Dynamic Graphics Project
Dept. of Computer Science
University of Toronto
Supervisor: Karan Singh
My interests are anything computer graphics. In particular, I'm interested in surface modeling and deformation and the mathematics of shape: differential geometry, exterior calculus, and geometric algebra.
|Staggered Poses: A Character Motion Representation for
Detail-Preserving Editing of Pose and Coordinated Timing.
Patrick Coleman, Jacobo Bibliowicz, Karan Singh, Michael Gleicher.
Symposium on Computer Animation 2008.
We introduce staggered poses--a representation of character motion that explicitly encodes coordinated timing among movement features in different parts of a character's body. This representation allows us to provide sparse, pose-based controls for editing motion that preserve existing movement detail, and we describe how to edit coordinated timing among extrema in these controls for stylistic editing. The staggered pose representation supports the editing of new motion by generalizing keyframe-based workflows to retain high-level control after local timing and transition splines have been created. For densely-sampled motion such as motion capture data, we present an algorithm that creates a staggered pose representation by locating coordinated movement features and modeling motion detail using splines and displacement maps. These techniques, taken together, enable feature-based keyframe editing of dense motion data.[project] [pdf]
|Video Browsing by Direct Manipulation.
Pierre Dragicevic, Gonzalo Ramos, Jacobo Bibliowicz, Derek Nowrouzezahrai, Ravin Balakrishnan, Karan Singh.
SIGCHI Conference on Human Factors in Computing Systems 2008.
We present a method for browsing videos by directly drag-ging their content. This method brings the benefits of direct manipulation to an activity typically mediated by widgets. We support this new type of interactivity by: 1) automati-cally extracting motion data from videos; and 2) a new technique called relative flow dragging that lets users control video playback by moving objects of interest along their visual trajectory. We show that this method can out-perform the traditional seeker bar in video browsing tasks that focus on visual content rather than time.[project] [pdf]
|An Automated Rigging System for Facial Animation.
M.S. Thesis, Cornell University, 2005.
We present a system for the automated rigging of human face models, providing
a significant time savings for this arduous task. Our system takes advantage
of previous work which deforms a reference facial surface to conform to new face
models. In particular, we have matched our reference model to digitized human
faces. We parameterize the construction of the reference rig on the surface topology
of the reference model; thus, the rig can be procedurally reconstructed onto
deformed copies of the model.