#### Filter Results:

- Full text PDF available (54)

#### Publication Year

1950

2017

- This year (1)
- Last 5 years (9)
- Last 10 years (36)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Organism

Learn More

- Mark Pauly, Niloy Jyoti Mitra, Joachim Giesen, Markus H. Gross, Leonidas J. Guibas
- Symposium on Geometry Processing
- 2005

We present a novel approach for obtaining a complete and consistent 3D model representation from incomplete surface scans, using a database of 3D shapes to provide geometric priors for regions ofâ€¦ (More)

- Balint Miklos, Joachim Giesen, Mark Pauly
- ACM Trans. Graph.
- 2010

This paper addresses the fundamental problem of computing stable medial representations of 3D shapes. We propose a <i>spatially adaptive</i> classification of geometric features that yields a robustâ€¦ (More)

- Tamal K. Dey, Joachim Giesen, Samrat Goswami
- WADS
- 2003

Geometric shapes are identified with their features. For computational purposes a concrete mathematical definition of features is required. In this paper we use a topological approach, namelyâ€¦ (More)

- Joachim Giesen, Matthias John
- SODA
- 2003

Structuring finite sets of points is at the heart of computational geometry. Such point sets arise naturally in many applications. Examples in <b>R</b><sup>3</sup> are point sets sampled from theâ€¦ (More)

- Joachim Giesen, Uli Wagner
- Symposium on Computational Geometry
- 2003

We introduce the <i>adaptive neighborhood graph</i> as a data structure for modeling a smooth manifold <i>M</i> embedded in some (potentially very high-dimensional) Euclidean spaceâ€¦ (More)

- Joachim Giesen, Uli Wagner
- 2003

We introduce the adaptive neighborhood graph as a data structure for modeling a smooth manifold M embedded in some Euclidean space . We assume that M is known to us only through a finite sample P âŠ‚ Mâ€¦ (More)

- Tamal K. Dey, Joachim Giesen, Samrat Goswami, Wulue Zhao
- SODA
- 2002

There are many scientific and engineering applications where an automatic detection of shape dimension from sample data is necessary. Topological dimensions of shapes constitute an important globalâ€¦ (More)

- Tamal K. Dey, Joachim Giesen
- Symposium on Computational Geometry
- 2001

Current surface reconstruction algorithms perform satisfactorily on we ll-sampled, smooth surfaces without boundaries. However, these algorithms face difficulty with undersampling. Cases ofâ€¦ (More)

- Bernhard SchÃ¶lkopf, Joachim Giesen, Simon Spalinger
- NIPS
- 2004

We describe methods for computing an implicit model of a hypersurface that is given only by a finite sampling. The methods work by mapping the sample points into a reproducing kernel Hilbert spaceâ€¦ (More)

- Joachim Giesen, Balint Miklos, Mark Pauly, Camille Wormser
- Symposium on Computational Geometry
- 2009

We introduce the scale axis transform, a new skeletal shape representation for bounded open sets O ⊂ R<sup>d</sup>. The scale axis transform induces a family of skeletons that captures theâ€¦ (More)