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Physically based simulation is often combined with geometric mesh animation to add realistic soft‐body dynamics to virtual characters. This is commonly done using constraint‐based simulation whereby a soft‐tissue simulation is constrained to geometric animation of a subpart (or otherwise proxy representation) of the character. We observe that standard constraint‐based simulation suffers from an important flaw that limits the expressiveness of soft‐body dynamics. Namely, under correct physics, the frequency and amplitude of soft‐tissue dynamics arising from constraints (“inertial amplitude”) are coupled, and cannot be adjusted independently merely by adjusting the material properties of the model. This means that the space of physically based simulations is inherently limited and cannot capture all effects typically expected by computer animators. For example, animators need the ability to adjust the frequency, inertial amplitude, gravity sag and damping properties of the virtual character, independently from each other, as these are the primary visual characteristics of the soft‐tissue dynamics. We demonstrate that independence can be achieved by transforming the equations of motion into a non‐inertial reference coordinate frame, then scaling the resulting inertial forces, and then converting the equations of motion back to the inertial frame. Such scaling of inertia makes it possible for the animator to set the character's inertial amplitude independently from frequency. We also provide exact controls for the amount of character's gravity sag, and the damping properties. In our examples, we use linear blend skinning and pose‐space deformation for geometric mesh animation, and the Finite Element Method for soft‐body constrained simulation; but our idea of scaling inertial forces is general and applicable to other animation and simulation methods. We demonstrate our technique on several character examples.

 

Precision modeling of the hand internal musculoskeletal anatomy has been largely limited to individual poses, and has not been connected into continuous volumetric motion of the hand anatomy actuating across the hand's entire range of motion. This is for a good reason, as hand anatomy and its motion are extremely complex and cannot be predicted merely from the anatomy in a single pose. We give a method to simulate the volumetric shape of hand's musculoskeletal organs to any pose in the hand's range of motion, producing external hand shapes and internal organ shapes that match ground truth optical scans and medical images (MRI) in multiple scanned poses. We achieve this by combining MRI images in multiple hand poses with FEM multibody nonlinear elastoplastic simulation. Our system models bones, muscles, tendons, joint ligaments and fat as separate volumetric organs that mechanically interact through contact and attachments, and whose shape matches medical images (MRI) in the MRI-scanned hand poses. The match to MRI is achieved by incorporating pose-space deformation and plastic strains into the simulation. We show how to do this in a non-intrusive manner that still retains all the simulation benefits, namely the ability to prescribe realistic material properties, generalize to arbitrary poses, preserve volume and obey contacts and attachments. We use our method to produce volumetric renders of the internal anatomy of the human hand in motion, and to compute and render highly realistic hand surface shapes. We evaluate our method by comparing it to optical scans, and demonstrate that we qualitatively and quantitatively substantially decrease the error compared to previous work. We test our method on five complex hand sequences, generated either using keyframe animation or performance animation using modern hand tracking techniques.