Line‐Drawing Video Stylization

We present a method to automatically convert videos and CG animations to stylized animated line drawings. Using a data‐driven approach, the animated drawings can follow the sketching style of a specific artist. Given an input video, we first extract edges from the video frames and vectorize them to curves. The curves are matched to strokes from an artist's library, while following the artist's stroke distribution and characteristics. The key challenge in this process is to match the large number of curves in the frames over time, despite topological and geometric changes, allowing to maintain temporal coherence in the output animation. We solve this problem using constrained optimization to build correspondences between tracked points and create smooth sheets over time. These sheets are then replaced with strokes from the artist's database to render the final animation. We evaluate our tracking algorithm on various examples and show stylized animation results based on various artists.     

A Flexible Approach for Output‐Sensitive Rendering of Animated Characters

Rendering detailed animated characters is a major limiting factor in crowd simulation. In this paper we present a new representation for 3D animated characters which supports output‐sensitive rendering. Our approach is flexible in the sense that it does not require us to pre‐define the animation sequences beforehand, nor to pre‐compute a dense set of pre‐rendered views for each animation frame. Each character is encoded through a small collection of textured boxes storing colour and depth values. At runtime, each box is animated according to the rigid transformation of its associated bone and a fragment shader is used to recover the original geometry using a dual‐depth version of relief mapping. Unlike competing output‐sensitive approaches, our compact representation is able to recover high‐frequency surface details and reproduces view‐motion parallax effectively. Our approach drastically reduces both the number of primitives being drawn and the number of bones influencing each primitive, at the expense of a very slight per‐fragment overhead. We show that, beyond a certain distance threshold, our compact representation is much faster to render than traditional level‐of‐detail triangle meshes. Our user study demonstrates that replacing polygonal geometry by our impostors produces negligible visual artefacts.     

Feature‐Aware Pixel Art Animation

Pixel art is a modern digital art in which high resolution images are abstracted into low resolution pixelated outputs using concise outlines and reduced color palettes. Creating pixel art is a labor intensive and skill‐demanding process due to the challenge of using limited pixels to represent complicated shapes. Not surprisingly, generating pixel art animation is even harder given the additional constraints imposed in the temporal domain. Although many powerful editors have been Designed to facilitate the creation of still pixel art images, the extension to pixel art animation remains an unexplored direction. Existing systems typically request users to craft individual pixels frame by frame, which is a tedious and error‐prone process. In this work, we present a novel animation framework tailored to pixel art images. Our system bases on conventional key‐frame animation framework and state‐of‐the‐art image warping techniques to generate an initial animation sequence. The system then jointly optimizes the prominent feature lines of individual frames respecting three metrics that capture the quality of the animation sequence in both spatial and temporal domains. We demonstrate our system by generating visually pleasing animations on a variety of pixel art images, which would otherwise be difficult by applying state‐of‐the‐art techniques due to severe artifacts.     

Efficient and Dynamic Simplification of Line Drawings

In this paper we present a pipeline for rendering dynamic 2D/3D line drawings efficiently. Our main goal is to create efficient static renditions and coherent animations of line drawings in a setting where lines can be added, deleted and arbitrarily transformed on‐the‐fly. Such a dynamic setting enables us to handle interactively sketched 2D line data, as well as arbitrarily transformed 3D line data in a unified manner. We evaluate the proximity of screen projected strokes to simplify them while preserving their continuity. We achieve this by using a special data structure that facilitates efficient proximity calculations in a dynamic setting. This on‐the‐fly proximity evaluation also facilitates generation of appropriate visibility cues to mitigate depth ambiguities and visual clutter for 3D line data. As we perform all these operations using only line data, we can create line drawings from 3D models without any surface information. We demonstrate the effectiveness and applicability of our approach by showing several examples with initial line representations obtained from a variety of sources: 2D and 3D hand‐drawn sketches and 3D salient geometry lines obtained from 3D surface representations.     

Reconstructing Animated Meshes from Time‐Varying Point Clouds

In this paper, we describe a novel approach for the reconstruction of animated meshes from a series of time‐deforming point clouds. Given a set of unordered point clouds that have been captured by a fast 3‐D scanner, our algorithm is able to compute coherent meshes which approximate the input data at arbitrary time instances. Our method is based on the computation of an implicit function in ?⁴ that approximates the time‐space surface of the time‐varying point cloud. We then use the four‐dimensional implicit function to reconstruct a polygonal model for the first time‐step. By sliding this template mesh along the time‐space surface in an as‐rigid‐as‐possible manner, we obtain reconstructions for further time‐steps which have the same connectivity as the previously extracted mesh while recovering rigid motion exactly. The resulting animated meshes allow accurate motion tracking of arbitrary points and are well suited for animation compression. We demonstrate the qualities of the proposed method by applying it to several data sets acquired by real‐time 3‐D scanners.     

Tensor Clustering for Rendering Many‐Light Animations

Rendering animations of scenes with deformable objects, camera motion, and complex illumination, including indirect lighting and arbitrary shading, is a long‐standing challenge. Prior work has shown that complex lighting can be accurately approximated by a large collection of point lights. In this formulation, rendering of animation sequences becomes the problem of efficiently shading many surface samples from many lights across several frames. This paper presents a tensor formulation of the animated many‐light problem, where each element of the tensor expresses the contribution of one light to one pixel in one frame. We sparsely sample rows and columns of the tensor, and introduce a clustering algorithm to select a small number of representative lights to efficiently approximate the animation. Our algorithm achieves efficiency by reusing representatives across frames, while minimizing temporal flicker. We demonstrate our algorithm in a variety of scenes that include deformable objects, complex illumination and arbitrary shading and show that a surprisingly small number of representative lights is sufficient for high quality rendering. We believe out algorithm will find practical use in applications that require fast previews of complex animation.     

3D Posture Reconstruction and Human Animation from 2D Feature Points

An optimal approach is proposed in this paper for posture reconstruction and human animation from 2D feature points extracted from the monocular images containing human motions. Biomechanical constraints are encoded in every joint of the adopted 3D skeletal human model to make sure that each state of the joints represents a physically valid posture. Size of the human model is adjusted to be consistent with the human figure represented by feature points. Energy Function is defined to represent the residuals between the extracted 2D feature points and the corresponding features resulted from projection of the 3D human model. Local Adjustment and Global Adjustment procedures are proposed to place the joints and body segments into proper locations and orientations in 3D space to create the posture with the minimum value of Energy Function. To find the optimal solution of the ill‐posed recovery problem from 2D to 3D, Genetic Algorithm is employed in the high‐dimensional parameter space by considering all the parameters simultaneously. Smooth and continuous changes between consecutive frames are considered in development of the human animation procedure. The proposed approach produces optimal reconstruction results of any possible human postures and movements. It is different from classical kinematics and dynamics formulations, and is an attempt to bridge the gap between computer vision and computer animation in human motion study.     

Hierarchical opacity optimization for sets of 3D line fields

The selection of meaningful lines for 3D line data visualization has been intensively researched in recent years. Most approaches focus on single line fields where one line passes through each domain point. This paper presents a selection approach for sets of line fields which is based on a global optimization of the opacity of candidate lines. For this, existing approaches for single line fields are modified such that significantly larger amounts of line representatives are handled. Furthermore, time coherence is addressed for animations, making this the first approach that solves the line selection problem for 3D time‐dependent flow. We apply our technique to visualize dense sets of pathlines, sets of magnetic field lines, and animated sets of pathlines, streaklines and masslines.     

Performance‐driven animation of hand‐drawn cartoon faces

We present a novel performance‐driven approach to animating cartoon faces starting from pure 2D drawings. A 3D approximate facial model automatically built from front and side view master frames of character drawings is introduced to enable the animated cartoon faces to be viewed from angles different from that in the input video. The expressive mappings are built by artificial neural network (ANN) trained from the examples of the real face in the video and the cartoon facial drawings in the facial expression graph for a specific character. The learned mapping model makes the resultant facial animation to properly get the desired expressiveness, instead of a mere reproduction of the facial actions in the input video sequence. Furthermore, the lit sphere, capturing the lighting in the painting artwork of faces, is utilized to color the cartoon faces in terms of the 3D approximate facial model, reinforcing the hand‐drawn appearance of the resulting facial animation. We made a series of comparative experiments to test the effectiveness of our method by recreating the facial expression in the commercial animation. The comparison results clearly demonstrate the superiority of our method not only in generating high quality cartoon‐style facial expressions, but also in speeding up the animation production of cartoon faces. Copyright © 2011 John Wiley & Sons, Ltd.     

T‐SAH: Animation Optimized Bounding Volume Hierarchies

We propose a method for creating a bounding volume hierarchy (BVH) that is optimized for all frames of a given animated scene. The method is based on a novel extension of surface area heuristic to temporal domain (T‐SAH). We perform iterative BVH optimization using T‐SAH and create a single BVH accounting for scene geometry distribution at different frames of the animation. Having a single optimized BVH for the whole animation makes our method extremely easy to integrate to any application using BVHs, limiting the per‐frame overhead only to refitting the bounding volumes. We evaluated the T‐SAH optimized BVHs in the scope of real‐time GPU ray tracing. We demonstrate, that our method can handle even highly complex inputs with large deformations and significant topology changes. The results show, that in a vast majority of tested scenes our method provides significantly better run‐time performance than traditional SAH and also better performance than GPU based per‐frame BVH rebuild.     

Stereo‐Consistent Contours in Object Space

Notebook scribbles, art or technical illustrations—line drawings are a simplistic method to visually communicate information. Automated line drawings often originate from virtual 3D models, but one cannot trivially experience their three‐dimensionality. This paper introduces a novel concept to produce stereo‐consistent line drawings of virtual 3D objects. Some contour lines do not only depend on an objects geometry, but also on the position of the observer. To accomplish consistency between multiple view positions, our approach exploits geometrical characteristics of 3D surfaces in object space. Established techniques for stereo‐consistent line drawings operate on rendered pixel images. In contrast, our pipeline operates in object space using vector geometry, which yields many advantages: The position of the final viewpoint(s) is flexible within a certain window even after the contour generation, e.g. a stereoscopic image pair is only one possible application. Such windows can be concatenated to simulate contours observed from an arbitrary camera path. Various types of popular contour generators can be handled equivalently, occlusions are natively supported and stylization based on geometry characteristics is also easily possible.     

Automatic expressive deformations for implying and stylizing motion

Three-dimensional computer animation often struggles to compete with the flexibility and expressiveness commonly found in traditional animation, particularly when rendered non-photorealistically. We present an animation tool that takes skeleton-driven 3D computer animations and generates expressive deformations to the character geometry. The technique is based upon the cartooning and animation concepts of “lines of action” and “lines of motion” and automatically infuses computer animations with some of the expressiveness displayed by traditional animation. Motion and pose-based expressive deformations are generated from the motion data and the character geometry is warped along each limb’s individual line of motion. The effect of this subtle, yet significant, warping is twofold: geometric inter-frame consistency is increased which helps create visually smoother animated sequences, and the warped geometry provides a novel solution to the problem of implied motion in non-photorealistic imagery. Object-space and image-space versions of the algorithm have been implemented and are presented.     

Path‐space Motion Estimation and Decomposition for Robust Animation Filtering

Renderings of animation sequences with physics‐based Monte Carlo light transport simulations are exceedingly costly to generate frame‐by‐frame, yet much of this computation is highly redundant due to the strong coherence in space, time and among samples. A promising approach pursued in prior work entails subsampling the sequence in space, time, and number of samples, followed by image‐based spatio‐temporal upsampling and denoising. These methods can provide significant performance gains, though major issues remain: firstly, in a multiple scattering simulation, the final pixel color is the composite of many different light transport phenomena, and this conflicting information causes artifacts in image‐based methods. Secondly, motion vectors are needed to establish correspondence between the pixels in different frames, but it is unclear how to obtain them for most kinds of light paths (e.g. an object seen through a curved glass panel). To reduce these ambiguities, we propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths. Each component is accompanied by motion vectors and other auxiliary features such as reflectance and surface normals. The motion vectors of specular paths are computed using a temporal extension of manifold exploration and the remaining components use a specialized variant of optical flow. Our experiments show that this decomposition leads to significant improvements in three image‐based applications: denoising, spatial upsampling, and temporal interpolation.     

Implicit Brushes for Stylized Line‐based Rendering

We introduce a new technique called Implicit Brushes to render animated 3D scenes with stylized lines in realtime with temporal coherence. An Implicit Brush is defined at a given pixel by the convolution of a brush footprint along a feature skeleton; the skeleton itself is obtained by locating surface features in the pixel neighborhood. Features are identified via image‐space fitting techniques that not only extract their location, but also their profile, which permits to distinguish between sharp and smooth features. Profile parameters are then mapped to stylistic parameters such as brush orientation, size or opacity to give rise to a wide range of line‐based styles.     

EXCOL: an EXtract-and-COmplete layering approach to cartoon animation reusing

We introduce the EXtract-and-COmplete Layering method (EXCOL)--a novel cartoon animation processing technique to convert a traditional animated cartoon video into multiple semantically meaningful layers. Our technique is inspired by vision-based layering techniques but focuses on shape cues in both the extraction and completion steps to reflect the unique characteristics of cartoon animation. For layer extraction, we define a novel similarity measure incorporating both shape and color of automatically segmented regions within individual frames and propagate a small set of user-specified layer labels among similar regions across frames. By clustering regions with the same labels, each frame is appropriately partitioned into different layers, with each layer containing semantically meaningful content. Then, a warping-based approach is used to fill missing parts caused by occlusion within the extracted layers to achieve a complete representation. EXCOL provides a flexible way to effectively reuse traditional cartoon animations with only a small amount of user interaction. It is demonstrated that our EXCOL method is effective and robust, and the layered representation benefits a variety of applications in cartoon animation processing.     

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.     

Efficient rendering of animated characters through optimized per‐joint impostors

In this paper, we present a new impostor‐based representation for 3D animated characters supporting real‐time rendering of thousands of agents. We maximize rendering performance by using a collection of pre‐computed impostors sampled from a discrete set of view directions. Our approach differs from previous work on view‐dependent impostors in that we use per‐joint rather than per‐character impostors. Our characters are animated by applying the joint rotations directly to the impostors, instead of choosing a single impostor for the whole character from a set of pre‐defined poses. This offers more flexibility in terms of animation clips, as our representation supports any arbitrary pose, and thus, the agent behavior is not constrained to a small collection of pre‐defined clips. Because our impostors are intended to be valid for any pose, a key issue is to define a proper boundary for each impostor to minimize image artifacts while animating the agents. We pose this problem as a variational optimization problem and provide an efficient algorithm for computing a discrete solution as a pre‐process. To the best of our knowledge, this is the first time a crowd rendering algorithm encompassing image‐based performance, small graphics processing unit footprint, and animation independence is proposed. Copyright © 2012 John Wiley & Sons, Ltd.     

Animation‐Aware Quadrangulation

Geometric meshes that model animated characters must be designed while taking into account the deformations that the shape will undergo during animation. We analyze an input sequence of meshes with point‐to‐point correspondence, and we automatically produce a quadrangular mesh that fits well the input animation. We first analyze the local deformation that the surface undergoes at each point, and we initialize a cross field that remains as aligned as possible to the principal directions of deformation throughout the sequence. We then smooth this cross field based on an energy that uses a weighted combination of the initial field and the local amount of stretch. Finally, we compute a field‐aligned quadrangulation with an off‐the‐shelf method. Our technique is fast and very simple to implement, and it significantly improves the quality of the output quad mesh and its suitability for character animation, compared to creating the quad mesh based on a single pose. We present experimental results and comparisons with a state‐of‐the‐art quadrangulation method, on both sequences from 3D scanning and synthetic sequences obtained by a rough animation of a triangulated model.     

Interactive Exploratory Visualization of 2D Vector Fields

In this paper we present several techniques to interactively explore representations of 2D vector fields. Through a set of simple hand postures used on large, touch‐sensitive displays, our approach allows individuals to custom‐design glyphs (arrows, lines, etc.) that best reveal patterns of the underlying dataset. Interactive exploration of vector fields is facilitated through freedom of glyph placement, glyph density control, and animation. The custom glyphs can be applied individually to probe specific areas of the data but can also be applied in groups to explore larger regions of a vector field. Re‐positionable sources from which glyphs—animated according to the local vector field—continue to emerge are used to examine the vector field dynamically. The combination of these techniques results in an engaging visualization with which the user can rapidly explore and analyze varying types of 2D vector fields, using a virtually infinite number of custom‐designed glyphs.