Visual Computing

We present an efficient method for augmenting keyframed character animations with physically-simulated secondary motion. Our method achieves a performance improvement of one to two orders of magnitude over previous work without compromising on quality.

We address the problem of stereoscopic content generation from light fields using multi-perspective imaging. Our proposed method takes as input a light field and a target disparity map, and synthesizes a stereoscopic image pair by selecting light rays that fulfill the given target disparity constraints. We formulate this as a variational convex optimization problem.

This paper addresses stereoscopic view generation from a light field. We present a framework that allows for the generation of stereoscopic image pairs with per-pixel control over disparity, based on multi-perspective imaging from light fields. The proposed framework is novel and useful for stereoscopic image processing and post-production.

Our work on “motion brushes” provides a new workflow for the creation and reuse of 3D animation with a focus on stylized movement and depiction. Conceptually, motion brushes expand existing brush models by incorporating hierarchies of 3D animated content including geometry, appearance information, and motion data as core brush primitives that are instantiated using a painting interface.

In this paper we propose a method for dynamic rescaling of music, inspired by recent works on image retargeting, video reshuffling and character animation in the computer graphics community. Given the desired target length of a piece of music and optional additional constraints such as position and importance of certain parts, we build on concepts from seam carving, video textures and motion graphs and extend them to allow for a global optimization of jumps in an audio signal.

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

We develop an algorithm for the efficient and stable simulation of large-scale elastic rod assemblies.

In this paper, we study observers' sensitivity to manipulations of overarm and underarm biological throwing animations.

Our novel `generate-and-rank' approach rapidly and semi-automatically generates data-driven fight scenes from high-level text descriptions composed of simple clauses and phrases. From a database of captured motions and its associated motion graph, we first generate a `cascade' of plausible scenes.

We describe in detail the required components, decisions, and new techniques that together make a usable, interactive tool for compositing HD video, paying special attention to running time and performance of each section.