Electrokinetic motion of particles and cells in microchannels

This paper provides an overview of the electrokinetic phenomena associated with particles and cells in microchannel systems. The most important phenomena covered include electrophoresis, dielectrophoresis, and induced-charge electrokinetics. The latest development of these electrokinetic techniques for particle or cell manipulations in microfluidic systems is reviewed, in terms of the basic theories, mathematical models, numerical and experimental methods, and the key results/findings from the published literatures in the most recent decades. Some of the limitations associated with the negative field effects are discussed and the perspectives for the future investigations are summarized.     

Two-character motion analysis and synthesis

In this paper, we deal with the problem of synthesizing novel motions of standing-up martial arts such as Kickboxing, Karate, and Taekwondo performed by a pair of human-like characters while reflecting their interactions. Adopting an example-based paradigm, we address three non-trivial issues embedded in this problem: motion modeling, interaction modeling, and motion synthesis. For the first issue, we present a semi-automatic motion labeling scheme based on force-based motion segmentation and learning-based action classification. We also construct a pair of motion transition graphs each of which represents an individual motion stream. For the second issue, we propose a scheme for capturing the interactions between two players. A dynamic Bayesian network is adopted to build a motion transition model on top of the coupled motion transition graph that is constructed from an example motion stream. For the last issue, we provide a scheme for synthesizing a novel sequence of coupled motions, guided by the motion transition model. Although the focus of the present work is on martial arts, we believe that the framework of the proposed approach can be conveyed to other two-player motions as well.     

Hybrid motion graph for character motion synthesis

ObjectiveThis paper proposes a novel framework of Hybrid Motion Graph (HMG) for creating character animations, which enhances the graph-based structural control by motion field representations for efficient motion synthesis of diverse and interactive character animations.MethodsIn HMG framework, the motion template of each class is automatically derived from the training motions for capturing the general spatio-temporal characteristics of an entire motion class. Typical motion field for each class is then constructed. The smooth transitions among motion classes are then generated by interpolating the related motion templates with spacetime constraints. Finally, a hybrid motion graph is built by integrating the separate motion fields for each motion class into the global structural control of motion graph through smooth transition.ResultsIn motion synthesis stage, a character may freely ‘switch’ among different motion classes in the hybrid motion graph via smooth transitions between motion templates and ‘flow’ within each class through the continuous space of motion field with agile and the continuous control process.ConclusionExperimental results show that our framework realizes the fast connectivity among different motion classes and high responsiveness and interactivity for creating realistic character animation of rich behaviors with limited motion data and computational resources.     

Periodic motion synthesis and Fourier compression

Periodic motion is an important class of motion to synthesize, but it is not easy to compute it robustly and efficiently. In this paper we propose a simple, robust and efficient method to compute periodic motion from linear equation systems. The method first calculates the response of the system when an external periodic force is applied during one period, and then sums up the periodically shifted versions of the system response to provide the periodic solution. It is also shown that Fourier decomposition is very effective to compress the motion data without a drop in visual fidelity. © 1998 John Wiley & Sons, Ltd.     

Interpolation synthesis of articulated figure motion

Most conventional media depend on engaging and appealing characters. Empty spaces and buildings would not fare well as television or movie programming, yet virtual reality usually offers up such spaces. The problem lies in the difficulty of creating computer generated characters that display real time, engaging interaction and realistic motion. Articulated figure motion for real time computer graphics offers one solution to this problem. A common approach stores a set of motions and lets you choose one particular motion at a time. The article describes a process that greatly expands the range of possible motions. Mixing motions selected from a database lets you create a new motion to exact specifications. The synthesized motion retains the original motions' subtle qualities, such as the realism of motion capture or the expressive, exaggerated qualities of artistic animation. Our method provides a new way to achieve inverse kinematics capability-for example, placing the hands or feet of an articulated figure in specific positions. It proves useful for both real time graphics and prerendered animation production. The method, called interpolation synthesis, is based on motion capture data and it provides real time character motion for interactive entertainment or avatars in virtual worlds     

Character motion synthesis by principal component analysis and motion control interface by hands

In this paper, we propose an interactive character motion control interface that uses hands. Using their hands and fingers, the user can control a large number of degrees of freedom at the same time. We applied principal component analysis to a set of sample poses and assigned the extracted principal components to each degree of freedom of the hands (such as the hand positions and finger bending/extending angles). The user can control the blending weights of the principal components and deform the character's pose by moving their hands and bending/extending their fingers. We introduced pose and action controls, so that we can alter the standing pose and perform various actions with deformations. So that various types of actions were possible, we constructed a number of action models in advance. We introduced action model selection and action execution mechanisms. We developed methods for computing the feature vector, for applying principal component analysis, and for pose and action synthesis. In addition, we introduced a pose transition method for performing a step motion when necessary to prevent foot sliding. We present our experimental results and demonstrate the effectiveness of our interface. Copyright © 2015 John Wiley & Sons, Ltd.     

DexHand: dexterous hand manipulation motion synthesis for virtual reality

Virtual Reality - Natural object manipulation is one of the important human skills. However, generating natural hand manipulation motions that are adaptive to object shapes and the tasks at hand in...     

Automated eye motion using texture synthesis

Modeling human eyes requires special care. The goal of this paper is to synthesize realistic eye-gaze and blink motion, accounting for any possible correlations between the two. The technique adopts a data-driven texture synthesis approach to the problem of synthesizing realistic eye motion. The basic assumption is that eye gaze probably has some connection with eyelid motion, as well as with head motion and speech. But the connection is not strictly deterministic and would be difficult to characterize explicitly. A major advantage of the data-driven approach is that the investigator does not need to determine whether these apparent correlations actually exist. If the correlations occur in the data, the synthesis (properly applied) will reproduce them.     

Electrophoretic motion of two spherical particles in a rectangular microchannel

The electrophoretic motion of two spherical particles in an aqueous electrolyte solution in a small rectangular microchannel was studied in this paper. A theoretical model was developed to describe the electric field, the flow field, and the particle motion. A direct numerical simulation method using the finite element method is employed to solve the model. The simulation results clearly show how the presence of one particle influences the electric field, the flow field, and the motion of the adjacent particle. Such an influence weakens with the separation distance. In addition to the zeta potentials, the particles motion depends on their sizes: the smaller particle moves slightly faster. For a faster particle moving from behind of a slower particle, the simulation results show that the faster particle will climb and then pass the slower particle when the two particles centers are not located on the same line parallel to the applied electric field.     

Stochastic response of offshore towers to random sea waves and strong motion earthquakes

Presented is a stochastic method of analysis of offshore towers subjected separately to random sea waves and to strong motion earthquakes. The Pierson-Moskowitz wave height spectrum is used along with linear wave theory to define a stationary random sea state as caused by wind generated surface waves. A zero mean ergodic Gaussian process of finite duration is used to characterize horizontal ground acceleration caused by strong motion earthquakes. For each type of loading, full fluid structure interaction effects are included in stochastic analysis. Numerical results for 4 representative deep water towers having heights of 475, 675, 875 and 1,075 feet are presented. Particular emphasis is placed on the maximum or extreme values of total transverse shear and total overturning moment versus elevation above the base of each tower. The results of the earthquake analysis are compared with corresponding design code values and the role of ductility is briefly discussed.     

Flow-aware synthesis:A generic motion model for video frame interpolation

A popular and challenging task in video research,frame interpolation aims to increase the frame rate of video.Most existing methods employ a fixed motion model,...     

On-line motion synthesis and adaptation using a trajectory database

Autonomous robots cannot be programmed in advance for all possible situations. Instead, they should be able to generalize the previously acquired knowledge to operate in new situations as they arise. A possible solution to the problem of generalization is to apply statistical methods that can generate useful robot responses in situations for which the robot has not been specifically instructed how to respond. In this paper we propose a methodology for the statistical generalization of the available sensorimotor knowledge in real-time. Example trajectories are generalized by applying Gaussian process regression, using the parameters describing a task as query points into the trajectory database. We show on real-world tasks that the proposed methodology can be integrated into a sensory feedback loop, where the generalization algorithm is applied in real-time to adapt robot motion to the perceived changes of the external world.     

Example-based automatic music-driven conventional dance motion synthesis

We introduce a novel method for synthesizing dance motions that follow the emotions and contents of a piece of music. Our method employs a learning-based approach to model the music to motion mapping relationship embodied in example dance motions along with those motions' accompanying background music. A key step in our method is to train a music to motion matching quality rating function through learning the music to motion mapping relationship exhibited in synchronized music and dance motion data, which were captured from professional human dance performance. To generate an optimal sequence of dance motion segments to match with a piece of music, we introduce a constraint-based dynamic programming procedure. This procedure considers both music to motion matching quality and visual smoothness of a resultant dance motion sequence. We also introduce a two-way evaluation strategy, coupled with a GPU-based implementation, through which we can execute the dynamic programming process in parallel, resulting in significant speedup. To evaluate the effectiveness of our method, we quantitatively compare the dance motions synthesized by our method with motion synthesis results by several peer methods using the motions captured from professional human dancers' performance as the gold standard. We also conducted several medium-scale user studies to explore how perceptually our dance motion synthesis method can outperform existing methods in synthesizing dance motions to match with a piece of music. These user studies produced very positive results on our music-driven dance motion synthesis experiments for several Asian dance genres, confirming the advantages of our method.     

Controllable motion synthesis in a gaseous medium

The generation of realistic motion satisfying user-defined requirements is one of the most important goals of computer animation. Our aim in this paper is the synthesis of realistic, controllable motion for lightweight natural objects in a gaseous medium. We formulate this problem as a large-scale spacetime optimization with user controls and fluid motion equations as constraints. We have devised novel and effective methods to make this large optimization tractable. Initial trajectories are generated with data-driven synthesis based on stylistic motion planning. Smoothed particle hydrodynamics (SPH) is used during optimization to produce fluid simulations at a reasonable computational cost, while interesting vortex-based fluid motion is generated by recording the presence of vortices in the initial trajectories and maintaining them through optimization. Object rotations are refined as a postprocess to enhance the visual quality of the results. We demonstrate our techniques on a number of animations involving single or multiple objects.     

A system for the capture and synthesis of insect motion

We present an integrated system that enables the capture and synthesis of 3D motions of small scale dynamic creatures, typically insects and arachnids, in order to drive computer generated models. The system consists of a number of stages, initially, the acquisition of a multi-view calibration scene and synchronised video footage of a subject performing some action is carried out. A user guided labelling process, that can be semi-automated using tracking techniques and a 3D point generating algorithm, then enables a full metric calibration and captures the motions of specific points on the subject. The 3D motions extracted, which often come from a limited number of frames of the original footage, are then extended to generate potentially infinitely long, characteristic motion sequences for multiple similar subjects. Finally a novel path following algorithm is used to find optimal path along with coherent motion for synthetic subjects.     

Constrained synthesis of textural motion for articulated characters

Obtaining high-quality, realistic motions of articulated characters is both time consuming and expensive, necessitating the development of easy-to-use and effective tools for motion editing and reuse. We propose a new simple technique for generating constrained variations of different lengths from an existing captured or otherwise animated motion. Our technique is applicable to textural motions, such as walking or dancing, where the motion sequence can be decomposed into shorter motion segments without an obvious temporal ordering among them. Inspired by previous work on texture synthesis and video textures, our method essentially produces a reordering of these shorter segments. Discontinuities are eliminated by carefully choosing the transition points and applying local adaptive smoothing in their vicinity, if necessary. The user is able to control the synthesis process by specifying a small number of simple constraints.     

Emergent synthesis of motion patterns for locomotion robots

Emergence of stable gaits in locomotion robots is studied in this paper. A classifier system, implementing an instance-based reinforcement-learning scheme, is used for the sensory-motor control of an eight-legged mobile robot and for the synthesis of the robot gaits. The robot does not have a priori knowledge of the environment and its own internal model. It is only assumed that the robot can acquire stable gaits by learning how to reach a goal area. During the learning process the control system is self-organized by reinforcement signals. Reaching the goal area defines a global reward. Forward motion gets a local reward, while stepping back and falling down get a local punishment. As learning progresses, the number of the action rules in the classifier systems is stabilized to a certain level, corresponding to the acquired gait patterns. Feasibility of the proposed self-organized system is tested under simulation and experiment. A minimal simulation model that does not require sophisticated computational schemes is constructed and used in simulations. The simulation data, evolved on the minimal model of the robot, is downloaded to the control system of the real robot. Overall, of 10 simulation data seven are successful in running the real robot.