Head-Tracked Stereo Viewing with Two-Handed 3 D Interaction for Animated Character Construction

In this paper, we demonstrate how a new interactive 3 D desktop metaphor based on two-handed 3 D direct manipulation registered with head-tracked stereo viewing can be applied to the task of constructing animated characters. In our configuration, a six degree-of-freedom head-tracker and CrystalEyes shutter glasses are used to produce stereo images that dynamically follow the user head motion. 3 D virtual objects can be made to appear at a fixed location in physical space which the user may view from different angles by moving his head. To construct 3 D animated characters, the user interacts with the simulated environment using both hands simultaneously: the left hand, controlling a Spaceball, is used for 3 D navigation and object movement, while the right hand, holding a 3 D mouse, is used to manipulate through a virtual tool metaphor the objects appearing in front of the screen. In this way, both incremental and absolute interactive input techniques are provided by the system. Hand-eye coordination is made possible by registering virtual space exactly to physical space, allowing a variety of complex 3 D tasks necessary for constructing 3 D animated characters to be performed more easily and more rapidly than is possible using traditional interactive techniques. The system has been tested using both Polhemus Fastrak and Logitech ultrasonic input devices for tracking the head and 3 D mouse.     

Soft Articulated Characters with Fast Contact Handling

Fast contact handling of soft articulated characters is a computationally challenging problem, in part due to complex interplay between skeletal and surface deformation. We present a fast, novel algorithm based on a layered representation for articulated bodies that enables physically-plausible simulation of animated characters with a high-resolution deformable skin in real time. Our algorithm gracefully captures the dynamic skeleton-skin interplay through a novel formulation of elastic deformation in the pose space of the skinned surface. The algorithm also overcomes the computational challenges by robustly decoupling skeleton and skin computations using careful approximations of Schur complements, and efficiently performing collision queries by exploiting the layered representation. With this approach, we can simultaneously handle large contact areas, produce rich surface deformations, and capture the collision response of a character/s skeleton.     

Model-based human shape reconstruction from multiple views

Image-based modelling allows the reconstruction of highly realistic digital models from real-world objects. This paper presents a model-based approach to recover animated models of people from multiple view video images. Two contributions are made, a multiple resolution model-based framework is introduced that combines multiple visual cues in reconstruction. Second, a novel mesh parameterisation is presented to preserve the vertex parameterisation in the model for animation. A prior humanoid surface model is first decomposed into multiple levels of detail and represented as a hierarchical deformable model for image fitting. A novel mesh parameterisation is presented that allows propagation of deformation in the model hierarchy and regularisation of surface deformation to preserve vertex parameterisation and animation structure. The hierarchical model is then used to fuse multiple shape cues from silhouette, stereo and sparse feature data in a coarse-to-fine strategy to recover a model that reproduces the appearance in the images. The framework is compared to physics-based deformable surface fitting at a single resolution, demonstrating an improved reconstruction accuracy against ground-truth data with a reduced model distortion. Results demonstrate realistic modelling of real people with accurate shape and appearance while preserving model structure for use in animation.     

Behaviourally rich actions for user-controlled characters

The increasing use of animated characters and avatars in computer games and 3D online worlds requires increasingly complex behaviour with increasingly simple and easy to use control systems. This paper presents a system for user-controlled actions that aims at simplicity and ease of use while being enhanced by modern animation techniques to produce rich and complex behaviour. We use inverse kinematics based motion adaptation to make pre-existing pieces of motion apply to new targets. The expressiveness of the character is enhanced by adding autonomous behaviour, in this case eye gaze behaviour. This behaviour is generated autonomously but is still influenced by the actions that the user is requesting the character to perform. The actions themselves are simple for a designer with no programming experience to design and for an end user to customise. They are also very simple to invoke.     

Sketching human character animations by composing sequences from large motion database

Quick creation of 3D character animations is an important task in game design, simulations, forensic animation, education, training, and more. We present a framework for creating 3D animated characters using a simple sketching interface coupled with a large, unannotated motion database that is used to find the appropriate motion sequences corresponding to the input sketches. Contrary to the previous work that deals with static sketches, our input sketches can be enhanced by motion and rotation curves that improve matching in the context of the existing animation sequences. Our framework uses animated sequences as the basic building blocks of the final animated scenes, and allows for various operations with them such as trimming, resampling, or connecting by use of blending and interpolation. A database of significant and unique poses, together with a two-pass search running on the GPU, allows for interactive matching even for large amounts of poses in a template database. The system provides intuitive interfaces, an immediate feedback, and poses very small requirements on the user. A user study showed that the system can be used by novice users with no animation experience or artistic talent, as well as by users with an animation background. Both groups were able to create animated scenes consisting of complex and varied actions in less than 20 minutes.     

Linear Time Stable PD Controllers for Physics-based Character Animation

In physics-based character animation, Proportional-Derivative (PD) controllers are commonly used for tracking reference motions in motor control tasks. Stable PD (SPD) controllers significantly improve the numerical stability of traditional PD controllers and support large gains and large integration time steps during simulation [TLT11]. For an articulated rigid body system with n degrees of freedom, all SPD implementations to date, however, use an O(n³) dense matrix factorization based method. In this paper, we propose a linear time algorithm for SPD computation, which is based on Featherstone's forward dynamics formulation for articulated rigid body systems in generalized coordinates [Fea14]. We demonstrate the performance advantage of our algorithm by comparing with both the conventional dense matrix factorization based method and an alternative sparse matrix factorization based method. We show that the proposed algorithm provides superior stability when controlling complex models at large time steps. We further demonstrate that our algorithm can improve the learning speed and quality of a Deep Reinforcement Learning (DRL) system for physics-based character animation.     

面向影视动画的真实感三维人脸快速建模算法

针对影视动画领域,利用LS_5000型三维激光扫描仪,提出了一套真实感三维人脸快速建模算法。只需输入真实演员人脸的三维扫描点云和未定标的照片,以及极少的人工交互,即可生成虚拟演员真实感的三维人脸模型（包括几何模型、纹理模型和面向动画的可变模型）。实验结果表明,算法输出的模型简洁规范,可直接应用于实际的影视动画制作,提高了人脸模型建模效率。     

Deformable Motion: Squeezing into Cluttered Environments

We present an interactive method that allows animated characters to navigate through cluttered environments. Our characters are equipped with a variety of motion skills to clear obstacles, narrow passages, and highly constrained environment features. Our control method incorporates a behavior model into well‐known, standard path planning algorithms. Our behavior model, called deformable motion, consists of a graph of motion capture fragments. The key idea of our approach is to add flexibility on motion fragments such that we can situate them into a cluttered environment via constraint‐based formulation. We demonstrate our deformable motion for realtime interactive navigation and global path planning in highly constrained virtual environments.     

Learnt inverse kinematics for animation synthesis

Existing work on animation synthesis can be roughly split into two approaches, those that combine segments of motion-capture data, and those that perform inverse kinematics. In this paper, we present a method for performing animation synthesis of an articulated object (e.g. human body and a dog) from a minimal set of body joint positions, following the approach of inverse kinematics. We tackle this problem from a learning perspective. Firstly, we address the need for knowledge on the physical constraints of the articulated body, so as to avoid the generation of a physically impossible poses. A common solution is to heuristically specify the kinematic constraints for the skeleton model. In this paper however, the physical constraints of the articulated body are represented using a hierarchical cluster model learnt from a motion capture database. Additionally, we shall show that the learnt model automatically captures the correlation between different joints through simultaneous modelling of their angles. We then show how this model can be utilised to perform inverse kinematics in a simple and efficient manner. Crucially, we describe how IK is carried out from a minimal set of end-effector positions. Following this, we show how this “learnt inverse kinematics” framework can be used to perform animation syntheses on different types of articulated structures. To this end, the results presented include the retargeting of a flat surface walking animation to various uneven terrains to demonstrate the synthesis of a full human body motion from the positions of only the hands, feet and torso. Additionally, we show how the same method can be applied to the animation synthesis of a dog using only its feet and torso positions.     

The development of an instrument to measure the degree of animation predisposition of agent users

The study reports on the development and operationalization of a construct that captures an individual’s degree of predisposition towards watching animated films. It is believed that this construct may potentially explicate a person’s perceptions and usage behavior towards animated agents in Microsoft Office applications. Animation predisposition is defined as an individual specific trait that reflects a person’s predisposition towards watching animated films. It is operationalized in form of a four-item Likert type scale, which was found highly reliable and valid. This construct does not correlate with two other individual specific traits: computer playfulness and personal innovativeness in the domain of information technology. As such, it is suggested that animation predisposition is a distinct and independent research construct exhibiting desirable psychometric properties. The analysis demonstrates that the degree of people’s animation predisposition is positively associated with their perceptions of enjoyment with an animated agent in MS Office. The computer users who have a higher degree of animation predisposition attempt to explore an agent’s personalization settings more frequently than those with a lower degree of animation predisposition. Overall, this study offers a new approach to the investigation of an untapped area aiming to improve the quality of the contemporary research on the usefulness and user acceptance of animated agents.