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.     

Dynamic Comics for Hierarchical Abstraction of 3D Animation Data

Image storyboards of films and videos are useful for quick browsing and automatic video processing. A common approach for producing image storyboards is to display a set of selected key‐frames in temporal order, which has been widely used for 2D video data. However, such an approach cannot be applied for 3D animation data because different information is revealed by changing parameters such as the viewing angle and the duration of the animation. Also, the interests of the viewer may be different from person to person. As a result, it is difficult to draw a single image that perfectly abstracts the entire 3D animation data. In this paper, we propose a system that allows users to interactively browse an animation and produce a comic sequence out of it. Each snapshot in the comic optimally visualizes a duration of the original animation, taking into account the geometry and motion of the characters and objects in the scene. This is achieved by a novel algorithm that automatically produces a hierarchy of snapshots from the input animation. Our user interface allows users to arrange the snapshots according to the complexity of the movements by the characters and objects, the duration of the animation and the page area to visualize the comic sequence. Our system is useful for quickly browsing through a large amount of animation data and semi‐automatically synthesizing a storyboard from a long sequence of animation.     

Example‐based Multiple Local Color Transfer by Strokes

This paper investigates a new approach for color transfer. Rather than transferring color from one image to another globally, we propose a system with a stroke‐based user interface to provide a direct indication mechanism. We further present a multiple local color transfer method. Through our system the user can easily enhance a defect (source) photo by referring to some other good quality (target) images by simply drawing some strokes. Then, the system will perform the multiple local color transfer automatically. The system consists of two major steps. First, the user draws some strokes on the source and target images to indicate corresponding regions and also the regions he or she wants to preserve. The regions to be preserved which will be masked out based on an improved graph cuts algorithm. Second, a multiple local color transfer method is presented to transfer the color from the target image(s) to the source image through gradient‐guided pixel‐wise color transfer functions. Finally, the defect (source) image can be enhanced seamlessly by multiple local color transfer based on some good quality (target) examples through an interactive and intuitive stroke‐based user interface.     

Context-Aware Skeletal Shape Deformation

We describe a system for the animation of a skeleton-controlled articulated object that preserves the fine geometric details of the object skin and conforms to the characteristic shapes of the object specified through a set of examples. The system provides the animator with an intuitive user interface and produces compelling results even when presented with a very small set of examples. In addition it is able to generalize well by extrapolating far beyond the examples.     

SDViz: A Context-Preserving Interactive Visualization System for Technical Diagrams

When performing daily maintenance and repair tasks, technicians require access to a variety of technical diagrams. As technicians trace components and diagrams from page-to-page, within and across manuals, the contextual information of the components they are analyzing can easily be lost. To overcome these issues, we have developed a Schematic Diagram Visualization System (SDViz) designed for maintaining and highlighting contextual information in technical documents, such as schematic and wiring diagrams. Our system incorporates various features to aid in the navigation and diagnosis of faults, as well as maintaining contextual information when tracing components/connections through multiple diagrams. System features include highlighting relationships between components and connectors, diagram annotation tools, the animation of flow through the system, a novel contextual blending method, and a variety of traditional focus+context visualization techniques. We have evaluated the usefulness of our system through a qualitative user study in which subjects utilized our system in diagnosing faults during a standard aircraft maintenance exercise.     

ScribbleBoost: Adding Classification to Edge‐Aware Interpolation of Local Image and Video Adjustments

One of the most common tasks in image and video editing is the local adjustment of various properties (e.g., saturation or brightness) of regions within an image or video. Edge‐aware interpolation of user‐drawn scribbles offers a less effort‐intensive approach to this problem than traditional region selection and matting. However, the technique suffers a number of limitations, such as reduced performance in the presence of texture contrast, and the inability to handle fragmented appearances. We significantly improve the performance of edge‐aware interpolation for this problem by adding a boosting‐based classification step that learns to discriminate between the appearance of scribbled pixels. We show that this novel data term in combination with an existing edge‐aware optimization technique achieves substantially better results for the local image and video adjustment problem than edge‐aware interpolation techniques without classification, or related methods such as matting techniques or graph cut segmentation.     

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.     

An Example-based Procedural System for Element Arrangement

We present a method for synthesizing two dimensional (2D) element arrangements from an example. The main idea is to combine texture synthesis techniques based‐on a local neighborhood comparison and procedural modeling systems based‐on local growth. Given a user‐specified reference pattern, our system analyzes neigh‐borhood information of each element by constructing connectivity. Our synthesis process starts with a single seed and progressively places elements one by one by searching a reference element which has local features that are the most similar to the target place of the synthesized pattern. To support creative design activities, we introduce three types of interaction for controlling global features of the resulting pattern, namely a spray tool, a flow field tool, and a boundary tool. We also introduce a global optimization process that helps to avoid local error concentrations. We illustrate the feasibility of our method by creating several types of 2D patterns.     

Layered Performance Animation with Correlation Maps

Performance has a spontaneity and “aliveness” that can be difficult to capture in more methodical animation processes such as keyframing. Access to performance animation has traditionally been limited to either low degree of freedom characters or required expensive hardware. We present a performance-based animation system for humanoid characters that requires no special hardware, relying only on mouse and keyboard input. We deal with the problem of controlling such a high degree of freedom model with low degree of freedom input through the use of correlation maps which employ 2D mouse input to modify a set of expressively relevant character parameters. Control can be continuously varied by rapidly switching between these maps. We present flexible techniques for varying and combining these maps and a simple process for defining them. The tool is highly configurable, presenting suitable defaults for novices and supporting a high degree of customization and control for experts. Animation can be recorded on a single pass, or multiple layers can be used to increase detail. Results from a user study indicate that novices are able to produce reasonable animations within their first hour of using the system. We also show more complicated results for walking and a standing character that gestures and dances.     

Physically Based Video Editing

Convincing manipulation of objects in live action videos is a difficult and often tedious task. Skilled video editors achieve this with the help of modern professional tools, but complex motions might still lack physical realism since existing tools do not consider the laws of physics. On the other hand, physically based simulation promises a high degree of realism, but typically creates a virtual 3D scene animation rather than returning an edited version of an input live action video. We propose a framework that combines video editing and physics‐based simulation. Our tool assists unskilled users in editing an input image or video while respecting the laws of physics and also leveraging the image content. We first fit a physically based simulation that approximates the object's motion in the input video. We then allow the user to edit the physical parameters of the object, generating a new physical behavior for it. The core of our work is the formulation of an image‐aware constraint within physics simulations. This constraint manifests as external control forces to guide the object in a way that encourages proper texturing at every frame, yet producing physically plausible motions. We demonstrate the generality of our method on a variety of physical interactions: rigid motion, multi‐body collisions, clothes and elastic bodies.     

Real‐time Realistic Ocean Lighting using Seamless Transitions from Geometry to BRDF

Realistic animation and rendering of the ocean is an important aspect for simulators, movies and video games. By nature, the ocean is a difficult problem for Computer Graphics: it is a dynamic system, it combines wave trains at all scales, ranging from kilometric to millimetric. Worse, the ocean is usually viewed at several distances, from very close to the viewpoint to the horizon, increasing the multi‐scale issue, and resulting in aliasing problems. The illumination comes from natural light sources (the Sun and the sky dome), is also dynamic, and often underlines the aliasing issues. In this paper, we present a new algorithm for modelling, animation, illumination and rendering of the ocean, in real‐time, at all scales and for all viewing distances. Our algorithm is based on a hierarchical representation, combining geometry, normals and BRDF. For each viewing distance, we compute a simplified version of the geometry, and encode the missing details into the normal and the BRDF, depending on the level of detail required. We then use this hierarchical representation for illumination and rendering. Our algorithm runs in real‐time, and produces highly realistic pictures and animations.     

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.     

Capturing Intention‐based Full‐Frame Video Stabilization

Annoying shaky motion is one of the significant problems in home videos, since hand shake is an unavoidable effect when capturing by using a hand‐held camcorder. Video stabilization is an important technique to solve this problem, but the stabilized videos resulting from some current methods usually have decreased resolution and are still not so stable. In this paper, we propose a robust and practical method of full‐frame video stabilization while considering user's capturing intention to remove not only the high frequency shaky motions but also the low frequency unexpected movements. To guess the user's capturing intention, we first consider the regions of interest in the video to estimate which regions or objects the user wants to capture, and then use a polyline to estimate a new stable camcorder motion path while avoiding the user's interested regions or objects being cut out. Then, we fill the dynamic and static missing areas caused by frame alignment from other frames to keep the same resolution and quality as the original video. Furthermore, we smooth the discontinuous regions by using a three‐dimensional Poisson‐based method. After the above automatic operations, a full‐frame stabilized video can be achieved and the important regions and objects can also be preserved.     

SoundRiver: Semantically‐Rich Sound Illustration

Sound is an integral part of most movies and videos. In many situations, viewers of a video are unable to hear the sound track, for example, when watching it in a fast forward mode, viewing it by hearing‐impaired viewers or when the plot is given as a storyboard. In this paper, we present an automated visualization solution to such problems. The system first detects the common components (such as music, speech, rain, explosions, and so on) from a sound track, then maps them to a collection of programmable visual metaphors, and generates a composite visualization. This form of sound visualization, which is referred to as SoundRiver, can be also used to augment various forms of video abstraction and annotated key frames and to enhance graphical user interfaces for video handling software. The SoundRiver conveys more semantic information to the viewer than traditional graphical representations of sound illustration, such as phonoautographs, spectrograms or artistic audiovisual animations.     

A Phase‐Based Approach for Animating Images Using Video Examples

We present a novel approach for animating static images that contain objects that move in a subtle, stochastic fashion (e.g. rippling water, swaying trees, or flickering candles). To do this, our algorithm leverages example videos of similar objects, supplied by the user. Unlike previous approaches which estimate motion fields in the example video to transfer motion into the image, a process which is brittle and produces artefacts, we propose an Eulerian phase‐based approach which uses the phase information from the sample video to animate the static image. As is well known, phase variations in a signal relate naturally to the displacement of the signal via the Fourier Shift Theorem. To enable local and spatially varying motion analysis, we analyse phase changes in a complex steerable pyramid of the example video. These phase changes are then transferred to the corresponding spatial sub‐bands of the input image to animate it. We demonstrate that this simple, phase‐based approach for transferring small motion is more effective at animating still images than methods which rely on optical flow.     

Sketching MLS Image Deformations On the GPU

In this paper, we present an image editing tool that allows the user to deform images using a sketch‐based interface. The user simply sketches a set of source curves in the input image, and also some target curves that the source curves should be deformed to. Then the moving least squares (MLS) deformation technique [ [SMW06] ] is adapted to produce realistic deformations while satisfying the curves' positional constraints. We also propose a scheme to reduce image fold‐overs in MLS deformations. Our system has a very intuitive user interface, generates physically plausible deformations, and can be easily implemented on the GPU for real‐time performance.     

Online Motion Capture Marker Labeling for Multiple Interacting Articulated Targets

In this paper, we propose an online motion capture marker labeling approach for multiple interacting articulated targets. Given hundreds of unlabeled motion capture markers from multiple articulated targets that are interacting each other, our approach automatically labels these markers frame by frame, by fitting rigid bodies and exploiting trained structure and motion models. Advantages of our approach include: 1) our method is an online algorithm, which requires no user interaction once the algorithm starts. 2) Our method is more robust than traditional the closest point-based approaches by automatically imposing the structure and motion models. 3) Due to the use of the structure model which encodes the rigidity of each articulated body of captured targets, our method can recover missing markers robustly. Our approach is efficient and particularly suited for online computer animation and video game applications.     

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.     

BetweenIT: An Interactive Tool for Tight Inbetweening

The generation of inbetween frames that interpolate a given set of key frames is a major component in the production of a 2D feature animation. Our objective is to considerably reduce the cost of the inbetweening phase by offering an intuitive and effective interactive environment that automates inbetweening when possible while allowing the artist to guide, complement, or override the results. Tight inbetweens, which interpolate similar key frames, are particularly time‐consuming and tedious to draw. Therefore, we focus on automating these high‐precision and expensive portions of the process. We have designed a set of user‐guided semi‐automatic techniques that fit well with current practice and minimize the number of required artist‐gestures. We present a novel technique for stroke interpolation from only two keys which combines a stroke motion constructed from logarithmic spiral vertex trajectories with a stroke deformation based on curvature averaging and twisting warps. We discuss our system in the context of a feature animation production environment and evaluate our approach with real production data.     

Stylized Caustics: Progressive Rendering of Animated Caustics

In recent years, much work was devoted to the design of light editing methods such as relighting and light path editing. So far, little work addressed the target‐based manipulation and animation of caustics, for instance to a differently‐shaped caustic, text or an image. The aim of this work is the animation of caustics by blending towards a given target irradiance distribution. This enables an artist to coherently change appearance and style of caustics, e.g., for marketing applications and visual effects. Generating a smooth animation is nontrivial, as photon density and caustic structure may change significantly. Our method is based on the efficient solution of a discrete assignment problem that incorporates constraints appropriate to make intermediate blends plausibly resemble caustics. The algorithm generates temporally coherent results that are rendered with stochastic progressive photon mapping. We demonstrate our system in a number of scenes and show blends as well as a key frame animation.