This survey reviews the use of computational topology in hand-drawn animation technology over the past 15 years. We discuss three main subfields of hand-drawn animation technology research: frame deformation, frame feature correspondence, and volumetric modeling of hand-drawn characters. We explore the various topological spaces and operators applied to each subfield, detailing the artistic and computational advantages and limitations of each topological approach. Throughout our discussion, we provide industry knowledge derived from interviews with leading hand-drawn animation professionals to enrich our assessments of topological approaches’ suitability in industry settings.

Via virtual reality (VR) and in 3D immersive virtual environments (IVEs), viewers can observe their surroundings in any direction. This unrestricted view challenges storytelling, as directors cannot control the viewer’s perspective. To overcome this, we propose to develop a system that enhances narrative focus by rendering only high-quality story-critical elements within an IVE. This approach ensures that viewers are guided to the intended view, maintaining the director’s vision while preserving the immersive experience of VR.

In this poster, we present work-in-progress research towards improving the spatial perception of 3D objects on Optical See-through Mixed Reality displays, addressing, in particular, visualizations comprising virtual objects embedded inside physical real-world objects. This use-case is common in visualization applications in medicine, engineering and geosciences, but is an added challenge in mixed reality (MR), where multiple modalities of data (real and virtual objects) essentially occupy the same 3D space leading to inevitable depth ambiguity. In this poster, we review several strategies for ameliorating this problem, discuss insights from preliminary implementations of such approaches and propose avenues for future work.

Lighting has been used to enhance emotion and appeal of characters for centuries, from paintings in the Renaissance to the modern-day digital arts. In VFX and animation studios, lighting is considered as important as modelling, shading, or rigging. Most existing work focuses on either empirical best-practice created by artists of the centuries or on lighting perception with basic shapes. In contrast, our work focuses on the effect of lighting on emotional characters. Our study presents an extensive set of novel perceptual experiments designed to investigate the effects of brightness levels (key light brightness) and the proportion of light intensity illuminating the two sides of a character’s face (key-to-fill ratio). We are particularly interested in the effect of lighting on the recognition of emotion, emotion intensity, and the overall appeal, as these are crucial factors for audience engagement. Our results have implications for artists and developers wishing to increase the appeal and emotional expression of their characters, ranging from cartoon to realistic styles. Our key finding is that lighting can be used to effectively alter the intensity of emotion of a character and that brighter conditions increased appeal across all of our experiments.

In this study, we propose an efficient approach for modelling and compressing large-scale datasets. The main idea is to subdivide each sample into smaller partitions where each partition constitutes a particular subset of attributes and then apply PCA to each partition separately. This simple approach enjoys several key advantages over the traditional holistic scheme in terms of reduced computational cost and enhanced reconstruction quality. We study two variants of this approach, namely, cell-based PCA for image datasets where samples are spatially divided into smaller blocks and the more general band-based PCA where attributes are partitioned based on their values distribution.

The design of lighting in Computer Graphics is directly derived from cinematography, and many digital artists follow the conventional wisdom on how lighting is set up to convey drama, appeal, or emotion. In this paper, we are interested in investigating the most commonly used lighting techniques to more formally determine their effect on our perception of animated virtual characters. Firstly, we commissioned a professional animator to create a sequence of dramatic emotional sentences for a typical CG cartoon character. Then, we rendered that character using a range of lighting directions, intensities, and shading techniques. Participants of our experiment rated the emotion, the intensity of the performance, and the appeal of the character. Our results provide new insights into how animated virtual characters are perceived, when viewed under different lighting conditions.

We present a novel algorithm to model density-dependent behaviours in crowd simulation. Previous work has shown that density is a key factor in governing how pedestrians adapt their behaviour. This paper specifically examines, through analysis of real pedestrian data, how density affects how agents control their rate of change of bearing angle with respect to one another. We extend upon existing synthetic vision based approaches to local collision avoidance and generate pedestrian trajectories that more faithfully represent how real people avoid each other. Our approach is capable of producing realistic human behaviours, particularly in dense, complex scenarios where the amount of time for agents to make decisions is limited.

Edges are one of the primary sources of clutter when viewing graphs as node-link diagrams. One technique to reduce this clutter is to bundle edges together based on a nearby source or destination. Combined with edge translucency, edge bundling is reported to reduce the clutter and reveal higher-level edge patterns. However there is very little empirical data on the impact of edge bundling on user performance, as well as the impact of graph characteristics such as edge density and graph size on the effectiveness of edge bundling as a graph-visualization technique. We have performed user experiments to evaluate the impact of bundling on user performance, using a set of randomly generated undirected compound graphs with varying vertex counts and edge densities. Our results indicate that edge bundling negatively impacts user performance at tracing paths between nodes, both in terms of accuracy and time. They also indicate that while edge bundling may provide no clear significant benefit in terms of accuracy for recognising higher-level cluster connectivity, it does provide a significant improvement in user response time.

Abstract This paper presents a novel interactive approach for adding depth information into hand‐drawn cartoon images and animations. In comparison to previous depth assignment techniques our solution requires minimal user effort and enables creation of consistent pop‐ups in a matter of seconds. Inspired by perceptual studies we formulate a custom tailored optimization framework that tries to mimic the way that a human reconstructs depth information from a single image. Its key advantage is that it completely avoids inputs requiring knowledge of absolute depth and instead uses a set of sparse depth (in)equalities that are much easier to specify. Since these constraints lead to a solution based on quadratic programming that is time consuming to evaluate we propose a simple approximative algorithm yielding similar results with much lower computational overhead. We demonstrate its usefulness in the context of a cartoon animation production pipeline including applications such as enhancement, registration, composition, 3D modelling and stereoscopic display.

Abstract We present a photon mapping technique capable of computing high quality global illumination at interactive frame rates. By extending the concept of photon differentials to efficiently handle diffuse reflections, we generate footprints at all photon hit points. These enable illumination reconstruction by density estimation with variable kernel bandwidths without having to locate the k nearest photon hits first. Adapting an efficient BVH construction process for ray tracing acceleration, we build photon maps that enable the fast retrieval of all hits relevant to a shading point. We present a heuristic that automatically tunes the BVH build's termination criterion to the scene and illumination conditions. As all stages of the algorithm are highly parallelizable, we demonstrate an implementation using NVidia's CUDA manycore architecture running at interactive rates on a single GPU. Both light source and camera may be freely moved with global illumination fully recalculated in each frame.

Abstract In this paper we presentLazyBrush, a novel interactive tool for painting hand‐made cartoon drawings and animations. Its key advantage is simplicity and flexibility. As opposed to previous custom tailored approaches [ SBv05 , QWH06 ]LazyBrushdoes not rely on style specific features such as homogenous regions or pattern continuity yet still offers comparable or even less manual effort for a broad class of drawing styles. In addition to this, it is not sensitive to imprecise placement of color strokes which makes painting less tedious and brings significant time savings in the context cartoon animation.LazyBrushoriginally stems from requirements analysis carried out with professional ink‐and‐paint illustrators who established a list of useful features for an ideal painting tool. We incorporate this list into an optimization framework leading to a variant of Potts energy with several interesting theoretical properties. We show how to minimize it efficiently and demonstrate its usefulness in various practical scenarios including the ink‐and‐paint production pipeline.

For many systems that produce physically based animations, plausibility rather than accuracy is acceptable. We consider the problem of evaluating the visual quality of animations in which physical parameters have been distorted or degraded, either unavoidably due to real-time frame-rate requirements, or intentionally for aesthetic reasons. To date, no generic means of evaluating or predicting the fidelity, either physical or visual, of the dynamic events occurring in an animation exists. As a first step towards providing such a metric, we present a set of psychophysical experiments that established some thresholds for human sensitivity to dynamic anomalies, including angular, momentum and spatio-temporal distortions applied to simple animations depicting the elastic collision of two rigid objects. In addition to finding significant acceptance thresholds for these distortions under varying conditions, we identified some interesting biases that indicate non-symmetric responses to these distortions (e.g., expansion of the angle between post-collision trajectories was preferred to contraction and increases in velocity were preferred to decreases). Based on these results, we derived a set of probability functions that can be used to evaluate the visual fidelity of a physically based simulation. To illustrate how our results could be used, two simple case studies of simulation levels of detail and constrained dynamics are presented.

Abstract Work on levels of detail for human simulation has occurred mainly on a geometrical level, either by reducing the numbers of polygons representing a virtual human, or replacing them with a two‐dimensional imposter. Approaches that reduce the complexity of motions generated have also been proposed. In this paper, we describe ongoing development of a framework for Adaptive Level Of Detail for Human Animation (ALOHA), which incorporates levels of detail for not only geometry and motion, but also includes a complexity gradient for natural behaviour, both conversational and social. ACM CSS: I.3.7 Three‐Dimensional Graphics and Realism—Animation

Level of Detail (LOD) techniques for real-time rendering and related perceptual issues have received a lot of attention in recent years. Researchers have also begun to look at the issue of perceptually adaptive techniques for plausible physical simulations. In this article, we are particularly interested in the problem of realistic collision simulation in scenes where large numbers of objects are colliding and processing must occur in real-time. An interruptible and therefore degradable collision-handling mechanism is used and the perceptual impact of this degradation is explored. We look for ways in which we can optimize the realism of such simulations and describe a series of psychophysical experiments that investigate different factors affecting collision perception, including eccentricity, separation, distractors, causality, and accuracy of physical response. Finally, strategies for incorporating these factors into a perceptually adaptive real-time simulation of large numbers of visually similar objects are presented.

Interactive simulation is made possible in many applications by simplifying or culling the finer details that would make real‐time performance impossible. This paper examines detail simplification in the specific problem of collision handling for rigid body animation. We present an automated method for calculating consistent collision response at different levels of detail. The mechanism works closely with a system which uses a pre‐computed hierarchical volume model for collision detection.