Object Repositioning Based on the Perspective in a Single Image

We propose an image editing system for repositioning objects in a single image based on the perspective of the scene. In our system, an input image is transformed into a layer structure that is composed of object layers and a background layer, and then the scene depth is computed from the ground region that is specified by the user using a simple boundary line. The object size and order of overlapping are automatically determined during the reposition based on the scene depth. In addition, our system enables the user to move shadows along with objects naturally by extracting the shadow mattes using only a few user‐specified scribbles. Finally, we demonstrate the versatility of our system through applications to depth‐of‐field effects, fog synthesis and 3D walkthrough in an image.     

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.     

Visual Analysis and Semantic Exploration of Urban LIDAR Change Detection

Many previous approaches to detecting urban change from LIDAR point clouds interpolate the points into rasters, perform pixel‐based image processing to detect changes, and produce 2D images as output. We present a method of LIDAR change detection that maintains accuracy by only using the raw, irregularly spaced LIDAR points, and extracts relevant changes as individual 3D models. We then utilize these models, alongside existing GIS data, within an interactive application that allows the chronological exploration of the changes to an urban environment. A three‐tiered level‐of‐detail system maintains a scale‐appropriate, legible visual representation across the entire range of view scales, from individual changes such as buildings and trees, to groups of changes such as new residential developments, deforestation, and construction sites, and finally to larger regions such as neighborhoods and districts of a city that are emerging or undergoing revitalization. Tools are provided to assist the visual analysis by urban planners and historians through semantic categorization and filtering of the changes presented.     

Defocus Magnification

A blurry background due to shallow depth of field is often desired for photographs such as portraits, but, unfortunately, small point-and-shoot cameras do not permit enough defocus because of the small diameter of their lenses. We present an image-processing technique that increases the defocus in an image to simulate the shallow depth of field of a lens with a larger aperture. Our technique estimates the spatially-varying amount of blur over the image, and then uses a simple image-based technique to increase defocus. We first estimate the size of the blur kernel at edges and then propagate this defocus measure over the image. Using our defocus map, we magnify the existing blurriness, which means that we blur blurry regions and keep sharp regions sharp. In contrast to more difficult problems such as depth from defocus, we do not require precise depth estimation and do not need to disambiguate textureless regions.     

Flow‐Based Automatic Generation of Hybrid Picture Mazes

A method for automatically generating a picture maze from two different images is introduced throughout this paper. The process begins with the extraction of salient contours and edge tangent flow information from the primary image in order to build the overall maze. Thus, mazes with passages flowing in the main edge directions and walls that effectively represent an abstract version of the primary image can be successfully created. Furthermore, our proposed approach makes possible the use of their solution path as a means of illustrating the main features of the secondary image, while attempting to keep its image motif concealed until the maze has been finally solved. The contour features and intensity of the secondary image are also incorporated into our method in order to determine the areas of the maze to be shaded by allowing the solution path to go through them. Moreover, an experiment has been conducted to confirm that solution paths can be successfully hidden from the participants in the mazes generated using our method.     

A Fast Simulation Method Using Overlapping Grids for Interactions between Smoke and Rigid Objects

Recently, many techniques using computational fluid dynamics have been proposed for the simulation of natural phenomena such as smoke and fire. Traditionally, a single grid is used for computing the motion of fluids. When an object interacts with a fluid, the resolution of the grid must be sufficiently high because the shape of the object is represented by a shape sampled at the grid points. This increases the number of grid points that are required, and hence the computational cost is increased. To address this problem, we propose a method using multiple grids that overlap with each other. In addition to a large single grid (a global grid) that covers the whole of the simulation space, separate grids (local grids) are generated that surround each object. The resolution of a local grid is higher than that of the global grid. The local grids move according to the motion of the objects. Therefore, the process of resampling the shape of the object is unnecessary when the object moves. To accelerate the computation, appropriate resolutions are adaptively‐determined for the local grids according to their distance from the viewpoint. Furthermore, since we use regular (orthogonal) lattices for the grids, the method is suitable for GPU implementation. This realizes the real‐time simulation of interactions between objects and smoke.     

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.     

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.     

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.     

Visualization and Analysis of Eddies in a Global Ocean Simulation

We present analysis and visualization of flow data from a high‐resolution simulation of the dynamical behavior of the global ocean. Of particular scientific interest are coherent vortical features called mesoscale eddies. We first extract high‐vorticity features using a metric from the oceanography community called the Okubo‐Weiss parameter. We then use a new circularity criterion to differentiate eddies from other non‐eddy features like meanders in strong background currents. From these data, we generate visualizations showing the three‐dimensional structure and distribution of ocean eddies. Additionally, the characteristics of each eddy are recorded to form an eddy census that can be used to investigate correlations among variables such as eddy thickness, depth, and location. From these analyses, we gain insight into the role eddies play in large‐scale ocean circulation.     

Embedded Implicit Stand-Ins for Animated Meshes: A Case of Hybrid Modelling

In this paper, we address shape modelling problems, encountered in computer animation and computer games development that are difficult to solve just using polygonal meshes. Our approach is based on a hybrid-modelling concept that combines polygonal meshes with implicit surfaces. A hybrid model consists of an animated polygonal mesh and an approximation of this mesh by a convolution surface stand-in that is embedded within it or is attached to it. The motions of both objects are synchronised using a rigging skeleton. We model the interaction between an animated mesh object and a viscoelastic substance, which is normally represented in an implicit form. Our approach is aimed at achieving verisimilitude rather than physically based simulation. The adhesive behaviour of the viscous object is modelled using geometric blending operations on the corresponding implicit surfaces. Another application of this approach is the creation of metamorphosing implicit surface parts that are attached to an animated mesh. A prototype implementation of the proposed approach and several examples of modelling and animation with near real-time preview times are presented.     

Dynamic Multi‐View Exploration of Shape Spaces

Statistical shape modeling is a widely used technique for the representation and analysis of the shapes and shape variations present in a population. A statistical shape model models the distribution in a high dimensional shape space, where each shape is represented by a single point. We present a design study on the intuitive exploration and visualization of shape spaces and shape models. Our approach focuses on the dual‐space nature of these spaces. The high‐dimensional shape space represents the population, whereas object space represents the shape of the 3D object associated with a point in shape space. A 3D object view provides local details for a single shape. The high dimensional points in shape space are visualized using a 2D scatter plot projection, the axes of which can be manipulated interactively. This results in a dynamic scatter plot, with the further extension that each point is visualized as a small version of the object shape that it represents. We further enhance the population‐object duality with a new type of view aimed at shape comparison. This new “shape evolution view” visualizes shape variability along a single trajectory in shape space, and serves as a link between the two spaces described above. Our three‐view exploration concept strongly emphasizes linked interaction between all spaces. Moving the cursor over the scatter plot or evolution views, shapes are dynamically interpolated and shown in the object view. Conversely, camera manipulation in the object view affects the object visualizations in the other views. We present a GPU‐accelerated implementation, and show the effectiveness of the three‐view approach using a number of real‐world cases. In these, we demonstrate how this multi‐view approach can be used to visually explore important aspects of a statistical shape model, including specificity, compactness and reconstruction error.     

Placement of Deformable Objects

With the increasing complexity of photorealistic scenes, the question of building and placing objects in three‐dimensional scenes is becoming ever more difficult. While the question of placement of rigid objects has captured the attention of researchers in the past, this work presents an intuitive and interactive scheme to properly place deformable objects with the aid of free‐form deformation tools. The presented scheme can also be used to animate the locomotion of nonrigid objects, most noticeably animals, and adapt the motion to arbitrary terrain. The automatic construction of our free‐form deformation tool is completely hidden from the end user, and hence, circumvents the difficulties typically faced in manipulating these deformation functions. Further, a precise bound on the error that is introduced by applying free‐form deformations to polygonal models is presented, along with an almost‐optimal adaptive refinement algorithm to achieve a certain accuracy in the mapping.     

Matting and Compositing for Fresnel Reflection on Wavy Surfaces

This paper introduces a framework that can extract an alpha matte from a single image with Fresnel reflection, and that can composite other objects with the image such that plausible reflections are included. Our method handles reflections in a plane with small undulations, for example, a water surface with waves or a glossy tabletop. During the matting stage, our method first estimates the transmission color, which is assumed to be uniform, and then calculates a reflection image and alpha matte based on user markups. However, accurate extraction of the matte becomes challenging when a plane has small undulations because these create perturbations in the matte. We therefore propose a filter that can refine the matte effectively. In the compositing stage, the reflection of a composited object is synthesized by ray tracing in real time. We demonstrate the effectiveness of our method through comparisons with ground‐truth data and results using natural images as inputs.     

High Performance GPU‐based Proximity Queries using Distance Fields

Proximity queries such as closest point computation and collision detection have many applications in computer graphics, including computer animation, physics‐based modelling, augmented and virtual reality. We present efficient algorithms for proximity queries between a closed rigid object and an arbitrary, possibly deformable, polygonal mesh. Using graphics hardware to densely sample the distance field of the rigid object over the arbitrary mesh, we compute minimal proximity and collision response information on the graphics processing unit (GPU) using blending and depth buffering, as well as parallel reduction techniques, thus minimizing the readback bottleneck. Although limited to image‐space resolution, our algorithm provides high and steady performance when compared with other similar algorithms. Proximity queries between arbitrary meshes with hundreds of thousands of triangles and detailed distance fields of rigid objects are computed in a few milliseconds at high‐sampling resolution, even in situations with large overlap.     

Creating and Preserving Vortical Details in SPH Fluid

We present a new method to create and preserve the turbulent details generated around moving objects in SPH fluid. In our approach, a high‐resolution overlapping grid is bounded to each object and translates with the object. The turbulence formation is modeled by resolving the local flow around objects using a hybrid SPH‐FLIP method. Then these vortical details are carried on SPH particles flowing through the local region and preserved in the global field in a synthetic way. Our method provides a physically plausible way to model the turbulent details around both rigid and deformable objects in SPH fluid, and can efficiently produce animations of complex gaseous phenomena with rich visual details.     

Enhancement of Bright Video Features for HDR Displays

To utilize the full potential of new high dynamic range (HDR) displays, a system for the enhancement of bright luminous objects in video sequences is proposed. The system classifies clipped (saturated) regions as lights, reflections or diffuse surfaces using a semi‐automatic classifier and then enhances each class of objects with respect to its relative brightness. The enhancement algorithm can significantly stretch the contrast of clipped regions while avoiding amplification of noise and contouring. We demonstrate that the enhanced video is strongly preferred to non‐enhanced video, and it compares favorably to other methods.     

Real‐Time Depth‐of‐Field Rendering Using Point Splatting on Per‐Pixel Layers

We present a real‐time method for rendering a depth‐of‐field effect based on the per‐pixel layered splatting where source pixels are scattered on one of the three layers of a destination pixel. In addition, the missing information behind foreground objects is filled with an additional image of the areas occluded by nearer objects. The method creates high‐quality depth‐of‐field results even in the presence of partial occlusion, without major artifacts often present in the previous real‐time methods. The method can also be applied to simulating defocused highlights. The entire framework is accelerated by GPU, enabling real‐time post‐processing for both off‐line and interactive applications.     

Visualizing Objects with Mirrors

We present an automatic camera and mirrors placement method for visualizing 3D scenes such that complete and nonredundant visibility is guaranteed, as well as highest image resolution. We provide algorithms and geometries for optimal object‐independent mirrors and viewpoint placement for all objects in a specific class. We also briefly consider object‐dependent algorithmic problems, where mirrors and viewpoints are positioned as a function of the object.     

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.