Motion Editing

Motion editing methods have been widely used to create realistic human animation, which is vital to maintain footplant constrains during motion editing process. In this paper, we present a simple but efficient way for footplant constraints detection. Existing methods for automatic footplant detection are all software-based which are sensitive to motion data noises. We improve this work by hardware instead. We equip the actor with a simple pressure trigger circuit under his shoes. Whenever the toes or heels of the actor touch the ground, the circuit will be switched on and this information will be captured by motion capture system. Combining this additional information with the ordinary captured motion data, we can identify footplant constraints effectively. Such additional information will then be saved into the output motion capture file and can be used conveniently by the user. The new framework we developed can provide more precise detection results than previous software-based methods. Moreover, by pre-computing the footplant constraints, the time for footplant constraints detection in previous software-based methods can be saved.

Time warping allows users to modify timing without affecting poses. It has many applications in animation systems for motion editing, such as rening motions to meet new timing constraints or modifying the acting of animated characters. However, time warping typically requires many manual adjustments to achieve the desired results. We present a technique which simplies this process by allowing time

3D Games frameworks usually have some type of Character Animation System based on a low level layer for animations and a high level layer related with the behavior and intelligence of characters. The low level is responsible for providing a way of obtaining animations and to play them correctly and suitable according to the needs of the high level. This paper presents the implementation of the low level layer of the Guff Framework. This system provides functionalities for obtaining animations based on the Doom3's MD5 models and the possibility of a fine tune post-design configuration stage, which allows game designers to set groups of animations for supplying the high level animation system, animationto-animation transitions and animations properties such as uniformity, evolution, and timing. Finally, a first approach to a high level animation system, based in a very simple finite state machine, is developed to show how the low level animation system can support the high level animation system.

In this paper, a computationally efficient parametric blending approach is presented with the application of enriching animation databases. This simplifies the process of creating an animation database, using fewer short clips, as many others can be generated appropriately and on demand, saving storage space and its associated problems.

3D Games frameworks usually have some type of Character Animation System based on a low level layer for animations and a high level layer related with the behavior and intelligence of characters. The low level is responsible for providing a way of obtaining animations and to play them correctly and suitable according to the needs of the high level. This paper presents the implementation of the low level layer of the Guff Framework. This system provides functionalities for obtaining animations based on the Doom3's MD5 models and the possibility of a fine tune post-design configuration stage, which allows game designers to set groups of animations for supplying the high level animation system, animationto-animation transitions and animations properties such as uniformity, evolution, and timing. Finally, a first approach to a high level animation system, based in a very simple finite state machine, is developed to show how the low level animation system can support the high level animation system.

Motion capture is a common method to create expressive motions for animated characters. In order to add flexibility when reusing motion data, many ways to modify its style have been developed. However, thorough evaluation of the resulting motions is often omitted. In this paper we present a questionnaire based method for evaluating visible emotions and styles in animated motion, and a set of algorithmic modifications to add emotional content to captured motion. Modifications were done by adjusting posture, motion path lengths and timings. The evaluation method was then applied to a set of acted and modified motions. The results show that a simple questionnaire is a useful tool to compare motions, and that expressivity of some emotions can be controlled by the proposed algorithms. However, we also found that motions should be evaluated using several describing dimensions simultaneously, as a single modification may have complex visible effects on the motion.

In this paper we present an approach to reduce the effort for planning robot motions by shifting the planning problem to a high-level representation. We combine classical sampling-based random tree planning with a reactive controller connecting sampling points with nontrivial trajectories, utilizing redundant DOFs to locally avoid obstacles. While the reactive planner operates locally on a short time scale, the complementary sampling-based method is able to find globally feasible solutions due to its larger preview horizon. Additionally, planning is done in a low-dimensional task space instead of the high-dimensional joint space. Comparing the average planning time and number of tree extensions for several scenarios and planning methods, we demonstrate that this hybrid planning approach is capable of solving a large fraction of planning queries while saving considerable planning time.

Our aim is to detect the point of release of a thrown virtual projectile in VR/AR. We capture the full-body motion of 18 participants throwing virtual projectiles and extract motion features, such as position, velocity, rotation and rotational velocity for arm joints. Frame-level binary classifiers that estimate the point of release are trained and evaluated using a metric that prioritizes detection timing to obtain a ranking of joints and motion features. We find that wrist joint and rotation motion feature are most accurate, which can can help when placing simple motion tracking sensors for real-time throw detection.

This paper presents an integrated set of tools to facilitate the manipulation and reuse of motion capture data. A functional representation in terms of nonuniform B-splines provides a compact and efficient description of motion sequences. A collection of B-spline curves attached to a hierarchical structure is used to represent the animation of articulated figures. A set of primitive operators acting on these curves and their application to motion editing is presented. We have successfully used these primitives to generate smooth transitions between motion sequences, motion interpolation and motion cyclification.

We present a novel approach to create stylised animations of gaseous phenomena. Existing computer-assisted systems employ computational physics-based approaches which generate 3D effects. Unfortunately, these effects usually don't look like traditional animation, nor can the user freely design the behaviour of the animation. Our approach combines benefits from existing 2D and 3D approaches integrating them in an unusual but effective way. Extending the application of particle systems, the particle paths vary both with time and with the 3D viewing direction. Rendering features such as smoothly varying common outlines and speedlines help to preserve the animator's artistic style. The incorporation into a structured 2D modelling and animation environment enables a stylised animation exhibiting a convincing frame-to-frame coherence and allows 3D camera movement without aliasing artefacts. The provided solution demonstrates how an animator can remain in full control of a stylised process for effects animation and how one framework is suitable for a wide range of effects.

Many applications in computer animation portray the motion of a human arm and torso. Often such applications can benefit from a combination of Inverse (IK) and Forward (FK) Kinematics controls to manipulate the arms of the model. The human arm is a ...

Many popular motion editing methods do not take physical principles into account potentially producing implausible motions. This paper introduces an efficient method for touching up edited motions to improve physical plausibility. We start by estimating a mass distribution consistent with reference motions known to be physically correct. The edited motion is then divided into ground and flight stages and adjusted to enforce appropriate physical laws for, respectively, zero moment point (ZMP) constraints and correct ballistic trajectory. Unlike previous methods, we do not solve a nonlinear optimization to calculate the adjustment. Instead, closed-form methods are used to construct a hierarchical displacement map which sequentially refines userspecified degrees of freedom at different scales. This is combined with standard methods for kinematic constraint enforcement, yielding an efficient and scalable editing method that allows users to model real human behaviors. The potential of our approach is demonstrated in a number of examples.

This paper presents an integrated set of tools to facilitate the manipulation and reuse of motion capture data. A functional representation in terms of nonuniform B-splines provides a compact and efficient description of motion sequences. A collection of B-spline curves attached to a hierarchical structure is used to represent the animation of articulated figures. A set of primitive operators acting on these curves and their application to motion editing is presented. We have successfully used these primitives to generate smooth transitions between motion sequences, motion interpolation and motion cyclification.

Utilization of motion capture techniques is becoming more popular in the pipeline of articulated character animation. Based upon captured motion data, defining accurate joints position and joints orientation for the movement of a hierarchical human-like character without using a pre-defined skeleton is still a potential concern for motion capture studio. In this paper, we present a method for automatically estimating hierarchical human skeleton from optical motion capture data. Our approach considers the marker group and the human biomechanical information to determine the topology of the character skeleton. The output of motion data from a hierarchical skeleton is able to be used for further character motion editing and retargeting.

This paper introduces a system for expressive locomotion generation that takes as input a set of sample locomotion clips and a motion path. Significantly, the system only requires a single sample of straight-path locomotion for each style modeled and can produce output locomotion for an arbitrary path with arbitrary motion transition points. For efficient locomotion generation, we represent each sample with a loop sequence which encapsulates its key style and utilize these sequences throughout the synthesis process. Several techniques are applied to automate the synthesis: foot-plant detection from unlabeled samples, estimation of an adaptive blending length for a natural style change, and a post-processing step for enhancing the physical realism of the output animation. Compared to previous approaches, the system requires significantly less data and manual labor, while supporting a large range of styles.

Performance has a spontaneity and "aliveness" that can be difficult to capture in more methodical animation processes such as keyframing. Access to performance animation has traditionally been limited to either low degree of freedom characters or required expensive hardware. We present a performance-based animation system for humanoid characters that requires no special hardware, relying only on mouse and keyboard input. We deal with the problem of controlling such a high degree of freedom model with low degree of freedom input through the use of correlation maps which employ 2D mouse input to modify a set of expressively relevant character parameters. Control can be continuously varied by rapidly switching between these maps. We present flexible techniques for varying and combining these maps and a simple process for defining them. The tool is highly configurable, presenting suitable defaults for novices and supporting a high degree of customization and control for experts. Animation can be recorded on a single pass, or multiple layers can be used to increase detail. Results from a user study indicate that novices are able to produce reasonable animations within their first hour of using the system. We also show more complicated results for walking and a standing character that gestures and dances.

This paper presents the results of a study using computer human modeling to examine machine appendage speed. The objective was to determine the impact of roof bolter machine appendage speed on the likelihood of the operator coming in contact with. A contact means two or more objects intersecting or touching each other, e.g., appendage makes contact with the operator's hand, arm, head or leg. Incident investigation reports do not usually contain enough information to aid in studying this problem and laboratory experiments with human subjects are also not feasible because of safety and ethical issues. As an alternative, researchers developed a computer model approach as the primary means to gather data. By simulating an operator's random behavior and machine's appendage velocity, researchers can study potential hazards of tasks where it is not possible to perform experiments with human subjects. Analysis information is helpful to the mining industry in terms of making recommendations that reduce the likelihood that roof-bolter operators experience injury due to contact with a moving boom. Data analysis of roof bolter simulations show that the virtual-operator's response time has little effect on the number of contacts experienced. Based on frequency and cross-tabulation, regardless of other variables, contact incidents were always greater when the boom was moving up, were always greater on the palm, and were always greater for the boom part of the machine. Also, regardless of boom speed, the 25 th-percentile-sized operators experienced more contacts than did other operator sizes. Furthermore, regardless of boom speed, the 152-cm mine seam experienced more contacts than did other seam heights tested. Results of a survival analytic approach suggest that controlling the boom speed is the most important factor in determining the risk of an operator making contact. Based on the data collected, boom speed greater than 41 cm/s results in a substantial increase in risk to the roof bolter operator and should probably be avoided. At speeds less than or equal to 25 cm/s are associated with a more modest relative risk, which represents an acceptable level of risk. Also, at speeds between 25 and 41 cm/s, there could be a particular boom speed in this range at which a significant inflection point in the relative risk estimates occurs. Based on the results, this issue needs to be addressed by future research.

Physics-based animation is increasingly being used to create realistic, autonomous animations. Although commercial systems have been developed that produce passive dynamics, lifelike creatures must have their internal forces and torques for locomotion actively controlled. Other simulation systems are applicable to only one type of object representation like articulated figures or deformable cloth.1

Skeletal animation being one of the most distinct technics in real-time computer graphic is constantly evolving, since the time it was first implemented. New features, methods of synthesis and processing are being actively worked on and shipped in commercial titles. One missing aspect of this subbranch of rendering is proper automatic validation for humanoid movements. In response to that niche a study was prepared. It consisted of typical industry standard animation environment, used state-of-the-art animations resources and run with repeatable results in controlled environment. On these bases motion data for selected animated joints were measured and stored. Collected test data was analyzed against biomechanical constraints of human body. With conclusion of promising results, further research and possible applications were proposed.

Natural motion of virtual characters is crucial in games and simulations. The quality of such motion strongly depends on the path the character walks and the animation of the character locomotion. Therefore, much work has been done on path planning and character animation. However, the combination of both fields has received less attention. Combining path planning and motion synthesis introduces several problems. A path generated by a path planner is often a simplification of the character movement. This raises the question which (body) part of the character should follow the path generated by the path planner and to what extent it should closely follow the path. We will show that enforcing the pelvis to follow the path will lead to unnatural animations and that our proposed solution, using path abstractions, generates significantly better animations.

An ordered series of control poses may be interpolated by a polyscrew (piecewise helical) rigid body motion composed of a series of screws, each interpolating a pair of consecutive control poses. The trajectory of each point during a screw motion segment is C ∞. Although a polyscrew is continuous, velocities are typically discontinuous at control poses when the motion switches between screws. We obtain a smooth motion by subdividing the polyscrew. Three subdivision schemes are proposed: the interpolating 4-point subdivision, the smooth cubic B-spline subdivision, and the new Jarek subdivision, an average of these two. Their implementation is trivial and their computation sufficiently fast for realtime subdivision and animation, which is particularly important for interactive motion editing.

This paper addresses an issue of solving customers' problems when applying evolutionary computation. Rather than the seemingly more impressive approach of wow-it-allevolved-from-nothing, tinkering with exisiting models can be a more pragmatic approach in doing so. Using interactive evolution, we experimentally validate this point on setting parameters of a human walk model for computer animation while previous applications are mostly about evolving motion controllers of far simpler creatures from scratch.

An ordered series of control poses may be interpolated by a polyscrew (piecewise helical) rigid body motion composed of a series of screws, each interpolating a pair of consecutive control poses. The trajectory of each point during a screw motion segment is C ∞. Although a polyscrew is continuous, velocities are typically discontinuous at control poses when the motion switches between screws. We obtain a smooth motion by subdividing the polyscrew. Three subdivision schemes are proposed: the interpolating 4-point subdivision, the smooth cubic B-spline subdivision, and the new Jarek subdivision, an average of these two. Their implementation is trivial and their computation sufficiently fast for realtime subdivision and animation, which is particularly important for interactive motion editing.

An ordered series of control poses may be interpolated by a polyscrew (piecewise helical) rigid body motion composed of a series of screws, each interpolating a pair of consecutive control poses. The trajectory of each point during a screw motion segment is C ∞. Although a polyscrew is continuous, velocities are typically discontinuous at control poses when the motion switches between screws. We obtain a smooth motion by subdividing the polyscrew. Three subdivision schemes are proposed: the interpolating 4-point subdivision, the smooth cubic B-spline subdivision, and the new Jarek subdivision, an average of these two. Their implementation is trivial and their computation sufficiently fast for realtime subdivision and animation, which is particularly important for interactive motion editing.

Designing a unified framework for simulating a broad variety of human behaviors has proven to be challenging. In this article, we present an approach for control system design that can generate animations of a diverse set of behaviors including walking, running, and a variety of gymnastic behaviors. We achieve this generalization with a balancing strategy that relies on a new form of inverted pendulum model (IPM), which we call the momentum-mapped IPM (MMIPM). We analyze reference motion capture data in a pre-processing step to extract the motion of the MMIPM. To compute a new motion, the controller plans a desired motion, frame by frame, based on the current pendulum state and a predicted pendulum trajectory. By tracking this time-varying trajectory, the controller creates a character that dynamically balances, changes speed, makes turns, jumps, and performs gymnastic maneuvers.

The aim of this work is to model and simulate the humanoid robot HOAP-3 in the OpenHRP3 platform. Our purpose is to create a virtual model of the robot so that different motions and tasks can be tested in different environments. This will be the first step before testing the motion patterns in the real HOAP-3. We use the OpenHRP3 platform for the creation and validation of the robot model and tasks. The procedure followed to reach this goal is detailed in this paper. In order to validate our experience, different walking motions are tested and the simulation results are compared with the experimental ones.

We present an application of a fast interactive inverse kinematics method as a dimensionality reduction for monocular human motion estimation. The inverse kinematics solver deals efficiently and robustly with box constraints and does not suffer from shaking artifacts. The presented motion estimation system uses a single camera to estimate the motion of a human. The results show that inverse kinematics can significantly speed up the estimation process, while retaining a quality comparable to a full pose motion estimation system. Our novelty lies primarily in use of inverse kinematics to significantly speed up the particle filtering. It should be stressed that the observation part of the system has not been our focus, and as such is described only from a sense of completeness. With our approach it is possible to construct a robust and computationally efficient system for human motion estimation.

It is time-consuming for an animator to explicitly model joint types and joint limits of articulated figures. In this paper we describe a simple and fast approach to automated joint estimation from motion capture data of articulated figures. Our method will make the joint modeling more efficient and less time consuming for the animator by providing a good starting estimate that can be fine-tuned or extended by the animator if she wishes, without restricting her artistic freedom. Our method is simple, easy to implement and specific for the types of articulated figures used in interactive animation such as computer games. Other work for joint limit modeling consider more complex and general purpose models. However, these are not immediately suitable for inverse kinematics skeletons used in interactive applications.

We investigate the use of multi-linear models to represent human motion data. We show that naturally occurring modes in several classes of motion can be used to efficiently represent the motions for various animation tasks, such as dimensionality reduction or synthesis of new motions by morphing. We show that especially for the approximations of motions by few components the reduction based on a multi-linear model can be considerably better than one obtained by principal component analysis (PCA).

Realistic movements of 3-Dimension (3D) human character play a very important role in virtual environment. Nonetheless, the main challenge in this field is to deform a new style of motions from original motion capture data input. The deformation of 3D human character movements contains complex parameters such as joints position and angle rotation in the generated motions. In this study, motion style deformation was controlled using multiple joint controller method. By using this method, the movements of 3D human character can be manipulated in real-time. Based on the results obtained, this system produced balance movements in the short sequences of 3D human character. This study can contribute in aiding the motion editing process to identify new style deformations by altering multiple joints in the real-time. This method is capable of producing realistic 3D human movements with a simple user interface.

Existing work on animation synthesis can be roughly split into two approaches, those that combine segments of motion capture data, and those that perform inverse kinematics. In this paper, we present a method for performing animation synthesis of an articulated object (e.g. human body and a dog) from a minimal set of body joint positions, following the approach of inverse kinematics. We tackle this problem from a learning perspective. Firstly, we address the need for knowledge on the physical constraints of the articulated body, so as to avoid the generation of a physically impossible poses. A common solution is to heuristically specify the kinematic constraints for the skeleton model. In this paper however, the physical constraints of the articulated body are represented using a hierarchical cluster model learnt from a motion capture database. Additionally, we shall show that the learnt model automatically captures the correlation between different joints through the simultaneous modelling their angles. We then show how this model can be utilised to perform inverse kinematics in a simple and efficient manner. Crucially, we describe how IK is carried out from a minimal set of end-effector positions. Following this, we show how this "learnt inverse kinematics" framework can be used to perform animation syntheses of different types of articulated structures. To this end, the results presented include the retargeting of a flat surface walking animation to various uneven terrains to demonstrate the synthesis of a full human body motion from the positions of only the hands, feet and torso. Additionally, we show how the same method can be applied to the animation synthesis of a dog using only its feet and torso positions.

The locomotion pattern is characterized by a translation displacement mostly occurring along the forward frontal body direction, whereas local repositioning with large reorientations , i.e. stepping, may induce translations both along the frontal and the lateral body directions (holonomy). We consider here a stepping pattern with initial and final null speeds within a radius of 40% of the body height and reorientation up to 180°. We propose a robust step detection method for such a context and identify a consistent intra-subject behavior in terms of the choice of starting foot and the number of steps.

In this paper we describe efforts to create a physically based system that automatically produces realistic realtime animations of walking figures, controlled by a neural network, the weights and functionality of which is evolved by genetic algorithm techniques. In traditional computer graphics, the animator is forced to use intuition about the physical world in specifying the motions of objects in a scene. The scenes must then be manually inspected for collisions. Since humans are sensitive to detecting anomalies in everyday physics, and real motions tend to be complex, manual control techniques have generally proven to be unsatisfactory. The use of dynamics greatly improves motion realism, and shifts control of the animation from specifying absolute positions of objects to applying forces and torques to the objects in the scene. In addition, it is possible for a dynamics system to automatically detect and respond to object collisions. This is a much more difficult task for a human to control. A neural network makes an ideal controller for the figures to be animated. Manually programming a neural network is yet more difficult for a human, and setting up training examples to make the neural network learn by back propagation is not straightforward, since there is no functional solution to be solved. Through the use of a genetic algorithm, one can determine the performance of a neural network as a whole, and select for whatever behavior is desired. Animator control is then directed through model design and behavior choices. In our system the genetic algorithm maximises the distance that the walking figure covers over a randomly generated terrain.

Many applications in computer animation portray the motion of a human arm and torso. Often such applications can benefit from a combination of Inverse (IK) and Forward (FK) Kinematics controls to manipulate the arms of the model. The human arm is a ...

Virtual humans are more and more used in VR applications, but their animation is still a challenge, especially if complex tasks must be carried out in interaction with the user. In many applications with virtual humans, credible virtual characters play a major role in presence. Motion editing techniques assume that the natural laws are intrinsically encoded in prerecorded trajectories and that modifications may preserve these natural laws, leading to credible autonomous actors. However, a complete knowledge of all the constraints is required to ensure continuity or to synchronize and blend several actions necessary to achieve a given task. We propose a framework capable of performing these tasks in an interactive environment that can change at each frame, depending on the user’s orders. This framework enables VR applications to animate from dozens of characters in real time for complex constraints, to hundreds of characters if only ground adaptation is performed. It offers the follo...

In this paper, we present an interactive motion deformation method to modify animations so that they satisfy a set of prioritized constraints. Our approach successfully handles the problem of retargetting, adjusting a motion, as well as adding significant changes to preexisting animations. We introduce the concept of prioritized constraints to avoid tweaking issues for competing constraints. Each frame is individually and smoothly adjusted to enforce a set of prioritized constraints. The iterative construction of the solution channels the convergence through intermediate solutions, enforcing the highest prioritized constraints first. In addition, we propose a new, simple formulation to control the position of the center of mass so that the resulting motions are physically plausible. Finally, we demonstrate that our method can address a wide range of motion editing problems.

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We introduce an acting-based animation system for creating and editing character animation at interactive speeds. Our system requires minimal training, typically under an hour, and is well suited for rapidly prototyping and creating expressive motion. A real-time motion-capture framework records the user's motions for simultaneous analysis and playback on a large screen. The animator's real-world, expressive motions are mapped into the character's virtual world. Visual feedback maintains a tight coupling between the animator and character. Complex motion is created by layering multiple passes of acting. We also introduce a novel motion-editing technique, which derives implicit relationships between the animator and character. The animator mimics some aspect of the character motion, and the system infers the association between features of the animator's motion and those of the character. The animator modifies the mimic by acting again, and the system maps the changes...

Motion capture involves recording the position and global orientation of joint sensors of a real object, in most cases a real person performing some human activities. This information is usually recorded at uniformly spaced instances of time, or as it is often called frame-by-frame. Then the recorded motion data sets are processed and mapped into a skeleton hierarchy of a virtual, computer simulated human figure to control the motion of the virtual human in the computer simulation. In the first part of the paper we review several new techniques developed to facilitate the manipulation, noise reduction, storage and reuse of captured data, which have a potential to reduce the overall cost of motion simulation and improve its realism. In the second part of the paper we consider the real life problem of reducing a worker’s risk from being hit by underground mining machinery in a confined space. We formulate a set of requirements to motion editing for this particular task and analyze the...