Augmented reality devices enable new approaches for character animation, e.g., given that character posing is three dimensional in nature it follows that interfaces with higher degrees-of-freedom (DoF) should outperform 2D interfaces. We present PoseMMR, allowing Multiple users to animate characters in a Mixed Reality environment, like how a stop-motion animator would manipulate a physical puppet, frame-by-frame, to create the scene. We explore the potential advantages of the PoseMMR can facilitate immersive posing, animation editing, version control and collaboration, and provide a set of guidelines to foster the development of immersive technologies as tools for collaborative authoring of character animation.
We present a system for fast and robust handovers with a robot character, together with a user study investigating the effect of robot speed and reaction time on perceived interaction quality. The system can match and exceed human speeds and confirms that users prefer human-level timing.
In this paper, we solve this problem by combining a window-based breakdown of the controls on the temporal dimension, together with a global wide search strategy that keeps locally sub-optimal samples throughout the optimization.
We present a method for adding artistic control to physics-based hair simulation.
We explore interacting with virtual characters in AR along real-world environments.
We introduce a simple and effective deep learning approach to automatically generate natural looking speech animation that synchronizes to input speech.
We present the potential of computational intelligence to empower authors and content creators in creating their own interactive animated stories.
Our system allows the user to act several loops of motion using a variety of capture devices and automatically extracts a looping cycle from this potentially noisy input.
We propose the concept of blendmaterials to give artists an intuitive means to account for changing material properties due to muscle activation.
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