Name
Title | ||
|---|---|---|
Playing with Puffball: simple scale-invariant inflation for use in vision and graphics |
Abstract | ||
|---|---|---|
We describe how inflation, the act of mapping a 2D silhouette to a 3D region, can be applied in two disparate problems to offer insight and improvement: silhouette part segmentation and image-based material transfer. To demonstrate this, we introduce Puffball, a novel inflation technique, which achieves similar results to existing inflation approaches -- including smoothness, robustness, and scale and shift-invariance -- through an exceedingly simple and accessible formulation. The part segmentation algorithm avoids many of the pitfalls of previous approaches by finding part boundaries on a canonical 3-D shape rather than in the contour of the 2-D shape; the algorithm gives reliable and intuitive boundaries, even in cases where traditional approaches based on the 2D Minima Rule are misled. To demonstrate its effectiveness, we present data in which subjects prefer Puffball's segmentations to more traditional Minima Rule-based segmentations across several categories of silhouettes. The texture transfer algorithm utilizes Puffball's estimated shape information to produce visually pleasing and realistically synthesized surface textures with no explicit knowledge of either underlying shape. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2338676.2338686 | SAP |
Keywords | Field | DocType |
texture transfer algorithm,part boundary,novel inflation technique,canonical 3-d shape,estimated shape information,simple scale-invariant inflation,existing inflation approach,part segmentation algorithm,underlying shape,silhouette part segmentation,2-d shape,shading,texture,surface texture,object recognition,lighting,explicit knowledge,rule based,shift invariant,scale invariance | Graphics,Computer vision,Scale invariance,Silhouette,Simulation,Computer science,Segmentation,Explicit knowledge,Robustness (computer science),Maxima and minima,Artificial intelligence,Cognitive neuroscience of visual object recognition | Conference |
Citations | PageRank | References |
7 | 0.60 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nathaniel R. Twarog | 1 | 21 | 1.70 |
| Marshall F. Tappen | 2 | 1901 | 89.34 |
| Edward H. Adelson | 3 | 1768 | 320.52 |