Figure 8 - uploaded by Sung-Hee Lee
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Using motion capture data as a training tool for animators. The COM is outside the support polygon while the character turns.
Source publication
Physical realism is an important aspect of producing convincing 3D character animation. This is particularly true for live-action visual effects where animated characters occupy the same scene as the live actors. In such a scenario, a virtual character's movements must visually match the behavior and movements of the live environment, else the disc...
Context in source publication
Context 1
... it was useful to cre- ate videos that showed, for example, the proper location of the COM and COP (or zero-moment point) during walking, running, or other motions. Such training videos can effectively teach anima- tors how to interpret our system, as in Figure 8. Of course, the animator chooses whether to make the character act human-like. ...
Citations
This work addresses the development of a character animation editing method that accommodates animation changes while preserving the animator’s original artistic intent. Our goal is to give the artist control over the automatic editing of animations by extending them with artist-defined metadata. We propose a metadata representation that describes which aspects of an animation can be varied. To make the authoring process easier, we have developed an interface for specifying the metadata. Our method extracts a collection of trajectories of both effectors and objects for the animation. We approximate and parameterize the trajectories with a series of cubic Bézier curves. Then, we generate a set of high-level parameters for editing which are related to trajectory deformations. The only possible deformations are those that preserve the fine structure of the original motion. From the trajectories, we use inverse kinematics to generate a new animation that conforms to the user’s edits while preserving the overall character of the original.
The mission of animators is to create nuanced, high-quality character motions. To achieve this, the careful editing of animation curves---curves that determine how a series of keyframed poses are interpolated over time---is an important task. Manual editing affords full and precise control, but requires tedious and nonintuitive trials and errors. Numerical optimization can automate such exploration; however, automatic solutions cannot always be perfect, and it is difficult for animators to control optimization owing to its black-box behavior. In this paper, we present a new framework called optimization-guided motion editing, which is aimed at maintaining a sense of full control while utilizing the power of optimization. We have designed interactions and developed a set of mathematical formulations to enable them. We discuss the framework's potential by demonstrating several usage scenarios with our proof-of-concept system, named OptiMo.
In this paper, we propose a DigiLog space that combines physical real world and its mirrored world to realize a 4D+ augmented reality. To support this, a RGB-D-based feature map is designed which is robust to lighting changes and enables texture-less object detection and tracking. Then we suggest a real-time context of interest (CoI) registration method for dynamic augmented reality (AR) information visualization. Through these technologies, a user wearing AR glasses can seamlessly experience CoI-based AR information of the 4D+ mirror world while moving indoors or outdoors. Therefore, a human's activity can be spatially/temporally extended by sharing and experiencing the mirror world's useful information. This could be applicable to AR-based time/space-transcended smart work, next-generation experimental education, AR simulation, video-based information surveying, AR medical information, and AR entertainment
Due to the incomparable ability to increase realism in synthesizing the motion of virtual objects, physics simulation is increasingly adopted in augmented reality (AR) applications. In this paper, we show with experiments that, if physics simulation is naively employed in AR applications, visual artifacts diminishing the realism of a scene may occur when real and virtual objects collide. This is due to the intrinsic limitation of AR in that virtual objects cannot apply forces to the real objects. We discuss possible methods to alleviate this artifacts.
Real-time adaptation of a motion capture sequence to virtual environments with physical perturbations requires robust control strategies. This paper describes an optimal feedback controller for motion tracking that allows for on-the-fly re-planning of long-term goals and adjustments in the final completion time. We first solve an offline optimal trajectory problem for an abstract dynamic model that captures the essential relation between contact forces and momenta. A feedback control policy is then derived and used to simulate the abstract model online. Simulation results become dynamic constraints for online reconstruction of full-body motion from a reference. We applied our controller to a wide range of motions including walking, long stepping, and a squat exercise. Results show that our controllers are robust to large perturbations and changes in the environment.
