Logo image
Back
Graspable parts recognition in Man-Made 3D shapes
Book chapter   Peer reviewed

Graspable parts recognition in Man-Made 3D shapes

H. Laga
Computer Vision – ACCV 2012: 11th Asian Conference on Computer Vision, Daejeon, Korea, November 5-9, 2012, Revised Selected Papers, Part II, Vol.7725, pp.552-564
Springer Berlin Heidelberg
2013
DOI: https://doi.org/10.1007/978-3-642-37444-9_43
url
Link to Published Version *Subscription may be requiredView

Abstract

We address the problem of automatic recognition of graspable parts in man-made 3D shapes, which exhibit high intra-class variability that cannot be captured with geometric descriptors alone. We observe that, in the presence of significant geometric and topological variations, the context of a part within a 3D shape provides important cues about its functionality. We propose to model the context as structural relationships between shape parts and use them, in addition to part geometry, as cues for identifying automatically the graspable parts. We design a set of spatial relationships that can be extracted from general shapes. Then, we propose a new similarity measure that captures a part context and enables better recognition of graspable parts. We use this property to design a classifier that learns the semantics of a shape part. We demonstrate that our approach outperforms the state-of-the-art approaches that are purely geometric-based.

Details

Metrics

45 Record Views
Logo image