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 5×-10×. 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

Fast Simulation of Skin Sliding

Skin sliding is the phenomenon of the skin moving over underlying layers of fat, muscle and bone. Due to the complex interconnections between these separate layers and their differing elasticity properties, it is difficult to model and expensive to compute. We present a novel method to simulate this phenomenon at real--time by remeshing the surface based on a parameter space resampling. In order to evaluate the surface parametrization, we borrow a technique from structural engineering known as the force density method which solves for an energy minimizing form with a sparse linear system. Our method creates a realistic approximation of skin sliding in real--time, reducing texture distortions in the region of the deformation. In addition it is flexible, simple to use, and can be incorporated into any animation pipeline

Sketching-out virtual humans: A smart interface for human modelling and animation

In this paper, we present a fast and intuitive interface for sketching out 3D virtual humans and animation. The user draws stick figure key frames first and chooses one for “fleshing-out” with freehand body contours. The system automatically constructs a plausible 3D skin surface from the rendered figure, and maps it onto the posed stick figures to produce the 3D character animation. A “creative model-based method” is developed, which performs a human perception process to generate 3D human bodies of various body sizes, shapes and fat distributions. In this approach, an anatomical 3D generic model has been created with three distinct layers: skeleton, fat tissue, and skin. It can be transformed sequentially through rigid morphing, fatness morphing, and surface fitting to match the original 2D sketch. An auto-beautification function is also offered to regularise the 3D asymmetrical bodies from users’ imperfect figure sketches. Our current system delivers character animation in various forms, including articulated figure animation, 3D mesh model animation, 2D contour figure animation, and even 2D NPR animation with personalised drawing styles. The system has been formally tested by various users on Tablet PC. After minimal training, even a beginner can create vivid virtual humans and animate them within minutes

Efficient ordinary differential equation-based modelling and skin deformations for character animation.

In the area of character animation, skin surface modelling, rigging and skin deforamtion are three essential aspects. Due to the different complexity of the characters, the time cost on creating corresponding skin surface model, animation skeleton in order to achieve diverse skin de- formations, fluctuates from several hours to several weeks. More importantly, the data size of skin deformations could sharply influence the efficiency of generating animation. Smaller data size can also speed up character animation and transmission over computer networks. Over years, researchers have developed a variety of skin deformation techniques. Geometric skin deformation approaches have high efficiency but low realism. Example-based skin deformation approaches interpolate a set of given example poses to improve realism and effects that cannot be easily produced by geometric approaches. Physics-based skin deformation methods can greatly improve the realism of character animation, but require non-trivial training, intensive manual intervention, and heavy numerical calculations. Due to these limitations, many recent activities have initiated the research of integrating geometric, example-based, and physics-based skin deformation approaches. The current research is to develop techniques based on Ordinary Differentical Equations (ODE) to efficiently create C2 continuous skin surfaces through two boundary curves, automatically generate skeleton to make the rigging process fast enough for highly efficient computer animation applications, and achieve physically realistic skin deformations for character animation by integrating geometric, physical and data-driven methods. Meanwhile, it is the first attempt to obtain an analytical solution to realistic physics-based skin deformations for highly efficient computation, to avoid the solving of a large set of linear equations, which largely reduces data size and computing time. The basic idea is to build ODE mechanics model, involve isoparametric curves and Fourier Series representation, develop accurate and efficient solutions to calculate physical skin deformations through interpolating input realistic reconstructed 3D models. The proposed techniques will greatly avoid tedious manual work, reduce data size, improve skin deformation realism, and raise efficiency of producing character animation

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

Automatic generation of dynamic skin deformation for animated characters

© 2018 by the authors. Since non-automatic rigging requires heavy human involvements, and various automatic rigging algorithms are less efficient in terms of computational efficiency, especially for current curve-based skin deformation methods, identifying the iso-parametric curves and creating the animation skeleton requires tedious and time-consuming manual work. Although several automatic rigging methods have been developed, but they do not aim at curve-based models. To tackle this issue, this paper proposes a new rigging algorithm for automatic generation of dynamic skin deformation to quickly identify iso-parametric curves and create an animation skeleton in a few milliseconds, which can be seamlessly used in curve-based skin deformation methods to make the rigging process fast enough for highly efficient computer animation applications

Dynamic skin deformation using finite difference solutions for character animation

We present a new skin deformation method to create dynamic skin deformations in this paper. The core elements of our approach are a dynamic deformation model, an efficient data-driven finite difference solution, and a curve-based representation of 3D models. We first reconstruct skin deformation models at different poses from the taken photos of a male human arm movement to achieve real deformed skin shapes. Then, we extract curves from these reconstructed skin deformation models. A new dynamic deformation model is proposed to describe physics of dynamic curve deformations, and its finite difference solution is developed to determine shape changes of the extracted curves. In order to improve visual realism of skin deformations, we employ data-driven methods and introduce skin shapes at the initial and final poses into our proposed dynamic deformation model. Experimental examples and comparisons made in this paper indicate that our proposed dynamic skin deformation technique can create realistic deformed skin shapes efficiently with a small data size

LiveCap: Real-time Human Performance Capture from Monocular Video

We present the first real-time human performance capture approach that reconstructs dense, space-time coherent deforming geometry of entire humans in general everyday clothing from just a single RGB video. We propose a novel two-stage analysis-by-synthesis optimization whose formulation and implementation are designed for high performance. In the first stage, a skinned template model is jointly fitted to background subtracted input video, 2D and 3D skeleton joint positions found using a deep neural network, and a set of sparse facial landmark detections. In the second stage, dense non-rigid 3D deformations of skin and even loose apparel are captured based on a novel real-time capable algorithm for non-rigid tracking using dense photometric and silhouette constraints. Our novel energy formulation leverages automatically identified material regions on the template to model the differing non-rigid deformation behavior of skin and apparel. The two resulting non-linear optimization problems per-frame are solved with specially-tailored data-parallel Gauss-Newton solvers. In order to achieve real-time performance of over 25Hz, we design a pipelined parallel architecture using the CPU and two commodity GPUs. Our method is the first real-time monocular approach for full-body performance capture. Our method yields comparable accuracy with off-line performance capture techniques, while being orders of magnitude faster

Rigging Realistic Skin Deformation with Muscle Systems

Realistic skin deformation is one of the major criteria for creating believable, dig- itally enhanced characters. Muscle simulation is one of the more popular techniques used in filmmaking. It helps bring a sense of realism to the character by adding subtle, secondary motion to the skin. Small features like these make the character appear more lifelike. This thesis focuses on the generation of a character rig and implementation of a digital muscle system for a tiger. The rig is built and animated in Maya and the Maya Muscle tool was used to create the muscle system. The muscle deformations are compared to the standard smooth skinning method in a walk and run animation