Line geometry for 3D shape understanding and reconstruction

Helmut Pottmann; Michael Hofer; Boris Odehnal; Johannes Wallner

doi:10.1007/978-3-540-24670-1_23

Line geometry for 3D shape understanding and reconstruction

Helmut Pottmann^*, Michael Hofer, Boris Odehnal, Johannes Wallner

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

25 Scopus citations

Abstract

We understand and reconstruct special surfaces from 3D data with line geometry methods. Based on estimated surface normals we use approximation techniques in line space to recognize and reconstruct rotational, helical, developable and other surfaces, which are characterized by the configuration of locally intersecting surface normals. For the computational solution we use a modified version of the Klein model of line space. Obvious applications of these methods lie in Reverse Engineering. We have tested our algorithms on real world data obtained from objects as antique pottery, gear wheels, and a surface of the ankle joint.

Original language	English (US)
Pages (from-to)	297-309
Number of pages	13
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3021
DOIs	https://doi.org/10.1007/978-3-540-24670-1_23
State	Published - 2004
Externally published	Yes

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/978-3-540-24670-1_23

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title = "Line geometry for 3D shape understanding and reconstruction",

abstract = "We understand and reconstruct special surfaces from 3D data with line geometry methods. Based on estimated surface normals we use approximation techniques in line space to recognize and reconstruct rotational, helical, developable and other surfaces, which are characterized by the configuration of locally intersecting surface normals. For the computational solution we use a modified version of the Klein model of line space. Obvious applications of these methods lie in Reverse Engineering. We have tested our algorithms on real world data obtained from objects as antique pottery, gear wheels, and a surface of the ankle joint.",

author = "Helmut Pottmann and Michael Hofer and Boris Odehnal and Johannes Wallner",

year = "2004",

doi = "10.1007/978-3-540-24670-1_23",

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volume = "3021",

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AU - Pottmann, Helmut

AU - Hofer, Michael

AU - Odehnal, Boris

AU - Wallner, Johannes

PY - 2004

Y1 - 2004

N2 - We understand and reconstruct special surfaces from 3D data with line geometry methods. Based on estimated surface normals we use approximation techniques in line space to recognize and reconstruct rotational, helical, developable and other surfaces, which are characterized by the configuration of locally intersecting surface normals. For the computational solution we use a modified version of the Klein model of line space. Obvious applications of these methods lie in Reverse Engineering. We have tested our algorithms on real world data obtained from objects as antique pottery, gear wheels, and a surface of the ankle joint.

AB - We understand and reconstruct special surfaces from 3D data with line geometry methods. Based on estimated surface normals we use approximation techniques in line space to recognize and reconstruct rotational, helical, developable and other surfaces, which are characterized by the configuration of locally intersecting surface normals. For the computational solution we use a modified version of the Klein model of line space. Obvious applications of these methods lie in Reverse Engineering. We have tested our algorithms on real world data obtained from objects as antique pottery, gear wheels, and a surface of the ankle joint.

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U2 - 10.1007/978-3-540-24670-1_23

DO - 10.1007/978-3-540-24670-1_23

M3 - Article

AN - SCOPUS:33745947166

SN - 0302-9743

VL - 3021

SP - 297

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JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -

Line geometry for 3D shape understanding and reconstruction

Abstract

ASJC Scopus subject areas

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