1. Introduction and Historical Background 1.1 Why make human figure models? 1.2 Historical roots 1.3 What is currently possible? 1.4 Manipulation, animation, and simulation 1.5 What did we leave out? 2. Mody Modeling 2.1 Geometric body modeling 2.2 Representing articulated figures 2.3 A flexible torso model 2.4 Shoulder complex 2.5 Clothing models 2.6 The anthropometry database 2.7 The anthropometry spreadsheet 2.8 Strength and torque display 3. Spatial Interaction 3.1 Direct manipulation 3.2 Manipulation with constraints 3.3 Inverse kinematic positioning 4. Behavioral Control of Articulated Figures 4.1 An interactive system for postural control 4.2 Interactive manipulation with behaviors 4.3 The animation interface 4.4 Human figure motions 4.5 Virtual human control 5. Simulation with Societies of Behaviors 5.1 Forward simulation with behaviors 5.2 Locomotion 5.3 Strength guided motion 5.4 Collision-free path and motion planning 5.5 Posture planning 6. Task-level Specifications 6.1 Performance simulation with simple commands 6.2 Natural language expressions of kinematics and space 6.3 Task-level simulation 6.4 A framework for instruction understanding 7. Epilogue 7.1 A road map toward the future 7.2 Conclusion

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Simulating humans: computer graphics animation and control

Motion-based recognition a survey

Human movements include limb gestures and postural attitude. Although many computer animation researchers have studied these classes of movements, procedurally generated movements still lack naturalness. We argue that looking only at the psychological notion of gesture is insufficient to capture movement qualities needed by animated charactes. We advocate that the domain of movement observation science, specifically Laban Movement Analysis (LMA) and its Effort and Shape components, provides us with valuable parameters for the form and execution of qualitative aspects of movements. Inspired by some tenets shared among LMA proponents, we also point out that Effort and Shape phrasing across movements and the engagement of the whole body are essential aspects to be considered in the search for naturalness in procedurally generated gestures. Finally, we present EMOTE (Expressive MOTion Engine), a 3D character animation system that applies Effort and Shape qualities to independently defined underlying movements and thereby generates more natural synthetic gestures.

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The EMOTE model for effort and shape

The authors develop a unique CT simulation tool based on the 4D extended cardiac-torso (XCAT) phantom, a whole-body computer model of the human anatomy and physiology based on NURBS surfaces Unlike current phantoms in CT based on simple mathematical primitives, the 4D XCAT provides an accurate representation of the complex human anatomy and has the advantage, due to its design, that its organ shapes can be changed to realistically model anatomical variations and patient motion A disadvantage to the NURBS basis of the XCAT, however, is that the mathematical complexity of the surfaces makes the calculation of line integrals through the phantom difficult They have to be calculated using iterative procedures; therefore, the calculation of CT projections is much slower than for simpler mathematical phantoms To overcome this limitation, the authors used efficient ray tracing techniques from computer graphics, to develop a fast analytic projection algorithm to accurately calculate CT projections directly from the surface definition of the XCAT phantom given parameters defining the CT scanner and geometry Using this tool, realistic high-resolution 3D and 4D projection images can be simulated and reconstructed from the XCAT within a reasonable amount of time In comparison with other simulators with geometrically defined organs, the XCAT-based algorithm was found to be only three times slower in generating a projection data set of the same anatomical structures using a single 32 GHz processor To overcome this decrease in speed would, therefore, only require running the projection algorithm in parallel over three processors With the ever decreasing cost of computers and the rise of faster processors and multi-processor systems and clusters, this slowdown is basically inconsequential, especially given the vast improvement the XCAT offers in terms of realism and the ability to generate 3D and 4D data from anatomically diverse patients As such, the authors conclude that the efficient XCAT-based CT simulator developed in this work will have applications in a broad range of CT imaging research

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Realistic CT simulation using the 4D XCAT phantom

This paper addresses the problem of simulating deformations between objects and the hand of a synthetic character during a grasping process. A numerical method based on finite element theory allows us to take into account the active forces of the fingers on the object and the reactive forces of the object on the fingers. The method improves control of synthetic human behavior in a task level animation system because it provides information about the environment of a synthetic human and so can be compared to the sense of touch. Finite element theory currently used in engineering seems one of the best approaches for modeling both elastic and plastic deformation of objects, as well as shocks with or without penetration between deformable objects. We show that intrinsic properties of the method based on composition/decomposition of elements have an impact in computer animation. We also state that the use of the same method for modeling both objects and human bodies improves the modeling both objects and human bodies improves the modeling of the contacts between them. Moreover, it allows a realistic envelope deformation of the human fingers comparable to existing methods. To show what we can expect from the method, we apply it to the grasping and pressing of a ball. Our solution to the grasping problem is based on displacement commands instead of force commands used in robotics and human behavior.

Simulation of object and human skin formations in a grasping task

A kinematic simulation model allows realistic animation of the human body-provided the body is in contact with the ground and input data is accurate.

Chapman

Papers

Aspects of the Kinematic Simulation of Human Movement