Hand Interface in Traditional Modeling and Animation Tasks

3-D task space in modeling and animation is usually reduced to the separate control dimensions supported by conventional interactive devices.This limitation maps only partial view of the problem to the device space at a time,and results in tedious and unnatural interface of control.This paper uses the DataGlove interface for modeling and animating scene behaviors.The modeling interface selects,scales,rotates,translates,copies and deletes the instances of the primitives.These basic modeling processes are directly performed in the task space,using hand shapes and motions.Hand shapes are recognized as discrete states that trigger the commands,and hand motion are mapped to the movement of a selected instance.The interactions through hand interface place the user as a participant in the process of behavior simulation.Both event triggering and role switching of hand are experimented in simulation.The event mode of hand triggers control signals or commands through a menu interface.The object mode of hand simulates itself as an object whose appearance or motion influences the motions of other objects in scene.The involvement of hand creates a diversity of dynamic situations for testing variable scene behaviors.Our experiments have shown the potential use of this interface directly in the 3-D modeling and animation task space.     

A behavioural test-bed using a dataglove input device

In many cases, traditional hand-drawn animation has been replaced by computer technology. Computer-supported approaches can essentially be characterised as two interface types: keyframing and coding. However, these two interface types offer limited editing ability for scene animation applications, which usually consist of a large testing space of similar behaviours. The testing cycle, using either predefined keyframe sequences or general coding interface, tends to be costly and time consuming. This paper reports work which uses the DataGlove device to support and test variable schooling behaviours of fish in a virtual marine world. This is put forward as a representative example of scene animation. The glove-based interface places the user as a participant in the behavioural simulation process. In the work, hand shapes and motions are recognised and used for either event triggering or role switching. The specific shapes and motions of the user's hand trigger control signals or commands through a menu-based interface. The hand can itself be used to simulate an object in the scene. The object, which can be either static or dynamic, participates in the control process. Using hand movements in this way allows the user to interactively specify the paths of moving objects in the scene, and also creates a diversity of dynamic situations which can be useful for testing variable scene behaviours. The application presented in this paper looks at examples of controlling fish behaviour in a limited pond environment controlled by glove-based interaction.     

Direct Virtual-hand Interface in Robot Assembly Programming

For a long time, robot assembly programming has been produced in two environments: on-line and off-line. On-line robot programming uses the actual robot for the experiments performing a given task; off-line robot programming develops a robot program in either an autonomous system with a high-level task planner and simulation or a 2D graphical user interface linked to other system components. This paper presents a whole hand interface for more easily performing robotic assembly tasks in the virtual tenvironment. The interface is composed of both static hand shapes (states) and continuous hand motions (modes). Hand shapes are recognized as discrete states that trigger the control signals and commands, and hand motions are mapped to the movements of a selected instance in real-time assembly. Hand postures are also used for specifying the alignment constraints and axis mapping of the hand-part coordinates. The basic virtual-hand functions are constructed through the states and modes developing the robotic assembly program. The assembling motion of the object is guided by the user immersed in the environment to a path such that no collisions will occur. The fine motion in controlling the contact and ending position/orientation is handled automatically by the system using prior knowledge of the parts and assembly reasoning. One assembly programming case using this interface is described in detail in the paper.     

Combined Direct and Inverse Kinematic Control for Articulated Figure Motion Editing

A new approach for the animation of articulated figures is presented. We propose a system of articulated motion design which offers a full combination of both direct and inverse kinematic control of the joint parameters. Such an approach allows an animator to specify interactively goal-directed changes to existing sampled joint motions, resulting in a more general and expressive class of possible joint motions. The fundamental idea is to consider any desired-joint space motion as a reference model inserted into the secondary task of an inverse kinematic control scheme. This approach profits from the use of half-space Cartesian main tasks in conjunction with a parallel control of the articulated figure called the coach-trainee metaphor. In addition, a transition function is introduced so as to guarantee the continuity of the control. The resulting combined kinematic control scheme leads to a new methodology of joint-motion editing which is demonstrated through the improvement of a functional model of human walking.     

基于Java 3D的虚拟人仿真方法

提出一种将3DS MAX、MS3D与Java 3D编程技术相结合的虚拟人仿真方法,可使虚拟人达到相对逼真且交互性强的效果。该方法首先采用3DS MAX角色动画技术进行人体静态建模和动作建模;然后通过将底层基本动作片段转化为MS3D格式,供Java 3D的骨骼动画模型接口调用;最后利用Java 3D编程来控制虚拟人的高层行为活动。该方法有利于角色建模、运动仿真和行为控制等设计工作的分工协作,适合于网络环境下多角色、复杂动作的虚拟人仿真。     

Physically Based Video Editing

Convincing manipulation of objects in live action videos is a difficult and often tedious task. Skilled video editors achieve this with the help of modern professional tools, but complex motions might still lack physical realism since existing tools do not consider the laws of physics. On the other hand, physically based simulation promises a high degree of realism, but typically creates a virtual 3D scene animation rather than returning an edited version of an input live action video. We propose a framework that combines video editing and physics‐based simulation. Our tool assists unskilled users in editing an input image or video while respecting the laws of physics and also leveraging the image content. We first fit a physically based simulation that approximates the object's motion in the input video. We then allow the user to edit the physical parameters of the object, generating a new physical behavior for it. The core of our work is the formulation of an image‐aware constraint within physics simulations. This constraint manifests as external control forces to guide the object in a way that encourages proper texturing at every frame, yet producing physically plausible motions. We demonstrate the generality of our method on a variety of physical interactions: rigid motion, multi‐body collisions, clothes and elastic bodies.     

Objects interaction using superquadrics for telemanipulation system simulation

A high-fidelity “hybrid” telerobotic simulator suitable for telemanipulation rehearsal, supervisory control, operator training, and human factors performance evaluation has been developed. The simulator is capable of operation in the conventional rate-control, master/slave control, and a data-driven preprogrammed mode of operation. It has teach/playback capability, which allows an operator to generate joint commands for real-time teleoperation. For high-level task execution, the operator selects a specific task from a set of menu options and the simulator automatically generates the required joint commands. In this article, an object detection strategy that has been implemented in the simulator for more realistic telemanipulation is presented. The object detection technique is based on the use of superellipsoids, which have a convenient inside-outside function for interference testing. The technique, which treats both moving and stationary objects in a consistent manner, has proved to be easy to implement and optimize for real-time applications. The object detection feature is also used to provide visual feedback as a low-cost force reflection strategy.     

State of the Art in Hand and Finger Modeling and Animation

The human hand is a complex biological system able to perform numerous tasks with impressive accuracy and dexterity. Gestures furthermore play an important role in our daily interactions, and humans are particularly skilled at perceiving and interpreting detailed signals in communications. Creating believable hand motions for virtual characters is an important and challenging task. Many new methods have been proposed in the Computer Graphics community within the last years, and significant progress has been made towards creating convincing, detailed hand and finger motions. This state of the art report presents a review of the research in the area of hand and finger modeling and animation. Starting with the biological structure of the hand and its implications for how the hand moves, we discuss current methods in motion capturing hands, data‐driven and physics‐based algorithms to synthesize their motions, and techniques to make the appearance of the hand model surface more realistic. We then focus on areas in which detailed hand motions are crucial such as manipulation and communication. Our report concludes by describing emerging trends and applications for virtual hand animation.     

Artist-Directed Inverse-Kinematics Using Radial Basis Function Interpolation

One of the most common tasks in computer animation is inverse-kinematics, or determining a joint configuration required to place a particular part of an articulated character at a particular location in global space. Inverse-kinematics is required at design-time to assist artists using commercial 3D animation packages, for motion capture analysis, and for run-time applications such as games.
We present an efficient inverse-kinematics methodology based on the interpolation of example motions and positions. The technique is demonstrated on a number of inverse-kinematics positioning tasks for a human figure. In addition to simple positioning tasks, the method provides complete motion sequences that satisfy an inverse-kinematic goal. The interpolation at the heart of the algorithm allows an artist's influence to play a major role in ensuring that the system always generates plausible results. Due to the lightweight nature of the algorithm, we can position a character at extremely high frame rates, making the technique useful for time-critical run-time applications such as games.     

基于多分辨率模型的快速运动过渡生成算法

运动捕获技术可以记录人体关节运动的细节,是当前最有前景的计算机动画技术.然而,运动数据的重用性一直是个难点,为此,多种运动编辑手段被提出.运动过渡是一种常见的编辑技术,它可以将输入的两端运动序列拼接,形成新的运动序列.其中,过渡点选择的合理与否直接影响着结果运动的质量.在两运动间选择过渡点,需要对输入运动的每一对帧之间分别计算帧间的距离,其计算复杂度是O(n2)的,通过引入多分辨率模型,文中将该复杂度降低到O(nlog2n),同时试验结果表明,此方法并未损害到结果运动的质量.     

Robot motion command simplification and scaling

It has been observed that human limb motions are not very accurate, leading to the hypothesis that the human motor control system may have simplified motion commands at the expense of motion accuracy. Inspired by this hypothesis, we propose learning schemes that trade motion accuracy for motion command simplification. When the original complex motion commands capable of tracking motion accurately are reduced to simple forms, the simplified motion commands can then be stored and manipulated by using learning mechanisms with simple structures and scanty memory resources, and they can be executed quickly and smoothly. We also propose learning schemes that can perform motion command scaling, so that simplified motion commands can be provided for a number of similar motions of different movement distances and velocities without recalculating system dynamics. Simulations based on human motions are reported that demonstrate the effectiveness of the proposed learning schemes in implementing this accuracy-simplification tradeoff.     

The effectiveness of task-level parallelism for production systems

Large production systems (rule-based systems) continue to suffer from extremely slow execution which limits their utility in practical applications as well as in research settings. Most investigations in speeding up these systems have focused on match parallelism. These investigations have revealed that the total speed-up available from this source is insufficient to alleviate the problem of slow execution in large-scale production system implementations. In this paper, we focus on task-level parallelism, which is obtained by a high-level decomposition of the production system. Speed-ups obtained from task-level parallelism will multiply with the speed-ups obtained from match parallelism. The vehicle for our investigation of task-level parallelism is SPAM, a high-level vision system, implemented as a production system. SPAM is a mature research system with a typical run requiring between 50,000 and 400,000 production firings. We report very encouraging speed-ups from task-level parallelism in SPAM… -our parallel implementation shows near linear speed-ups of over 12-fold using 14 processors and points the way to substantial (50- to 100-fold) speed-ups. We present a characterization of task-level parallelism in production systems and describe our methodology for selecting and applying a particular approach to parallelize SPAM. Additionally, we report the speed-ups obtained from the use of virtual shared memory. Overall, task-level parallelism has not received much attention in the literature. Our experience illustrates that it is potentially a very important tool for speeding up large-scale production systems.     

Integrating a flexible anthropomorphic, robot hand into the control, system of a humanoid robot

This article presents the approaches taken to integrate a novel anthropomorphic robot hand into a humanoid robot. The requisites enabling such a robot hand to use everyday objects in an environment built for humans are presented. Starting from a design that resembles the human hand regarding size and movability of the mechatronical system, a low-level control system is shown providing reliable and stable controllers for single joint angles and torques, entire fingers and several coordinated fingers. Further on, the high-level control system connecting the low-level control system with the rest of the humanoid robot is presented. It provides grasp skills to the superior robot control system, coordinates movements of hand and arm and determines grasp patterns, depending on the object to grasp and the task to execute. Finally some preliminary results of the system, which is currently tested in simulations, will be presented.     

具有真实感的三维人脸动画

具有真实感的三维人脸模型的构造和动画是计算机图形学领域中一个重要的研究课题.如何在三维人脸模型上实时地模拟人脸的运动,产生具有真实感的人脸表情和动作,是其中的一个难点.提出一种实时的三维人脸动画方法,该方法将人脸模型划分成若干个运动相对独立的功能区,然后使用提出的基于加权狄里克利自由变形DFFD(Dirichlet free-form deformation)和刚体运动模拟的混合技术模拟功能区的运动.同时,通过交叉的运动控制点模拟功能区之间运动的相互影响.在该方法中,人脸模型的运动通过移动控制点来驱动.为了简化人脸模型的驱动,提出了基于MPEG-4中脸部动画参数FAP(facial animation parameters)流和基于肌肉模型的两种高层驱动方法.这两种方法不但具有较高的真实感,而且具有良好的计算性能,能实时模拟真实人脸的表情和动作.     

Human motion prediction for human-robot collaboration

In human-robot collaborative manufacturing, industrial robots would work alongside human workers who jointly perform the assigned tasks seamlessly. A human-robot collaborative manufacturing system is more customised and flexible than conventional manufacturing systems. In the area of assembly, a practical human-robot collaborative assembly system should be able to predict a human worker’s intention and assist human during assembly operations. In response to the requirement, this research proposes a new human-robot collaborative system design. The primary focus of the paper is to model product assembly tasks as a sequence of human motions. Existing human motion recognition techniques are applied to recognise the human motions. Hidden Markov model is used in the motion sequence to generate a motion transition probability matrix. Based on the result, human motion prediction becomes possible. The predicted human motions are evaluated and applied in task-level human-robot collaborative assembly.     

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.     

Connectionist modelling of skill dynamics

This paper discusses a method for modelling skilled action for synthetic actors in a virtual environment. The method guides lower-level motor skills from a connectionist model of skill memory, implemented as collections of trained neural networks. The relationship between this work and that of other projects in task-level animation is discussed, the principles of connectionist learning are explained, and a series of experiments testing the concept of connectionist skill modelling are reviewed.