Abstract The synthesis of porous, lattice, or microstructure geometries has captured the attention of many researchers in recent years. Implicit forms, such as triply periodic minimal surfaces (TPMS) has captured a significant attention, recently, as tiles in lattices, partially because implicit forms have the potential for synthesizing with ease more complex topologies of tiles, compared to parametric forms. In this work, we show how variable offsets of implicit forms could be used in lattice design as well as lattice analysis, while graded wall and edge thicknesses could be fully controlled in the lattice and even vary within a single tile. As a result, (geometrically) heterogeneous lattices could be created and adapted to follow analysis results while maintaining continuity between adjacent tiles. We demonstrate this ability on several 3D models, including TPMS.

Boolean sum and ruling are two well-known construction operators for both parametric surfaces and trivariates. In many cases, the input freeform curves in or surfaces in are complex, and as a result, these construction operators might fail to build the parametric geometry so that it has a positive Jacobian throughout the domain. In this work, we focus on cases in which those constructors fail to build parametric geometries with a positive Jacobian throughout while the freeform input has a kernel point. We show that in the limit, for high enough degree raising or enough refinement, our construction scheme must succeed if a kernel exists. In practice, our experiments, on quadratic, cubic and quartic Bézier and B-spline curves and surfaces show that for a reasonable degree raising and/or refinement, the vast majority of construction examples are successful.

We present a complete microstructure tiling paradigm for V-rep models, or volumetric models consisting of trimmed trivariates. Existing methods (Massarwi et al., 2018) are employed to tile individual primitive tensor product trivariates in a conformal way, only to handle the intersection of the microstructure tiles with the trimming surfaces of the trivariates. One-to-one and two-to-one bridging tiles are then constructed along the trimmed zones, while tile-clipping is completely avoided. The Boolean operation cases of subtraction, intersection and union are considered. The result is a set of, regular in the interior, possibly heterogeneous, trivariates, that defines the whole microstructure arrangement. This result is fully compatible with iso-geometric analysis as well as heterogeneous additive manufacturing. Examples are presented, including of 3D printed heterogeneous microstructures.

Deformation of skin and muscle is essential for bringing an animated character to life. This deformation is difficult to animate in a realistic fashion using traditional techniques because of the subtlety of the skin deformations that must move appropriately for the character design. In this paper, we present an algorithm that generates natural, dynamic, and detailed skin deformation (movement and jiggle) from joint angle data sequences. The algorithm has two steps: identification of parameters for a quasi-static muscle deformation model, and simulation of skin deformation. In the identification step, we identify the model parameters using a musculoskeletal model and a short sequence of skin deformation data captured via a dense marker set. The simulation step first uses the quasi-static muscle deformation model to obtain the quasi-static muscle shape at each frame of the given motion sequence (slow jump). Dynamic skin deformation is then computed by simulating the passive muscle and soft tissue dynamics modeled as a mass–spring–damper system. Having obtained the model parameters, we can simulate dynamic skin deformations for subjects with similar body types from new motion data. We demonstrate our method by creating skin deformations for muscle co-contraction and external impacts from four different behaviors captured as skeletal motion capture data. Experimental results show that the simulated skin deformations are quantitatively and qualitatively similar to measured actual skin deformations.

Abstract The human shoulder complex is perhaps the most complicated joint in the human body being comprised of a set of three bones, muscles, tendons, and ligaments. Despite this anatomical complexity, computer graphics models for motion capture most often represent this joint as a simple ball and socket. In this paper, we present a method to determine a shoulder skeletal model that, when combined with standard skinning algorithms, generates a more visually pleasing animation that is a closer approximation to the actual skin deformations of the human body. We use a data‐driven approach and collect ground truth skin deformation data with an optical motion capture system with a large number of markers (200 markers on the shoulder complex alone). We cluster these markers during movement sequences and discover that adding one extra joint around the shoulder improves the resulting animation qualitatively and quantitatively yielding a marker set of approximately 70 markers for the complete skeleton. We demonstrate the effectiveness of our skeletal model by comparing it with ground truth data as well as with recorded video. We show its practicality by integrating it with the conventional rendering/animation pipeline.