Title

Playing With Puffball: Simple Scale-Invariant Inflation For Use In Vision And Graphics

Keywords

lighting; object recognition; shading; texture; textures

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. © 2012 ACM.

Publication Date

9-4-2012

Publication Title

Proceedings, SAP 2012 - ACM Symposium on Applied Perception

Number of Pages

47-54

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1145/2338676.2338686

Socpus ID

84865549730 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84865549730

This document is currently not available here.

Share

COinS