Manipulation of Motion Capture Animation by Characteristics

Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 2009

Animation data, from motion capture or other sources, is becoming increasingly available and provides high quality motion, but is difficult to customize for the needs of a particular application. This is especially true when stylistic changes are needed, for example, to reflect a character's changing mood, differentiate one character from another or meet the precise desires of an animator. We introduce a system for editing animation data that is particularly well suited to making stylistic changes. Our approach transforms the joint angle representation of animation data into a set of pose parameters more suitable for editing. These motion drives include position data for the wrists, ankles and center of mass, as well as the rotation of the pelvis. We also extract correlations between drives and body movement, specifically between wrist position and the torso angles. The system solves for the pose at each frame based on the current values of these drives and correlations using an efficient set of inverse kinematics and balance algorithms. An animator can interactively edit the motion by performing linear operations on the motion drives or extracted correlations, or by layering additional correlations. We demonstrate the effectiveness of the approach with various examples of gesture and locomotion.

Computational Science and Its Applications—ICCSA …, 2003

2020

In this paper we discuss a novel multidisciplinary method for computer animation, using motion capture ('mocap') as reference, combining techniques from 2D and 3D animation, and digital sculpting. Our method develops a process to create animation based on mocap data, without being restricted by standard practices that depend on existing rigged 3D models, allowing for visual expression and improvisation while taking advantage of naturalistic motion and interaction within a 3D environment. The standard mocap methodology for creating animation consists of retargeting (transferring) the recorded data from actors and performers to existing digital characters, providing them with movement. The motion is then polished and tweaked by animators, until the final result is achieved. The character's animation is the result of the captured performance and the original character design, but they are not created at the same time, as they are put together later on. Something similar happens with 3D computer animation: in order for animators to articulate characters into poses that are interpolated by the computer, a model of a character has to be built first. Here, the animators fully control the performance, but the design of the character pre-dates this process, and can only be modified within certain constraints. Mocap is bound by physics and naturalistic movements, animation can be exaggerated, weight and force have to be conveyed, rather than imposed. Both differ aesthetically but none of the approaches takes full advantage of 2D animation methods, where drawings dictate shape, form and motion at the same time. The characters here can be designed for the movement they perform in particular shots. This opens possibilities for a more experimental approach, where abstraction can exist. Our method combines the different disciplines and allows form to be created for each key pose, using digital sculpting tools for development and mocap as reference. Then, poses can be interpolated so the method is still interactive, allowing for experimentation. Using drawing as the starting point from the mocap data allows for greater understanding of the poses by studying the human figure in motion. This creates new opportunities for designing the animation, regarding shapes, forms and movement.

The Visual Computer, 2013

Quick creation of 3D character animations is an important task in game design, simulations, forensic animation, education, training, and more. We present a framework for creating 3D animated characters using a simple sketching interface coupled with a large, unannotated motion database that is used to find the appropriate motion sequences corresponding to the input sketches. Contrary to the previous work that deals with static sketches, our input sketches can be enhanced by motion and rotation curves that improve matching in the context of the existing animation sequences. Our framework uses animated sequences as the basic building blocks of the final animated scenes, and allows for various operations with them such as trimming, resampling, or connecting by use of blending and interpolation. A database of significant and unique poses, together with a two-pass search running on the GPU, allows for interactive matching even for large amounts of poses in a template database. The system provides intuitive interfaces, an immediate feedback, and poses very small requirements on the user. A user study showed that the system can be used by novice users with no animation experience or artistic talent, as well as by users with an animation background. Both groups were able to create animated scenes consisting of complex and varied actions in less than 20 minutes.

Computer Animation and Virtual Worlds, 2006

Human motion is difficult to create and manipulate because of the high dimensionality and spatiotemporal nature of human motion data. Recently, the use of large collections of captured motion data has added increased realism in character animation. In order to make the synthesis and analysis of motion data tractable, we present a low‐dimensional motion space in which high‐dimensional human motion can be effectively visualized, synthesized, edited, parameterized, and interpolated in both spatial and temporal domains. Our system allows users to create and edit the motion of animated characters in several ways: The user can sketch and edit a curve on low‐dimensional motion space, directly manipulate the character's pose in three‐dimensional object space, or specify key poses to create in‐between motions. Copyright © 2006 John Wiley & Sons, Ltd.

IEEE Computer Graphics and Applications, 1997

M ost 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.

2008 Digital Image Computing: Techniques and Applications, 2008

The motion capture technique is gathering more and more attention because of its powerful potential for providing lifelike motions in computer graphics (CG) animation via sample-based motion creating techniques. Since motion data is multi-dimensional and spatio-temporal data that is difficult to edit as desired, an effective scheme for reusing captured motion sets to create new motion is advantageous. Reusing a motion data set requires effective browsing and extraction techniques that enable the user to look up and capture the relations among the motion contents in the motion data set. We propose a new framework for a motion editing tool by focusing on the connectivity between motions and utilizing it as a filter to extract the desired motion contents from a motion database. The proposed system uses a tree structure for expressing possible connective motion paths in the motion database. The motion connective tree can be a useful user interface to browse and select a motion scenario by exploring the existing motion data sets in the database. Our prototype system demonstrates an easy-tounderstand interface to explore and quickly edit a motion data set by selecting icons of the motion tree nodes.

This paper presents a high-level parametric approach for synthesis of novel human animation sequences from short clips data. The parametric approach generates motions according to user-defined high-level motion parameters, such as speed, slope and direction, while maintaining the quality and realism of captured motions, and preserving the motion constraints. The approach allows simultaneous control over multiple motion parameters. This is also done with efficient computations. Animation sequences are synthesized by parametric blending, according to high-level parameters. The mapping between high-level parameters and low-level blending coefficients is automatically pre-computed, enabling efficient motion synthesis with high-level parametric control. This allows realistic synthesis of novel motions intuitively and without expert animation skills. Hence, the presented high-level parametric approach allows both novice and expert users/animators to define their desired motion using intui...

SIGGRAPH Asia conference proocedings, 2018

Motion capture is increasingly used in games and movies. However, it often requires editing before it can be used. Unfortunately, editing is laborious because of the low-level representation of the data. Existing motion editing methods accomplish modest changes, but larger edits require the artist to "re-animate" the motion by manually selecting a subset of the frames as keyframes. In this paper, we automatically find sets of frames that serve as keyframes for editing the motion. We formulate the problem of selecting an optimal set of keyframes as a type of shortest-path problem, and solve this problem using efficient dynamic programming. Our algorithm can simplify motion capture to around 10% of the original number of frames while retaining most of its detail. By simplifying animation with our algorithm, we realize a new approach to motion editing and stylization founded on the time-tested keyframe interface.

Lecture Notes in Computer Science, 2000

The growth of motion capture systems have contributed to the proliferation of human motion database, mainly because human motion is important in many applications, ranging from games entertainment and films to sports and medicine. However, the captured motions normally attend specific needs. As an effort for adapting and reusing captured human motions in new tasks and environments and improving the animator's work, we present and discuss a new data-driven constraintbased animation system for interactive human motion editing. This method offers the compelling advantage that it provides faster deformations and more natural-looking motion results compared to goal-directed constraint-based methods found in the literature.