle clouds in real‐time into a view‐dependent proxy for the desired output view and performs a pixel‐accurate accumulation of the colour contributions from each available input view. This makes it possible to reconstruct even fine‐scale view‐dependent illumination effects. We demonstrate how all these processing stages of the pipeline can be implemented entirely on the GPU with memory efficient, scalable data structures for maximum performance. This allows us to generate new output renderings of high visual quality from input images in real‐time.     

Radiometric Transfer: Example‐based Radiometric Linearization of Photographs

We present an example‐based approach for radiometrically linearizing photographs that takes as input a radiometrically linear exemplar image and a target regular uncalibrated image of the same scene, possibly from a different viewpoint and/or under different lighting. The output of our method is a radiometrically linearized version of the target image. Modeling the change in appearance of a small image patch seen from a different viewpoint and/or under different lighting as a linear 1D subspace, allows us to recast radiometric transfer in a form similar to classic radiometric calibration from exposure stacks. The resulting radiometric transfer method is lightweight and easy to implement. We demonstrate the accuracy and validity of our method on a variety of scenes.     

Panorama light‐field imaging

We present a novel approach to recording and computing panorama light fields. In contrast to previous methods that estimate panorama light fields from focal stacks or naive multi‐perspective image stitching, our approach is the first that processes ray entries directly and does not require depth reconstruction or matching of image features. Arbitrarily complex scenes can therefore be captured while preserving correct occlusion boundaries, anisotropic reflections, refractions, and other light effects that go beyond diffuse reflections of Lambertian surfaces.     

Registration Based Non‐uniform Motion Deblurring

This paper proposes an algorithm which uses image registration to estimate a non‐uniform motion blur point spread function (PSF) caused by camera shake. Our study is based on a motion blur model which models blur effects of camera shakes using a set of planar perspective projections (i.e., homographies). This representation can fully describe motions of camera shakes in 3D which cause non‐uniform motion blurs. We transform the non‐uniform PSF estimation problem into a set of image registration problems which estimate homographies of the motion blur model one‐by‐one through the Lucas‐Kanade algorithm. We demonstrate the performance of our algorithm using both synthetic and real world examples. We also discuss the effectiveness and limitations of our algorithm for non‐uniform deblurring.     

Content‐Independent Multi‐Spectral Display Using Superimposed Projections

Many works focus on multi‐spectral capture and analysis, but multi‐spectral display still remains a challenge. Most prior works on multi‐primary displays use ad‐hoc narrow band primaries that assure a larger color gamut, but cannot assure a good spectral reproduction. Content‐dependent spectral analysis is the only way to produce good spectral reproduction, but cannot be applied to general data sets. Wide primaries are better suited for assuring good spectral reproduction due to greater coverage of the spectral range, but have not been explored much. In this paper we explore the use of wide band primaries for accurate spectral reproduction for the first time and present the first content‐independent multi‐spectral display achieved using superimposed projections with modified wide band primaries. We present a content‐independent primary selection method that selects a small set of n primaries from a large set of m candidate primaries where m > n. Our primary selection method chooses primaries with complete coverage of the range of visible wavelength (for good spectral reproduction accuracy), low interdependency (to limit the primaries to a small number) and higher light throughput (for higher light efficiency). Once the primaries are selected, the input values of the different primary channels to generate a desired spectrum are computed using an optimization method that minimizes spectral mismatch while maximizing visual quality. We implement a real prototype of multi‐spectral display consisting of 9‐primaries using three modified conventional 3‐primary projectors, and compare it with a conventional display to demonstrate its superior performance. Experiments show our display is capable of providing large gamut assuring a good visual appearance while displaying any multi‐spectral images at a high spectral accuracy.     

Digital Camouflage Images Using Two‐scale Decomposition

We present an alternative approach to create digital camouflage images which follows human's perception intuition and complies with the physical creation procedure of artists. Our method is based on a two‐scale decomposition scheme of the input images. We modify the large‐scale layer of the background image by considering structural importance based on energy optimization and the detail layer by controlling its spatial variation. A gradient correction is presented to prevent halo artifacts. Users can control the difficulty level of perceiving the camouflage effect through a few parameters. Our camouflage images are natural and have less long coherent edges in the hidden region. Experimental results show that our algorithm yields visually pleasing camouflage images.     

Video Panorama for 2D to 3D Conversion

Accurate depth estimation is a challenging, yet essential step in the conversion of a 2D image sequence to a 3D stereo sequence. We present a novel approach to construct a temporally coherent depth map for each image in a sequence. The quality of the estimated depth is high enough for the purpose of2D to 3D stereo conversion. Our approach first combines the video sequence into a panoramic image. A user can scribble on this single panoramic image to specify depth information. The depth is then propagated to the remainder of the panoramic image. This depth map is then remapped to the original sequence and used as the initial guess for each individual depth map in the sequence. Our approach greatly simplifies the required user interaction during the assignment of the depth and allows for relatively free camera movement during the generation of a panoramic image. We demonstrate the effectiveness of our method by showing stereo converted sequences with various camera motions.     

Evaluation of Tone‐Mapping Operators for HDR Video Under Different Ambient Luminance Levels

Since high dynamic range (HDR) displays are not yet widely available, there is still a need to perform a dynamic range reduction of HDR content to reproduce it properly on standard dynamic range (SDR) displays. The most common techniques for performing this reduction are termed tone‐mapping operators (TMOs). Although mobile devices are becoming widespread, methods for displaying HDR content on these SDR screens are still very much in their infancy. While several studies have been conducted to evaluate TMOs, few have been done with a goal of testing small screen displays (SSDs), common on mobile devices. This paper presents an evaluation of six state‐of‐the‐art HDR video TMOs. The experiments considered three different levels of ambient luminance under which 180 participants were asked to rank the TMOs for seven tone‐mapped HDR video sequences. A comparison was conducted between tone‐mapped HDR video footage shown on an SSD and on a large screen SDR display using an HDR display as reference. The results show that there are differences between the performance of the TMOs under different ambient lighting levels and the TMOs that perform well on traditional large screen displays also perform well on SSDs at the same given luminance level.     

Color Me Noisy: Example‐based Rendering of Hand‐colored Animations with Temporal Noise Control

We present an example‐based approach to rendering hand‐colored animations which delivers visual richness comparable to real artwork while enabling control over the amount of perceived temporal noise. This is important both for artistic purposes and viewing comfort, but is tedious or even intractable to achieve manually. We analyse typical features of real hand‐colored animations and propose an algorithm that tries to mimic them using only static examples of drawing media. We apply the algorithm to various animations using different drawing media and compare the quality of synthetic results with real artwork. To verify our method perceptually, we conducted experiments confirming that our method delivers distinguishable noise levels and reduces eye strain. Finally, we demonstrate the capabilities of our method to mask imperfections such as shower‐door artifacts.