3D modeling of the human upper limb including the biomechanics of joints, muscles and soft tissues

The challenge in virtual human modeling is to achieve the representation of the main human characteristics with as much realism as possible. Such achievements would allow the simulation and/or analysis of many virtual situations involving humans. Simulation is especially useful to derive information from the models so as to predict and/or reproduce the behaviors that would be observed in real situations. Computer methods in visualization and simulation have thus great potential for advances in medicine. The processes of strength generation and motion coordination are some of these phenomena for which there is still much remaining to be understood. The human shoulder is also probably the articulation of the human body which deserves more than any other to be named "terra incognita". Investigations towards the biomechanical modeling and simulation of the human upper limb are therefore presented in this study. It includes thorough investigation into the musculoskeletal anatomy and biomechanics of the human upper limb, into the biomechanical constitutive modeling of muscles and soft tissues, and into the nonlinear continuum mechanics and numerical methods, especially the incremental finite element methods, necessary for their simulation. On this basis, a 3-D biomechanical musculoskeletal human upper limb model has been designed using the Visible Human Data provided by the U.S. National Library of Medicine, and applied to the dynamic musculoskeletal simulation of the human upper limb. This research has been achieved in the context of the EU ESPRIT Project CHARM, whose objective has been to develop a comprehensive human animation resource database and a set of software tools allowing the modeling of the human complex musculoskeletal system and the simulation of its dynamics, including the finite element simulation of soft tissue deformation and muscular contraction. An investigation towards the application of this knowledge for the realistic modeling and animation of the upper limb in computer animation is then presented. The anatomical and biomechanical modeling of the scapulo-thoracic constraint and the shoulder joint sinus cones are proposed and applied to the realistic animation, using inverse kinematics, of a virtual skeleton and an anatomic musculoskeletal body model.

Automated body modeling from video sequences

Pascal Fua, Ralf Plänkers

Synthetic modeling of human bodies and the simulation of motion is a long-standing problem in animation and much work is involved before a near-realistic performance can be achieved. At present, it takes an experienced designer a very long time to build a complete and realistic model that closely resembles a specific person. Our ultimate goal is to automate the process and to produce realistic animation models given a set of video sequences. In this paper we show that, given video sequences of a person moving in front of the camera, we can recover shape information and joint locations. Both of which are essential to instantiate a complete and realistic model that closely resembles a specific person and without knowledge about the position of the articulations a character cannot be animated. This is achieved with minimal human intervention. The recovered shape and motion parameters can be used to reconstruct the original movement or to allow other animation models to mimic the subject's actions

1999

Human shoulder modeling including scapulo-thoracic constraint and joint sinus cones

Daniel Thalmann

In virtual human modeling, the shoulder is usually composed of clavicular, scapular and arm segments related by rotational joints. Although the model is improved, the realistic animation of the shoulder is hardly achieved. This is due to the fact that it is difficult to coordinate the simultaneous motion of the shoulder components in a consistent way. Also, the common use of independent one-degree of freedom (DOF) joint hierarchies does not properly render the 3-D accessibility space of real joints. On the basis of former biomechanical investigations, we propose an extended shoulder model including scapulo-thoracic constraint and joint sinus cones. As a demonstration, the model is applied, using inverse kinematics, to the animation of a 3-D anatomic muscled skeleton model

Elsevier2000

Realtime Face Tracking and Animation

Sofien Bouaziz

Capturing and processing human geometry, appearance, and motion is at the core of computer graphics, computer vision, and human-computer interaction. The high complexity of human geometry and motion dynamics, and the high sensitivity of the human visual system to variations and subtleties in faces and bodies make the 3D acquisition and reconstruction of humans in motion a challenging task. Digital humans are often created through a combination of 3D scanning, appearance acquisition, and motion capture, leading to stunning results in recent feature films. However, these methods typically require complex acquisition systems and substantial manual post-processing. As a result, creating and animating high-quality digital avatars entails long turn-around times and substantial production costs. Recent technological advances in RGB-D devices, such as Microsoft Kinect, brought new hopes for realtime, portable, and affordable systems allowing to capture facial expressions as well as hand and body motions. RGB-D devices typically capture an image and a depth map. This permits to formulate the motion tracking problem as a 2D/3D non-rigid registration of a deformable model to the input data. We introduce a novel face tracking algorithm that combines geometry and texture registration with pre-recorded animation priors in a single optimization. This led to unprecedented face tracking quality on a low cost consumer level device. The main drawback of this approach in the context of consumer applications is the need for an offline user-specific training. Robust and efficient tracking is achieved by building an accurate 3D expression model of the user's face who is scanned in a predefined set of facial expressions. We extended this approach removing the need of a user-specific training or calibration, or any other form of manual assistance, by modeling online a 3D user-specific dynamic face model. In complement of a realtime face tracking and modeling algorithm, we developed a novel system for animation retargeting that allows learning a high-quality mapping between motion capture data and arbitrary target characters. We addressed one of the main challenges of existing example-based retargeting methods, the need for a large number of accurate training examples to define the correspondence between source and target expression spaces. We showed that this number can be significantly reduced by leveraging the information contained in unlabeled data, i.e. facial expressions in the source or target space without corresponding poses. Finally, we present a novel realtime physics-based animation technique allowing to simulate a large range of deformable materials such as fat, flesh, hair, or muscles. This approach could be used to produce more lifelike animations by enhancing the animated avatars with secondary effects. We believe that the realtime face tracking and animation pipeline presented in this thesis has the potential to inspire numerous future research in the area of computer-generated animation. Already, several ideas presented in thesis have been successfully used in industry and this work gave birth to the startup company faceshift AG.

EPFL2015

Realtime Face Tracking and Animation

Sofien Bouaziz

EPFL2015