Name
Abstract | ||
|---|---|---|
We introduce a novel technique for the construction of a 3D character proxy, or canvas, directly from a 2D cartoon drawing and a user-provided correspondingly posed 3D skeleton. Our choice of input is motivated by the observation that traditional cartoon characters are well approximated by a union of generalized surface of revolution body parts, anchored by a skeletal structure. While typical 2D character contour drawings allow ambiguities in 3D interpretation, our use of a 3D skeleton eliminates such ambiguities and enables the construction of believable character canvases from complex drawings. Our canvases conform to the 2D contours of the input drawings, and are consistent with the perceptual principles of Gestalt continuity, simplicity, and contour persistence. We first segment the input 2D contours into individual body-part outlines corresponding to 3D skeletal bones using the Gestalt continuation principle to correctly resolve inter-part occlusions in the drawings. We then use this segmentation to compute the canvas geometry, generating 3D generalized surfaces of revolution around the skeletal bones that conform to the original outlines and balance simplicity against contour persistence. The combined method generates believable canvases for characters drawn in complex poses with numerous inter-part occlusions, variable contour depth, and significant foreshortening. Our canvases serve as 3D geometric proxies for cartoon characters, enabling unconstrained 3D viewing, articulation, and non-photorealistic rendering. We validate our algorithm via a range of user studies and comparisons to ground-truth 3D models and artist-drawn results. We further demonstrate a compelling gallery of 3D character canvases created from a diverse set of cartoon drawings with matching 3D skeletons. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2801134 | ACM Transactions on Graphics |
Keywords | Field | DocType |
Algorithms,Sketch-based modeling,2D characters | Computer vision,Surface of revolution,Computer graphics (images),Sketch-based modeling,Segmentation,Gestalt psychology,Artificial intelligence,Rendering (computer graphics),User studies,Mathematics | Journal |
Volume | Issue | ISSN |
34 | 5 | 0730-0301 |
Citations | PageRank | References |
10 | 0.50 | 32 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mikhail Bessmeltsev | 1 | 61 | 5.20 |
| William Chang | 2 | 75 | 3.47 |
| Nicholas Vining | 3 | 93 | 7.66 |
| Alla Sheffer | 4 | 3074 | 143.00 |
| Karan Singh | 5 | 1529 | 76.00 |