Disney Research Pittsburgh

This paper considers the design, construction, and example use of a new type of 3D printer which fabricates three-dimensional objects from soft fibers (wool and wool blend yarn). This printer allows the substantial advantages of additive manufacturing techniques (including rapid turn-around prototyping of physical objects and support for high levels of customization and configuration) to be employed with a new class of material.

In this paper, we present a shoulder design using a novel differential mechanism to counterbalance the arm while preserving an anthropomorphically favorable singularity configuration and natural range-of-motion. Furthermore, because the motors driving the shoulder are completely grounded, counterbalance masses or springs are easily placed away from the shoulder and low in the torso, improving mass distribution and balance.

We present a hybrid stochastic/deterministic optimization scheme that uses RJMCMC to perform stochastic search over the space of detection configurations, interleaved with deterministic computation of the optimal multi-frame data association for each proposed detection hypothesis.

In this paper, we present a method which can accurately determine the identity of a team from spatiotemporal player tracking data. We do this by utilizing a formation descriptor which is found by minimizing the entropy of role-specific occupancy maps.

In this paper, we propose an “augmented- Hidden Conditional Random Field” (a-HCRF) which incorporates the local observation within the HCRF which boosts its forecasting performance.

We propose a method of representing audience behavior through facial and body motions from a single video stream and use these motions to predict the rating for feature-length movies.

In this paper, we address the problem of jointly summarizing large-scale Flickr images and YouTube user videos.

We propose a weakly-supervised framework for object detection where we discover subcategories and the composites automatically with only traditional object-level category labels as input.

This paper studies the balancing of simple planar bipedal robot models in dynamic, unstable environments like seesaw, bongoboard and board on a curved floor.

This paper presents a novel universal balancing controller that successfully stabilizes a planar bipedal robot in dynamic, unstable environments like seesaw and bongoboards, and also in static environments like curved and flat floors.