Dengming Zhu

Geometry-based control of fire simulation

High-level control of fire is very attractive to artists, as it facilitates a detail-free user interface to make desirable flame effects. In this paper, a unified framework is proposed for modeling and animating fire under general geometric constraints and evolving rules. To capture the fire projection on user’s model animation, we develop a modified closest-point method (MCPM) to handle dynamic situations while maintaining the robustness of the closest-point method. A control blue core (CBC) is designed and generated automatically from the fire projection at each time step. It translates the geometric constraints and the user-specified evolving rules into implicit control conditions. Our L-Speed function leverages CBC’s shape information and conducts the large-scale motion of fire, leaving the basic physically-based model to refine simulation details. The experimental results show the effectiveness of our method for modeling fire propagation along complex curves or surfaces, or forming a flaming shape and following its motion.

Least-squares fitting of multiple M -dimensional point sets

Based on the classic absolute orientation technique, a new method for least-squares fitting of multiple point sets in m-dimensional space is proposed, analyzed and extended to a weighted form in this paper. This method generates a fixed point set from k corresponding original m-dimensional point sets and minimizes the mean squared error between the fixed point set and these k point sets under the similarity transformation. Experiments and interesting applications are presented to show its efficiency and accuracy.

From motion capture data to character animation

In this paper, we propose a practical and systematical solution to the mapping problem that is from 3D marker position data recorded by optical motion capture systems to joint trajectories together with a matching skeleton based on least-squares fitting techniques. First, we preprocess the raw data and estimate the joint centers based on related efficient techniques. Second, a skeleton of fixed length which precisely matching the joint centers are generated by an articulated skeleton fitting method. Finally, we calculate and rectify joint angles with a minimum angle modification technique. We present the results for our approach as applied to several motion-capture behaviors, which demonstrates the positional accuracy and usefulness of our method.

Skeleton-based control of fluid animation

We present a skeleton-based control method for fluid animation. Our method is designed to provide an easy and intuitive control approach while producing visually plausible fluid behavior. In our method, users are allowed to control animated fluid with skeleton keyframes. Expected results are then obtained by driving fluid towards a sequence of targets specified in these keyframes. In order to solve for an optimal driving solution, we propose a keyframe matching model based on the transportation principle. Moreover, to ensure that the fluid actors move as rigid bodies while preserving liquid properties during animation, we introduce an approach of driving solid-like liquid motion. Finally, we embed the skeleton-based control method into the standard fluid animation, and apply it to control fluid actors’ motion as well as liquid shape deformation. Experimental results show that our method can generate natural-looking interesting fluid behavior with little additional cost.

Total least squares fitting of point sets in m-D

The absolute orientation technique, minimizing the mean squared error between two matched point sets under similarity transformations, has numerously applied in the areas of photogrammetry, robotics, object motion analysis as well as object pose estimation following recognition. Based on it, in this paper, a total least squares fitting algorithm, which generates a fixed point set from k corresponding original point sets and minimizes the mean squared error between the fixed point sets and these k point sets, is proposed and proved. Experiments and interesting applications are also presented to show its efficiency, accuracy and robustness.

On pair additivity of the depletion force

The depletion interaction between two and three big hard spheres in a small hard sphere fluid with volume fraction π/10 is calculated both from Monte Carlo simulations and the Asakura–Oosawa approximation. The Monte Carlo results are in good agreement with previous DFT results. The three-body interaction at this volume fraction of small hard spheres is found to be very small, which indicates that the pair additivity of the depletion force is a good approximation.

Realistically rendering polluted water

Polluted water is very common in our world. Vividly rendering polluted water can bring people real, different, and fancy feelings. Especially in under water imagery, taking polluted water into consideration will produce more plausible results. Polluted water consists of many kinds of pollutants, which interact with light differently and make water look turbid. The optical properties of polluted water change with the concentrations of pollutants significantly. In this paper, we provide a method to obtain the optical properties of polluted water, which makes a bio-optical model for polluted water and connects the optical parameters with water quality data, i.e., the concentrations of pollutants. Our method can estimate the optical properties of polluted water regardless of the kinds and the concentrations of pollutants in water. Polluted water is inhomogeneous and has multiple scattering effects. We use volumetric photon mapping to render it and provide a 3D weight-varying radiance estimate method for the photon mapping. This radiance estimate method can compute high-frequency effects easily, which can show more details of the pollution process. Experiments demonstrate that our approach can generate polluted water effects unachievable by standard rendering methods.

A robust method for analyzing the physical correctness of motion capture data

The physical correctness of motion capture data is important for human motion analysis and athlete training. However, until now there is little work that wholly explores this problem of analyzing the physical correctness of motion capture data. In this paper, we carefully discuss this problem and solve two major issues in it. Firstly, a new form of Newton-Euler equations encoded by quaternions and Euler angles which are very fit for analyzing the motion capture data are proposed. Secondly, a robust optimization method is proposed to correct the motion capture data to satisfy the physical constraints. We demonstrate the advantage of our method with several experiments.

Rigid‐motion‐inspired liquid character animation

We present a rigid‐motion‐inspired method for animating liquid characters in this paper. Our method allows an animator to control the motion of liquid characters with motion capture data that is widely used in rigid body animation. It animates the most visual interesting part of liquid character, that is, to preserve characters shape as well as produce enough liquid details. To this end, we build a two‐layer model to represent the character by two coaxial layers: the rigid kernel and the liquid shell. Different control paradigms are used for the two layers instead of applying homogeneous force that is common in previous approaches. By embedding the control algorithm to the Navier–Stokes equations, we compute the fluid velocity that drives the motion of the liquid character. Results show that the method is easy and intuitive to use while incurring little additional cost.Copyright

Real-time online learning of Gaussian mixture model for opacity mapping

Rendering volumetric scattering in real-time is a challenge due to the complex interactions between the light and the particles in the participating media. Assuming that a ray leaving the emitter is scattered only once along its path to the sensor, we propose to represent the extinction coefficient by a Gaussian mixture model. Then the model is trained with a large number of particles colliding that ray in an online way. A low-cost updating function based on the weighted maximum likelihood estimation is derived for the weighted stepwise expectation-maximization algorithm, which is fitted into the graphics pipeline as a stage of learning. This enables all those particles to contribute to the extinction on the fly without storing and sorting them together with respect to the emitter in a geometry pass. Our approach is able to accurately reconstruct the per-pixel transmittance of the opacity map for optically thick heterogeneous media in real-time but operate in bounded memory, using the recently introduced fragment shader critical section feature of the graphics processing unit.