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Fast and deep deformation approximations
Character rigs are procedural systems that compute the shape of an animated character for a given pose. They can be highly complex and must account for bulges, wrinkles, and other aspects of a character's appearance. When comparing film-quality character rigs with those designed for real-time applications, there is typically a substantial and readily apparent difference in the quality of the mesh deformations. Real-time rigs are limited by a computational budget and often trade realism for performance. Rigs for film do not have this same limitation, and character riggers can make the rig as complicated as necessary to achieve realistic deformations. However, increasing the rig complexity slows rig evaluation, and the animators working with it can become less efficient and may experience frustration. In this paper, we present a method to reduce the time required to compute mesh deformations for film-quality rigs, allowing better interactivity during animation authoring and use in real-time games and applications. Our approach learns the deformations from an existing rig by splitting the mesh deformation into linear and nonlinear portions. The linear deformations are computed directly from the transformations of the rig's underlying skeleton. We use deep learning methods to approximate the remaining nonlinear portion. In the examples we show from production rigs used to animate lead characters, our approach reduces the computational time spent on evaluating deformations by a factor of 5Ă-10Ă. This significant savings allows us to run the complex, film-quality rigs in real-time even when using a CPU-only implementation on a mobile device
A survey of real-time crowd rendering
In this survey we review, classify and compare existing approaches for real-time crowd rendering. We first overview character animation techniques, as they are highly tied to crowd rendering performance, and then we analyze the state of the art in crowd rendering. We discuss different representations for level-of-detail (LoD) rendering of animated characters, including polygon-based, point-based, and image-based techniques, and review different criteria for runtime LoD selection. Besides LoD approaches, we review classic acceleration schemes, such as frustum culling and occlusion culling, and describe how they can be adapted to handle crowds of animated characters. We also discuss specific acceleration techniques for crowd rendering, such as primitive pseudo-instancing, palette skinning, and dynamic key-pose caching, which benefit from current graphics hardware. We also address other factors affecting performance and realism of crowds such as lighting, shadowing, clothing and variability. Finally we provide an exhaustive comparison of the most relevant approaches in the field.Peer ReviewedPostprint (author's final draft
Considerations for believable emotional facial expression animation
Facial expressions can be used to communicate emotional states through the use of universal signifiers within key regions of the face. Psychology research has identified what these signifiers are and how different combinations and variations can be interpreted. Research into expressions has informed animation practice, but as yet very little is known about the movement within and between emotional expressions. A better understanding of sequence, timing, and duration could better inform the production of believable animation. This paper introduces the idea of expression choreography, and how tests of observer perception might enhance our understanding of moving emotional expressions
Investigating facial animation production through artistic inquiry
Studies into dynamic facial expressions tend to make use of experimental methods based on objectively manipulated stimuli. New techniques for displaying increasingly realistic facial movement and methods of measuring observer responses are typical of computer animation and psychology facial expression research. However, few projects focus on the artistic nature of performance production. Instead, most concentrate on the naturalistic appearance of posed or acted expressions. In this paper, the authors discuss a method for exploring the creative process of emotional facial expression animation, and ask whether anything can be learned about authentic dynamic expressions through artistic inquiry
Fidelity metrics for animation
In this talk, the problem of evaluating the fidelity of animations will be addressed. The concept of plausible simulation has recently be receiving much attention, and I will present a review of this field and discuss how perceptual metrics are necessary to ensure that such animations are truly perceived as real. Then, our recent work in the development of such metrics will be presented. This includes investigations into the perception of collisions and, more recently, psychophysical experiments that examined human sensitivity to dynamic anomalies, leading to the first steps to developing a metric to evaluate the visual fidelity of physically - based animations. Finally, the efforts to develop perceptual metrics for other types of animation, including multi-modal systems and character animation, will also be discusse
Creative approaches to emotional expression animation
In facial expression research, it is well established that certain emotional expressions are universally recognized. Studies into observer perception of expressions have built upon this research by highlighting the importance of particular facial regions, actions, and movements to the recognition of emotions. In many studies, the stimuli for such studies have been generated through posing by non-experts or performances by trained actors. However, character animators are required to craft recognizable, believable emotional facial expressions as a part of their profession. In this poster, the authors discuss some of the creative processes employed in their research into emotional expressions, and how practice-led research into expression animation might offer a new perspective on the generation of believable emotional expressions
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