Exploring collections of 3D models using fuzzy correspondences
Abstract
Large collections of 3D models from the same object class (e.g., chairs, cars, animals) are now commonly available via many public repositories, but exploring the range of shape variations across such collections remains a challenging task. In this work, we present a new exploration interface that allows users to browse collections based on similarities and differences between shapes in user-specified regions of interest (ROIs). To support this interactive system, we introduce a novel analysis method for computing similarity relationships between points on 3D shapes across a collection. We encode the inherent ambiguity in these relationships using fuzzy point correspondences and propose a robust and efficient computational framework that estimates fuzzy correspondences using only a sparse set of pairwise model alignments. We evaluate our analysis method on a range of correspondence benchmarks and report substantial improvements in both speed and accuracy over existing alternatives. In addition, we demonstrate how fuzzy correspondences enable key features in our exploration tool, such as automated view alignment, ROI-based similarity search, and faceted browsing.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jul 01, 2012
- Source ID
- 10.1145/2185520.2185550
Entities
People
- Niloy J. Mitra
- Stephen Diverdi
- Thomas Funkhouser
- Vladimir G. Kim
- Wilmot Li
Organizations
- Adobe
- Air Force Office of Scientific Research
- Division of Computer and Network Systems
- Division of Computing and Communication Foundations
- Princeton University
- Seventh Framework Programme
- University College London