Modeling and Simulating Virtual Anatomical Humans

IEEE C95.1 (radio frequency) and C95.6 (low frequency) standards for human protection from electromagnetic fields are currently under revision. In the next revision, they will be combined into one standard covering the frequency range from 0 Hz to 300 GHz. Although the C95.1 standard considers anatomical human models for deriving the relationship between internal and external field strengths, homogeneous ellipses are used in the C95.6 standard. In the guidelines of the International Commission on Non-Ionizing Radiation Protection, anatomical human models are used together with reduction factors to account for numerical uncertainty. It is worth revisiting their relationship when using different anatomical models. In this paper, five research groups performed a comparative study to update the state-of-the-art knowledge of in situ electric fields in anatomical human models when exposed to uniform low-frequency magnetic fields. The main goals were to clarify both numerical uncertainty and model variability. The computational results suggest a high consistency among in situ field strengths across laboratories; agreement in the 99th percentile with a discrepancy of under 5% was achieved. The in situ electric fields varied as expected given the models’ different dimensions. The induction factor, which is the ratio of the in situ electric fields for the temporal derivative of the external magnetic flux density, is derived for body parts and tissues. The classification of body parts into “the limb” and “other tissues” is shown to be critical for determining the in situ field strength.

<div class="section abstract"><div class="htmlview paragraph">The paper contributes to the field of vehicle safety technology by the virtual approach using biomechanical virtual human body models. The goal of the paper is to exploit the previously developed scaling algorithm to create several virtual human models of a given age and body proportions and to assess the impact analysis using the sensitivity approach.</div><div class="htmlview paragraph">Based on a validated reference model, the previously developed scaling algorithm develops virtual human body models for given height, mass, age and gender. Particular body segments are scaled based on the anthropometrical database concerning the body dimensions taking also percentiles into account. The body stiffness is driven by age dependent flexindex.</div><div class="htmlview paragraph">Several virtual models of human bodies representing particular cadavers were generated via the automatic scaling algorithm. The frontal sled test response of three models was successfully compared to the available experimental data previously. Since all the sled tests concerned different seat and loading conditions, the models were further compared by running the same standard sled test. The particular model anthropometry dependent response was compared for the different body statures.</div></div>

Until relatively recently, researchers in computer graphics paid scant attention to the numerics of their computations. Computation was used as a simple tool to evaluate algorithms or transform data into some appropriate pictoral representation. Thus standard computer graphics texts have little to say about numerical methods, just as earlier numerical analysis textbooks had little to say about computer graphics. This is now changing, for the important reasons outlined in this paper.

Three-dimensional (3D) body scanning technology opens opportunities for virtual try-on and automatic made-to-measure apparel design. This paper proposes a new feature-based parametric method for modeling human body shape from scanned point clouds of a 3D body scanner [TC] 2. The human body model consists of two layers: the skeleton and the cross sections of each body part. First, a simple skeleton model from the body scanner [TC] 2 system has been improved by adding and adjusting the position of joints in order to better address some fit issues related to body shape changes such as spinal bending. Second, an automatic approach to extracting semantic features for cross sections has been developed based on the body hierarchy. For each cross section, it is described by a set of key points which can be fit with a closed cardinal spline. According to the point distribution in point clouds, an extraction method of key points on cross sections has been studied and developed. Third, this paper presents an interpolation approach to fitting the key points on a cross section to a cardinal spline, in which different tension parameters are tested and optimized to represent simple deformations of body shape. Finally, a connection approach of body parts is proposed by sharing a boundary curve. The proposed method has been tested with the developed virtual human model (VHM) system which is robust and easier to use. The model can also be imported in a CAD environment for other applications.

The modeling of plants is an active area of research in computer graphics and the geometrical modeling of veins is essential for obtaining plant images with a realistic appearance. The venation patterns determine the anisotropy of plant tissues, and affect the shadowing and masking of light incident on these tissues, hence the images. The current trend in the area of plant image generation is to aim for realism using biologically-based and predictable algorithms. Such algorithms do not depend on ad hoc parameters that have to be tuned whenever a new image is being generated. A number of plant image generation algorithms are now available in the literature that have achieved an impressive level of sophistication in many aspects, generating realistic looking images. One notable exception is the geometrical modeling of veins. This remains as an open problem in computer graphics. In this paper we review the state of art of the realistic simulation of plant venation systems from a geometric modeling perspective and propose a specified set of requirements for evaluating possible solutions for this problem.

Maintainability is one of the main targets of product development. Through simulating the actual maintenance process, maintainability problems can be identified by virtual reality technology. Most virtual reality softwares provide virtual human motion simulation functions, but the virtual human motion control methods of them are defective. In order to enhance virtual human motion control, maintenance task model was established in this paper, virtual human motion model was designed. Then a virtual human motion database based on Jack was developed by Tcl/Tk Python language, and it was applied to a real maintenance process. Furthermore, the maintenance process was simulated in Jack and the ergonomics of it were analyzed. The result showed that the motion database can be effectively applied to virtual maintenance simulation and make the maintenance process-related ergonomics analysis conveniently.

The human head is a significant part of the human body, with which we can recognize individuals from a vast universe of populations. Since the early 1970s, considerable effort has been devoted to computeraided modeling of human head for applications varied from realistic effect in computer graphics to custom model generation in modern manufacturing industries. However, realistic head modeling is still a challenge and continues to fascinate computer graphics researchers. The greatest difficulties in human head modeling result from the extremely complex geometric form of the human head. To generate realistic individualized models, most proposed head modeling techniques use the common approach of deforming a generic model into an individualized one, based on individual head information. There are various sources to obtain individual information, e.g., anthropometric data, range data and 2D pictures. Given the individual information, the quality of the resulting individualized model depends on the quality of the generic model and the deformation technique used. In our study, we observe that the mathematical form in which the generic model is represented strongly determines the deformation effect and, thus, determines the quality of the resulting individualized models. During the past few years, the multiresolution modeling technique has been demonstrated to be a powerful tool for highly detailed sculptured object modeling. In our work, we adopt the multiresolution technique for generic head modeling and propose a feature-based deformation technique. We show that using our technique we can generate highly realistic individualized head models with speed and efficiency. We also demonstrate that our proposed technique can result in great efficiency for a wide range of downstream applications.

Achieving an efficient realistic illumination is an important aim of research in computer graphics. In this paper a new parallel global illumination method for hybrid systems based on the hierarchical radiosity method is presented. Our solution allows the exploitation of systems that combine independent nodes with multiple cores per node. Thus, multiple nodes work in parallel in the computation of the global illumination for the same scene. Within each node, all the available computational cores are used through a shared-memory multithreading approach. The good results obtained in terms of speedup on several distributed-memory and shared-memory configurations show the versatility of our hybrid proposal.

Numerical simulations of vortex sheets have a long history. The major advantage of the vortex sheet model lies in the efficiency of its boundary integral formulation, which allows us to avoid expensive computations of volumetric equations in some important problems. Although some researchers in computer graphics have exploited this benefit, there seems to be ample room for further improvements to their methods in relation to new results achieved in the applied mathematics community. On the other hand, applied mathematicians also could gain insight into flexible treatment of moving surfaces, which are very common in the current CG community. In this paper, we give an overview of recent progress in numerical simulations of the motion of three-dimensional vortex sheets with surface tension and discuss open problems that interests researchers in both communities referring to important papers from graphics.

Spectral methods for mesh processing and analysis rely on the eigenvalues, eigenvectors, or eigenspace projections derived from appropriately defined mesh operators to carry out desired tasks. Early work in this area can be traced back to the seminal paper by Taubin in 1995, where spectral analysis of mesh geometry based on a combinatorial Laplacian aids our understanding of the low‐pass filtering approach to mesh smoothing. Over the past 15 years, the list of applications in the area of geometry processing which utilize the eigenstructures of a variety of mesh operators in different manners have been growing steadily. Many works presented so far draw parallels from developments in fields such as graph theory, computer vision, machine learning, graph drawing, numerical linear algebra, and high‐performance computing. This paper aims to provide a comprehensive survey on the spectral approach, focusing on its power and versatility in solving geometry processing problems and attempting to bridge the gap between relevant research in computer graphics and other fields. Necessary theoretical background is provided. Existing works covered are classified according to different criteria: the operators or eigenstructures employed, application domains, or the dimensionality of the spectral embeddings used. Despite much empirical success, there still remain many open questions pertaining to the spectral approach. These are discussed as we conclude the survey and provide our perspective on possible future research.

Posing character has always been playing an important role in character animation and interactive applications such as computer games. However, such a task is time-consuming and labor-intensive. In order to improve the efficiency in character posing, researchers in computer graphics have been working on a wide variety of semi- or fully automatic approaches in creating full-body poses, ranging from traditional approaches like inverse kinematics (IK), data-driven approaches which make use of captured motion data, as well as direct pose manipulation through intuitive interfaces. In this book chapter, we will introduce the aforementioned techniques and also discuss their applications in animation production.

Pose recognition in character animations is an important avenue of research in computer graphics. However, the current use of traditional artificial intelligence algorithms to recognize animation gestures faces hurdles such as low accuracy and speed. Therefore, to overcome the above problems, this paper proposes a real-time 3D pose recognition system, which includes both facial and body poses, based on deep convolutional neural networks and further designs a single-purpose 3D pose estimation system. First, we transformed the human pose extracted from the input image to an abstract pose data structure. Subsequently, we generated the required character animation at runtime based on the transformed dataset. This challenges the conventional concept of monocular 3D pose estimation, which is extremely difficult to achieve. It can also achieve real-time running speed at a resolution of 384 fps. The proposed method was used to identify multiple-character animation using multiple datasets (Microsoft COCO 2014, CMU Panoptic, Human3.6M, and JTA). The results indicated that the improved algorithm improved the recognition accuracy and performance by approximately 3.5% and 8–10 times, respectively, which is significantly superior to other classic algorithms. Furthermore, we tested the proposed system on multiple pose-recognition datasets. The 3D attitude estimation system speed can reach 24 fps with an error of 100 mm, which is considerably less than that of the 2D attitude estimation system with a speed of 60 fps. The pose recognition based on deep learning proposed in this study yielded surprisingly superior performance, proving that the use of deep-learning technology for image recognition has great potential.

The Advanced Volume Visualization Display (AVVD) research program is a joint research program between the Fraunhofer Center for Research in Computer Graphics, Inc. and Innovative Research and Development Corp. It is dedicated the application of the human visual system to real-time visualization of high- resolution volumetric sensor data sets. The AVVD program has successfully demonstrated its application to undersea imaging using data from the Naval Undersea Warfare Center -- Division Newport's High Resolution Array (HRA), and from the Naval Surface Warfare Center -- Coastal System Stations's Toroidal Volume Search Sonar (TVSS).

Fast display of realistic dynamic cloud scene is a challenging task for researchers in computer graphics. This paper describes a novel method of simulating animations of cloud. We first model the motion of cloud based on the physical theory of cloud formation. Then, the physical model of cloud is solved in discrete sparse grids. Thus, we can get approximate motion of cloud. Next, we advect texture image using the calculated velocity field to add the local detail of dynamic cloud scene. Here the texture image we used is Perlin noise map. The color of arbitrary point in the simulation space is got by calculating the product of the density texture and the regenerated Perlin noise texture. Finally, by changing different noise maps, realistic dynamic cloud scenes in different light environment are generated at high rendering rates.

Separation of the diffuse and specular components of observed reflectance has been an active area of research in computer graphics and vision, with major applications in reflectance modeling and scene analysis. Traditionally, researchers have investigated diffusespecular separation under point or directional illumination conditions while employing polarization and, in the case of dielectric materials, color space analysis techniques. Recently, Ma et al. [2007] introduced a technique for estimating high quality diffuse and specular normals and albedo maps (see Fig. 1, (a) & (d)) of a specular object using polarized spherical gradient illumination. However, the employed polarization technique imposes view-point restriction, and results in insufficient light levels for performance capture with high speed acquisition. Hence, in this work, we look into an alternate diffuse-specular separation technique for spherical gradients based on a data-driven reflectance model. Traditional separation techniques based on color space analysis focus on removing specular reflections from the observation for scene analysis [Mallick et al. 2005]. In contrast, we focus on obtaining high quality estimates of both the diffuse and the specular reflectance components.