Zhidong Xiao

Motion data correction and extrapolation using physical constraints

Optimization techniques have proven to be a powerful approach for generating new motions. In this paper, we present a physically based optimization method to synthesize motions by using motion capture data as input. We assume that the captured motion data is physically plausible. We start by defining and estimating the physical properties of human characters. The procedure of motion synthesis is from coarse to fine according to the objective function and physical constraints. Our motion synthesis is like a motion editing method, which is appropriate for motion correction and extrapolation. By this means, we can correct and eliminate unrealistic motion data.

Automatic Estimation of Skeletal Motion from Optical Motion Capture Data

Utilization of motion capture techniques is becoming more popular in the pipeline of articulated character animation. Based upon captured motion data, defining accurate joint positions and joint orientations for the movement of a hierarchical human-like character without using a pre-defined skeleton is still a potential concern for motion capture studios. In this paper, we present a method for automatically estimating and determining the topology of hierarchical human skeleton from optical motion capture data based on the human biomechanical information. Through the use of a novel per-frame based recursive method with joint angle minimization, human skeleton mapping from optical marker and joint angle rotations are achieved in real time. The output of motion data from a hierarchical skeleton can be applied for further character motion editing and retargeting.

Enhancing character posing by a sketch-based interaction

Sketch as the most intuitive and powerful 2D design method has been used by artists for decades. However it is not fully integrated into current 3D animation pipeline as the difficulties of interpreting 2D line drawing into 3D. Several successful research for character posing from sketch has been presented in the past few years, such as the Line of Action [Guay et al. 2013] and Sketch Abstractions [Hahn et al. 2015]. However both of the methods require animators to manually give some initial setup to solve the corresponding problems. In this paper, we propose a new sketch based character posing system which is more flexible and efficient. It requires less input from the user than the system from [Hahn et al. 2015]. The character can be easily posed no matter the sketch represents a skeleton structure or shape contours.

Real-time facial expression transfer with single video camera

Facial expression transfer has been actively researched in the past few years. Existing methods either suffer from depth ambiguity or require special hardware. We present a novel marker‐less, real‐time facial transfer method that requires only a single video camera. We develop a robust model, which is adaptive to user‐specific facial data. It computes expression variances in real time and rapidly transfers them onto a target character either from images or videos. Our method can be applied to videos without prior camera calibration and focal adjustment. It enables realistic online facial expression editing and performance transferring in many scenarios such as video conference, news broadcasting, lip‐syncing for song performances and so on. With low computational cost and hardware requirement, our method tracks a single user at an average of 38fps and runs smoothly even in web browsers. Copyright

Sketch-based human motion retrieval via selected 2D geometric posture descriptor

Abstract Sketch-based human motion retrieval is a hot topic in computer animation in recent years. In this paper, we present a novel sketch-based human motion retrieval method via selected 2-dimensional (2D) Geometric Posture Descriptor (2GPD). Specially, we firstly propose a rich 2D pose feature call 2D Geometric Posture Descriptor (2GPD), which is effective in encoding the 2D posture similarity by exploiting the geometric relationships among different human body parts. Since the original 2GPD is of high dimension and redundant, a semi-supervised feature selection algorithm derived from Laplacian Score is then adopted to select the most discriminative feature component of 2GPD as feature representation, and we call it as selected 2GPD. Finally, a posture-by-posture motion retrieval algorithm is used to retrieve a motion sequence by sketching several key postures. Experimental results on CMU human motion database demonstrate the effectiveness of our proposed approach.

3D content creation exploiting 2D character animation

While 3D animation is constantly increasing its popularity, 2D is still largely in use in animation production. In fact, 2D has two main advantages. The first one is economic, as it is more rapid to produce, having a dimension less to consider. The second one is important for the artists, as 2D characters usually have highly distinctive traits, which are lost in a 3D transposition. An iconic example is Mickey Mouse, whom ears appear circular no matter which way he is facing.

Posing 3D Models from Drawings

Inferring the 3D pose of a character from a drawing is a complex and under-constrained problem. Solving it may help automate various parts of an animation production pipeline such as pre-visualization. In this article, a novel way of inferring the 3D pose from a monocular 2D sketch is proposed. The proposed method does not make any external assumptions about the model, allowing it to be used on different types of characters. The inference of the 3D pose is formulated as an optimization problem and a parallel variation of the Particle Swarm Optimization algorithm called PARAC-LOAPSO is utilized for searching the minimum. Testing in isolation as well as part of a larger scene, the presented method is evaluated by posing a lamp, a horse, and a human character. The results show that this method is robust, highly scalable, and able to be extended to various types of models.

Repurpose 2D Character Animations for a VR Environment Using BDH Shape Interpolation

Virtual Reality technology has spread rapidly in recent years. However, its growth risks ending soon due to the absence of quality content, except for few exceptions. We present an original framework that allows artists to use 2D characters and animations in a 3D Virtual Reality environment, in order to give an easier access to the production of content for the platform. In traditional platforms, 2D animation represents a more economic and immediate alternative to 3D. The challenge in adapting 2D characters to a 3D environment is to interpret the missing depth information. A 2D character is actually flat, so there is not any depth information, and every body part is at the same level of the others. We exploit mesh interpolation, billboarding and parallax scrolling to simulate the depth between each body segment of the character. We have developed a prototype of the system, and extensive tests with a 2D animation production show the effectiveness of our framework.

Recent Progress of Computational Fluid Dynamics Modeling of Animal and Human Swimming for Computer Animation

A literature review is conducted on the Computational Fluid Dynamics (CFD) modeling of swimming. The scope is animated films and games, sports science, animal biological research, bio-inspired submersible vehicle design and robotic design. There are CFD swimming studies on animals (eel, clownfish, turtle, manta, frog, whale, dolphin, shark, trout, sunfish, boxfish, octopus, squid, jellyfish, lamprey) and humans (crawl, butterfly, backstroke, breaststroke, dolphin kick, glide). A benefit is the ability to visualize the physics-based effects of a swimmer’s motion, using key-frame or motion capture animation. Physics-based animation can also be used as a training tool for sports scientists in swimming, water polo and diving. Surface swimming is complex and considers the water surface shape, splashes, bubbles, foam, bubble coalescence, vortex shedding, solid-fluid coupling and body deformation. Only the Navier-Stokes fluid flow equations can capture these features. Two-way solid-fluid coupling between the swimmer and the water is modeled to be able to propel the swimmer forwards in the water. Swimmers are often modeled using articulated rigid bodies, thus avoiding the complexity of deformable body modeling. There is interesting potential research, including the effects of hydrodynamic flow conditions on a swimmer, and the use of motion capture data. The predominant approach for swimming uses grid-based fluid methods for better accuracy. Emerging particle and hybrid-based fluid methods are being increasingly used in swimming for better 3D fluid visualization of the motion of the water surface, droplets, bubbles and foam.

Fluid Simulation by the Smoothed Particle Hydrodynamics Method: A Survey

This paper presents a survey of Smoothed Particle Hydrodynamics (SPH) and its use in computational fluid dynamics. As a truly mesh-free particle method based upon the Lagrangian formulation, SPH has been applied to a variety of different areas in science, computer graphics and engineering. It has been established as a popular technique for fluid based simulations, and has been extended to successfully simulate various phenomena such as multi-phase flows, rigid and elastic solids, and fluid features such as air bubbles and foam. Various aspects of the method will be discussed: Similarities, advantages and disadvantages in comparison to Eulerian methods; Fundamentals of the SPH method; The use of SPH in fluid simulation; The current trends in SPH. The paper ends with some concluding remarks about the use of SPH in fluid simulations, including some of the more apparent problems, and a discussion on prospects for future work.