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Disney Research

Disney Research Los Angeles

James Kennedy

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HI Robot: Human Intention-Aware Robot Planning for Safe and Efficient Navigation in Crowds

We present an algorithmic framework for the early classification of human intentions, and use it to accurately predict future human motions when planning the path of a robot in an environment that is shared with humans.

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Globally Continuous and Non-Markovian Activity Analysis from Videos

By using non-parametric Bayesian methods, we learn coupled spatial and temporal patterns with minimum prior knowledge.

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Walk the Talk: Coordinating Gesture with Locomotion for Conversational Characters

In this paper, we consider the problem of creating rich and varied conversational behaviors for data-driven animation of walking and jogging characters.

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Automultiscopic Displays Based on Orbital Angular Momentum of Light

We propose and demonstrate the viability of using OAM to create an automultiscopic 3D display.

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Morgan Pope

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FrankenFolk: Distinctiveness and Attractiveness of Voice and Motion

In this article, we conduct a series of experiments to evaluate the distinctiveness and attractiveness of human motions (face and body) and voices.

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Trending Paths: A Metric for Evaluating Crowd Simulation

We propose a new approach based on finding latent Path Patterns in both real and simulated data in order to analyze and compare them.

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Sackcloth or Silk? The Impact of Appearance vs Dynamics on the Perception of Animated Cloth

In this paper, we present a set of experiments in which we explore some factors that contribute to the perception of cloth, to determine how efficiency could be improved without sacrificing realism.

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Coding Two‐Dimensional Images with Orbital Angular Momentum of Light

We show that with selective coding OAM states, off‐axis points and spatial variables encoded with OAM are reproducible.

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