Disney Research Pittsburgh

We present Mole Madness, a side-scrolling computer game that is built to explore multi-child language use, turn-taking, engagement, and social interaction in a fast-paced speech-operated activity.

This paper investigates the effects of adding gestures to a physical game between a human and a humanoid robot.

In this work, we review autonomous camera systems developed over the past twenty years.

We introduce a set of Game Context Features extracted from noisy detections to describe the current state of the match, such as how the players are spatially distributed.

In this paper, we present an unimodal interface concept that allows one person to cover live sporting action by controlling multiple cameras and and determining which view to broadcast.

In this paper, we develop a new model for recognizing human actions.

We propose an effective and efficient semi-supervised domain adaptation (SSDA) approach for addressing such more severe biases in the data.

In this paper, we propose a structured kernel machine approach to treat object detection and pose estimation jointly in a mutually beneficial way.

We propose a hierarchical generalization of the ddCRP which clusters data within groups based on distances between data items, and couples clusters across groups via distances based on aggregate properties of these local clusters.

We propose a new weakly-supervised structured learning approach for recognition and spatio-temporal localization of actions in video.