3D Motion Completion in Crowded Scenes

Crowded motions refer to multiple objects moving around and interacting such as crowds, pedestrians and etc. We capture crowded scenes using a depth scanner at video frame rates. Thus, our input is a set of depth frames which sample the scene over time. Processing such data is challenging as it is highly unorganized, with large spatio‐temporal holes due to many occlusions. As no correspondence is given, locally tracking 3D points across frames is hard due to noise and missing regions. Furthermore global segmentation and motion completion in presence of large occlusions is ambiguous and hard to predict. Our algorithm utilizes Gestalt principles of common fate and good continuity to compute motion tracking and completion respectively. Our technique does not assume any pre‐given markers or motion template priors. Our key‐idea is to reduce the motion completion problem to a 1D curve fitting and matching problem which can be solved efficiently using a global optimization scheme. We demonstrate our segmentation and completion method on a variety of synthetic and real world crowded scanned scenes.     

Skeleton based Vertex Connection Resampling for Bidirectional Path Tracing

Bidirectional path tracing is known to perform poorly for the rendering of highly occluded scenes. Indeed, the connection strategy between light and eye subpaths does not take into account the visibility factor, presenting no contribution for many sampled paths. To improve the efficiency of bidirectional path tracing, we propose a new method for adaptive resampling of connections between light and eye subpaths. Aiming for this objective, we build discrete probability distributions of light subpaths based on a skeleton of the empty space of the scene. In order to demonstrate the efficiency of our algorithm, we compare our method to both standard bidirectional path tracing and a recent important caching method.     

A Data‐Driven Framework for Visual Crowd Analysis

We present a novel approach for analyzing the quality of multi‐agent crowd simulation algorithms. Our approach is data‐driven, taking as input a set of user‐defined metrics and reference training data, either synthetic or from video footage of real crowds. Given a simulation, we formulate the crowd analysis problem as an anomaly detection problem and exploit state‐of‐the‐art outlier detection algorithms to address it. To that end, we introduce a new framework for the visual analysis of crowd simulations. Our framework allows us to capture potentially erroneous behaviors on a per‐agent basis either by automatically detecting outliers based on individual evaluation metrics or by accounting for multiple evaluation criteria in a principled fashion using Principle Component Analysis and the notion of Pareto Optimality. We discuss optimizations necessary to allow real‐time performance on large datasets and demonstrate the applicability of our framework through the analysis of simulations created by several widely‐used methods, including a simulation from a commercial game.     

Narrow Band FLIP for Liquid Simulations

The Fluid Implicit Particle method (FLIP) for liquid simulations uses particles to reduce numerical dissipation and provide important visual cues for events like complex splashes and small‐scale features near the liquid surface. Unfortunately, FLIP simulations can be computationally expensive, because they require a dense sampling of particles to fill the entire liquid volume. Furthermore, the vast majority of these FLIP particles contribute nothing to the fluid's visual appearance, especially for larger volumes of liquid. We present a method that only uses FLIP particles within a narrow band of the liquid surface, while efficiently representing the remaining inner volume on a regular grid. We show that a naïve realization of this idea introduces unstable and uncontrollable energy fluctuations, and we propose a novel coupling scheme between FLIP particles and regular grid which overcomes this problem. Our method drastically reduces the particle count and simulation times while yielding results that are nearly indistinguishable from regular FLIP simulations. Our approach is easy to integrate into any existing FLIP implementation.     

Multi‐layer Lattice Model for Real‐Time Dynamic Character Deformation

Due to the recent advancement of computer graphics hardware and software algorithms, deformable characters have become more and more popular in real‐time applications such as computer games. While there are mature techniques to generate primary deformation from skeletal movement, simulating realistic and stable secondary deformation such as jiggling of fats remains challenging. On one hand, traditional volumetric approaches such as the finite element method require higher computational cost and are infeasible for limited hardware such as game consoles. On the other hand, while shape matching based simulations can produce plausible deformation in real‐time, they suffer from a stiffness problem in which particles either show unrealistic deformation due to high gains, or cannot catch up with the body movement. In this paper, we propose a unified multi‐layer lattice model to simulate the primary and secondary deformation of skeleton‐driven characters. The core idea is to voxelize the input character mesh into multiple anatomical layers including the bone, muscle, fat and skin. Primary deformation is applied on the bone voxels with lattice‐based skinning. The movement of these voxels is propagated to other voxel layers using lattice shape matching simulation, creating a natural secondary deformation. Our multi‐layer lattice framework can produce simulation quality comparable to those from other volumetric approaches with a significantly smaller computational cost. It is best to be applied in real‐time applications such as console games or interactive animation creation.     

Implicit Formulation for SPH‐based Viscous Fluids

We propose a stable and efficient particle‐based method for simulating highly viscous fluids that can generate coiling and buckling phenomena and handle variable viscosity. In contrast to previous methods that use explicit integration, our method uses an implicit formulation to improve the robustness of viscosity integration, therefore enabling use of larger time steps and higher viscosities. We use Smoothed Particle Hydrodynamics to solve the full form of viscosity, constructing a sparse linear system with a symmetric positive definite matrix, while exploiting the variational principle that automatically enforces the boundary condition on free surfaces. We also propose a new method for extracting coefficients of the matrix contributed by second‐ring neighbor particles to efficiently solve the linear system using a conjugate gradient solver. Several examples demonstrate the robustness and efficiency of our implicit formulation over previous methods and illustrate the versatility of our method.     

IISPH‐FLIP for incompressible fluids

We propose to use Implicit Incompressible Smoothed Particle Hydrodynamics (IISPH) for pressure projection and boundary handling in Fluid‐Implicit‐Particle (FLIP) solvers for the simulation of incompressible fluids. This novel combination addresses two issues of existing SPH and FLIP solvers, namely mass preservation in FLIP and efficiency and memory consumption in SPH. First, the SPH component enables the simulation of incompressible fluids with perfect mass preservation. Second, the FLIP component efficiently enriches the SPH component with detail that is comparable to a standard SPH simulation with the same number of particles, while improving the performance by a factor of 7 and significantly reducing the memory consumption. We demonstrate that the proposed IISPH‐FLIP solver can simulate incompressible fluids with a quantifiable, imperceptible density deviation below 0.1%. We show large‐scale scenarios with up to 160 million particles that have been processed on a single desktop PC using only 15GB of memory. One‐ and two‐way coupled solids are illustrated.     

Environment‐Adaptive Contact Poses for Virtual Characters

We present a novel method to generate a virtual character's multi‐contact poses adaptive to the various shapes of the environment. Given the user‐specified center of mass (CoM) position and direction as inputs, our method finds the potential contacts for the character in the surrounding geometry of the environment and generates a set of stable poses that are contact‐rich. Major contributions of the work are in efficiently finding admissible support points for the target environment by precomputing candidate support points from a human pose database, and in automatically generating interactive poses that can maintain stable equilibrium. We develop the concept of support complexity to scale the set of precomputed support points by the geometric complexity of the environment. We demonstrate the effectiveness of our method by creating contact poses for various test cases of environments.     

Feedback control for rotational movements in feature space

Synthesizing controllers for rotational movements in feature space is an open research problem and is particularly challenging because of the need to precisely regulate the character's global orientation, angular momentum and inertia. This paper presents feature‐based controllers for a wide variety of rotational movements, including cartwheels, dives and flips. We show that the controllers can be made robust to large external disturbances by using a time‐invariant control scheme. The generality of the control laws is demonstrated by providing examples of the flip controller with different apexes, the diving controller with different heights and styles, the cartwheel controller with different speeds and straddle widths, etc. The controllers do not rely on any input motion or offline optimization.     

A Dimension‐reduced Pressure Solver for Liquid Simulations

This work presents a method for efficiently simplifying the pressure projection step in a liquid simulation. We first devise a straightforward dimension reduction technique that dramatically reduces the cost of solving the pressure projection. Next, we introduce a novel change of basis that satisfies free‐surface boundary conditions exactly, regardless of the accuracy of the pressure solve. When combined, these ideas greatly reduce the computational complexity of the pressure solve without compromising free surface boundary conditions at the highest level of detail. Our techniques are easy to parallelize, and they effectively eliminate the computational bottleneck for large liquid simulations.     

Locomotion Skills for Insects with Sample‐based Controller

Natural‐looking insect animation is very difficult to simulate. The fast movement and small scale of insects often challenge the standard motion capture techniques. As for the manual key‐framing or physics‐driven methods, significant amounts of time and efforts are necessary due to the delicate structure of the insect, which prevents practical applications. In this paper, we address this challenge by presenting a two‐level control framework to efficiently automate the modeling and authoring of insects’ locomotion. On the top level, we design a Triangle Placement Engine to automatically determine the location and orientation of insects’ foot contacts, given the user‐defined trajectory and settings, including speed, load, path and terrain etc. On the low‐level, we relate the Central Pattern Generator to the triangle profiles with the assistance of a Controller Look‐Up Table to fast simulate the physically‐based movement of insects. With our approach, animators can directly author insects’ behavior among a wide range of locomotion repertoire, including walking along a specified path or on an uneven terrain, dynamically adjusting to external perturbations and collectively transporting prey back to the nest.     

Multiple Vertex Next Event Estimation for Lighting in dense,forward‐scattering Media

We present a new technique called Multiple Vertex Next Event Estimation, which outperforms current direct lighting techniques in forward scattering, optically dense media with the Henyey‐Greenstein phase function. Instead of a one‐segment connection from a vertex within the medium to the light source, an entire sub path of arbitrary length can be created and we show experimentally that 4–10 segments work best in practice. This is done by perturbing a seed path within the Monte Carlo context. Our technique was integrated in a Monte Carlo renderer, combining random walk path tracing with multiple vertex next event estimation via multiple importance sampling for an unbiased result. We evaluate this new technique against standard next event estimation and show that it significantly reduces noise and increases performance of multiple scattering renderings in highly anisotropic, optically dense media. Additionally, we discuss multiple light sources and performance implications of memory‐heavy heterogeneous media.     

A Practical Method for High‐Resolution Embedded Liquid Surfaces

Combining high‐resolution level set surface tracking with lower resolution physics is an inexpensive method for achieving highly detailed liquid animations. Unfortunately, the inherent resolution mismatch introduces several types of disturbing visual artifacts. We identify the primary sources of these artifacts and present simple, efficient, and practical solutions to address them. First, we propose an unconditionally stable filtering method that selectively removes sub‐grid surface artifacts not seen by the fluid physics, while preserving fine detail in dynamic splashing regions. It provides comparable results to recent error‐correction techniques at lower cost, without substepping, and with better scaling behavior. Second, we show how a modified narrow‐band scheme can ensure accurate free surface boundary conditions in the presence of large resolution mismatches. Our scheme preserves the efficiency of the narrow‐band methodology, while eliminating objectionable stairstep artifacts observed in prior work. Third, we demonstrate that the use of linear interpolation of velocity during advection of the high‐resolution level set surface is responsible for visible grid‐aligned kinks; we therefore advocate higher‐order velocity interpolation, and show that it dramatically reduces this artifact. While these three contributions are orthogonal, our results demonstrate that taken together they efficiently address the dominant sources of visual artifacts arising with high‐resolution embedded liquid surfaces; the proposed approach offers improved visual quality, a straightforward implementation, and substantially greater scalability than competing methods.     

An Efficient Boundary Handling with a Modified Density Calculation for SPH

We propose a new boundary handling method for smoothed particle hydrodynamics (SPH). Previous approaches required the use of boundary particles to prevent particles from sticking to the boundary. We address this issue by correcting the fundamental equations of SPH with the integration of a kernel function. Our approach is able to directly handle triangle mesh boundaries without the need for boundary particles. We also show how our approach can be integrated into a position‐based fluid framework.     

TSS BVHs: Tetrahedron Swept Sphere BVHs for Ray Tracing Subdivision Surfaces

We present a novel, compact bounding volume hierarchy, TSS BVH, for ray tracing subdivision surfaces computed by the Catmull‐Clark scheme. We use Tetrahedron Swept Sphere (TSS) as a bounding volume to tightly bound limit surfaces of such subdivision surfaces given a user tolerance. Geometric coordinates defining our TSS bounding volumes are implicitly computed from the subdivided mesh via a simple vertex ordering method, and each level of our TSS BVH is associated with a single distance bound, utilizing the Catmull‐Clark scheme. These features result in a linear space complexity as a function of the tree depth, while many prior BVHs have exponential space complexity. We have tested our method against different benchmarks with path tracing and photon mapping. We found that our method achieves up to two orders of magnitude of memory reduction with a high culling ratio over the prior AABB BVH methods, when we represent models with two to four subdivision levels. Overall, our method achieves three times performance improvement thanks to these results. These results are acquired by our theorem that rigorously computes our TSS bounding volumes.     

A Practical and Controllable Hair and Fur Model for Production Path Tracing

We present an energy‐conserving fiber shading model for hair and fur that is efficient enough for path tracing. Our model adopts a near‐field formulation to avoid the expensive integral across the fiber, accounts for all high order internal reflection events with a single lobe, and proposes a novel, closed‐form distribution for azimuthal roughness based on the logistic distribution. Additionally, we derive, through simulation, a parameterization that relates intuitive user controls such as multiple‐scattering albedo and isotropic cylinder roughness to the underlying physical parameters.     

General and Robust Error Estimation and Reconstruction for Monte Carlo Rendering

Adaptive filtering techniques have proven successful in handling non‐uniform noise in Monte‐Carlo rendering approaches. A recent trend is to choose an optimal filter per pixel from a selection of non spatially‐varying filters. Nonetheless, the best filter choice is difficult to predict in the absence of a reference rendering. Our approach relies on the observation that the reconstruction error is locally smooth for a given filter. Hence, we propose to construct a dense error prediction from a small set of sparse but robust estimates. The filter selection is then formulated as a non‐local optimization problem, which we solve via graph cuts, to avoid visual artifacts due to inconsistent filter choices. Our approach does not impose any restrictions on the used filters, outperforms previous state‐of‐the‐art techniques and provides an extensible framework for future reconstruction techniques.     

Sparse high‐degree polynomials for wide‐angle lenses

Rendering with accurate camera models greatly increases realism and improves the match of synthetic imagery to real‐life footage. Photographic lenses can be simulated by ray tracing, but the performance depends on the complexity of the lens system, and some operations required for modern algorithms, such as deterministic connections, can be difficult to achieve. We generalise the approach of polynomial optics, i.e. expressing the light field transformation from the sensor to the outer pupil using a polynomial, to work with extreme wide angle (fisheye) lenses and aspherical elements. We also show how sparse polynomials can be constructed from the large space of high‐degree terms (we tested up to degree 15). We achieve this using a variant of orthogonal matching pursuit instead of a Taylor series when computing the polynomials. We show two applications: photorealistic rendering using Monte Carlo methods, where we introduce a new aperture sampling technique that is suitable for light tracing, and an interactive preview method suitable for rendering with deep images.     

Rich‐VPLs for Improving the Versatility of Many‐Light Methods

Many‐light methods approximate the light transport in a scene by computing the direct illumination from many virtual point light sources (VPLs), and render low‐noise images covering a wide range of performance and quality goals. However, they are very inefficient at representing glossy light transport. This is because a VPL on a glossy surface illuminates a small fraction of the scene only, and a tremendous number of VPLs might be necessary to render acceptable images. In this paper, we introduce Rich‐VPLs which, in contrast to standard VPLs, represent a multitude of light paths and thus have a more widespread emission profile on glossy surfaces and in scenes with multiple primary light sources. By this, a single Rich‐VPL contributes to larger portions of a scene with negligible additional shading cost. Our second contribution is a placement strategy for (Rich‐)VPLs proportional to sensor importance times radiance. Although both Rich‐VPLs and improved placement can be used individually, they complement each other ideally and share interim computation. Furthermore, both complement existing many‐light methods, e.g. Lightcuts or the Virtual Spherical Lights method, and can improve their efficiency as well as their application for scenes with glossy materials and many primary light sources.     

Robust Statistical Pixel Estimation

Robust statistical methods are employed to reduce the noise in Monte Carlo ray tracing. Through the use of resampling, the sample mean distribution is determined for each pixel. Because this distribution is uni‐modal and normal for a large sample size, robust estimates converge to the true mean of the pixel values. Compared to existing methods, less additional storage is required at each pixel because the sample mean distribution can be distilled down to a compact size, and fewer computations are necessary because the robust estimation process is sampling independent and needs a small input size to compute pixel values. The robust statistical pixel estimators are not only resistant to impulse noise, but they also remove general noise from fat‐tailed distributions. A substantial speedup in rendering can therefore be achieved by reducing the number of samples required for a desired image quality. The effectiveness of the proposed approach is demonstrated for path tracing simulations.