We present a novel realtime algorithm to compute the trajectory of each pedestrian in a crowded scene. Our formulation is based on an adaptive scheme that uses a combination of deterministic and probabilistic trackers to achieve high accuracy and efficiency simultaneously. Furthermore, we integrate it with a multi-agent motion model and local interaction scheme to accurately compute the trajectory of each pedestrian. We highlight the performance and benefits of our algorithm on well-known datasets with tens of pedestrians.

We present a method to control the behavior of elastic, deformable material in a dynamic simulation. We introduce dynamic morph targets, the equivalent in dynamic simulation to the geometric morph targets in (quasi-static) modeling. Dynamic morph targets define the pose-dependent physical state of soft objects, including surface deformation and elastic and inertial properties. Given these morph targets, our algorithm then derives a dynamic model that can be simulated in time-pose-space, interpolating the dynamic morph targets at the input poses. Our method easily integrates with current modeling and animation pipelines: at different poses, an artist simply provides a set of dynamic morph targets. Whether these input states are physically plausible is completely up to the artist. The resulting deformable models expose fully dynamic, pose-dependent behavior, driven by the artist-provided morph targets, complete with inertial effects.

We present an efficient technique to model sound propagation accurately in an arbitrary 3D scene by numerically integrating the wave equation. We show that by performing an offline modal analysis and using eigenvalues from a refined mesh, we can simulate sound propagation with reduced dispersion on a much coarser mesh, enabling accelerated computation. Since performing a modal analysis on the complete scene is usually not feasible, we present a domain decomposition approach to drastically shorten the pre-processing time. We introduce a simple, efficient and stable technique for handling the communication between the domain partitions. We validate the accuracy of our approach against cases with known analytical solutions. With our approach, we have observed up to an order of magnitude speedup compared to a standard finite-difference technique.

Abstract Fast contact handling of soft articulated characters is a computationally challenging problem, in part due to complex interplay between skeletal and surface deformation. We present a fast, novel algorithm based on a layered representation for articulated bodies that enables physically‐plausible simulation of animated characters with a high‐resolution deformable skin in real time. Our algorithm gracefully captures the dynamic skeleton‐skin interplay through a novel formulation of elastic deformation in the pose space of the skinned surface. The algorithm also overcomes the computational challenges by robustly decoupling skeleton and skin computations using careful approximations of Schur complements, and efficiently performing collision queries by exploiting the layered representation. With this approach, we can simultaneously handle large contact areas, produce rich surface deformations, and capture the collision response of a character/s skeleton.

We have developed a physically-based VR system that enables users to interactively style dynamic virtual hair by using multiresolution simulation techniques and graphics hardware rendering acceleration for simulating and rendering hair in real time. With a 3D haptic interface, users can directly manipulate and position hair strands, as well as employ real-world styling applications (cutting, blow-drying, etc.) to create hairstyles more intuitively than previous techniques.

We present a novel algorithm to solve dense linear systems using graphics processors (GPUs). We reduce matrix decomposition and row operations to a series of rasterization problems on the GPU. These include new techniques for streaming index pairs, swapping rows and columns and parallelizing the computation to utilize multiple vertex and fragment processors. We also use appropriate data representations to match the rasterization order and cache technology of graphics processors. We have implemented our algorithm on different GPUs and compared the performance with optimized CPU implementations. In particular, our implementation on a NVIDIA GeForce 7800 GPU outperforms a CPU-based ATLAS implementation. Moreover, our results show that our algorithm is cache and bandwidth efficient and scales well with the number of fragment processors within the GPU and the core GPU clock rate. We use our algorithm for fluid flow simulation and demonstrate that the commodity GPU is a useful co-processor for many scientific applications.

Forward dynamics is central to physically-based simulation and control of articulated bodies. We present an adaptive algorithm for computing forward dynamics of articulated bodies: using novel motion error metrics, our algorithm can automatically simplify the dynamics of a multi-body system, based on the desired number of degrees of freedom and the location of external forces and active joint forces. We demonstrate this method in plausible animation of articulated bodies, including a large-scale simulation of 200 animated humanoids and multi-body dynamics systems with many degrees of freedom. The graceful simplification allows us to achieve up to two orders of magnitude performance improvement in several complex benchmarks.