Disney Research Pittsburgh

In this paper, we make progress toward both capabilities: we generate a foundational library of usable haptic vocabulary and do so with a methodology that allows ongoing additions to the library in a principled and effective way.

We demonstrate an interactive, human-powered energy harvesting system that converts a person's movements into electrical energy and then visible light. It explores the interaction of bodies, movement, materials, and electric power.

In this paper, we use ball and player tracking data from “Hawk-Eye” to discover unique player styles and predict within-point events.

In this paper, we describe a method to represent and discover adversarial group behavior in a continuous domain.

In this paper, we use ball and player tracking data from STATS SportsVU from the 2012-2013 NBA season to analyze offensive and defensive formations of teams.

We show that we can accurately segment a match into distinct game phases and detect highlights. (i.e. shots, corners, free-kicks, etc) completely automatically using a decision-tree formulation.

Our demonstration shows an interactive procedure for authoring haptic media content using the FE library, playing it back during interactions in the game, and broadcasting it to a group of guests.

In this paper, we present a humanoid robot which extracts and imitates the person-specific differences in motions, which we will call style.

This paper presents an offline, centralized motion planning algorithm for displaying stick figure animations by a group of mobile robots equipped with a light source.