Gabriel Taubin Brown University Holly Rushmeier, who’s served as associate editor in chief (AEIC) for special issues since 2007, has recently been appointed co-editor in chief of Eurographics’ Computer Graphics Forum, effective May 2010. Owing to her increased responsibilities and numerous other commitments, Holly has decided she’ll be unable to continue serving effectively in her current CG&A ...

Hair ingested by licking during cat grooming can eventually coalesce into solid masses in cat gastrointestinal tract. It is believed that dietary fibre might reduce formation of these trichobezoars (hairballs). The effects of two insoluble fibre sources added to kibble diets were evaluated with respect to trichobezoar faecal excretion. Thirty-two cats and four diets were used in a randomised bl...

Visualization is a powerful paradigm for exploratory data analysis. Visualizing large graphs, however, often results in a meaningless hairball. In this paper, we propose a different approach that helps the user adaptively explore large million-node graphs from a local perspective. For nodes that the user investigates, we propose to only show the neighbors with the most subjectively interesting ...

Visualization is a powerful paradigm for exploratory data analysis. Visualizing large graphs, however, often results in a meaningless hairball. In this paper, we propose a different approach that helps the user adaptively explore large million-node graphs from a local perspective. For nodes that the user investigates, we propose to only show the neighbors with the most subjectively interesting ...

We analyze a well known type of puzzle in planar geometry: given a planar shape, it is required to find a cut that divides the shape into two identical parts (up to rotation and translation). Clearly not all shapes can be so dissected and for some shapes that appear in puzzles the cutting curve is quite surprising and difficult to find. In this paper we first analyze the inverse problem of asse...

Visualization is a powerful paradigm for exploratory data analysis. Visualizing large graphs, however, often results in a meaningless hairball. In this paper, we propose a different approach that helps the user adaptively explore large million-node graphs from a local perspective. For nodes that the user investigates, we propose to only show the neighbors with the most subjectively interesting ...