H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 48 Citations 10,210 241 World Ranking 3184 National Ranking 143

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Algorithm

Reinhard Klein mainly focuses on Artificial intelligence, Computer vision, Computer graphics, Algorithm and Rendering. His Artificial intelligence research includes elements of Building model, Set and Pattern recognition. His study ties his expertise on Graph together with the subject of Computer vision.

His Tessellation, Real-time rendering and Shader study, which is part of a larger body of work in Computer graphics, is frequently linked to Cultural heritage, bridging the gap between disciplines. His biological study spans a wide range of topics, including Point cloud, Surface, Mathematical optimization and Geometric modeling. His Rendering research is multidisciplinary, relying on both Bidirectional reflectance distribution function, Bidirectional texture function, Texture mapping and Visualization.

His most cited work include:

  • Efficient RANSAC for Point‐Cloud Shape Detection (1141 citations)
  • 3D zernike descriptors for content based shape retrieval (276 citations)
  • Octree-based point-cloud compression (255 citations)

What are the main themes of his work throughout his whole career to date?

Reinhard Klein mainly investigates Artificial intelligence, Computer vision, Rendering, Computer graphics and Algorithm. He regularly links together related areas like Pattern recognition in his Artificial intelligence studies. His work is dedicated to discovering how Computer vision, Surface are connected with Representation and other disciplines.

His Rendering study integrates concerns from other disciplines, such as Visualization, Computer graphics and Texture memory. Visualization is closely attributed to Human–computer interaction in his work. His Algorithm research integrates issues from Polygon mesh, Mathematical optimization and Geometric modeling.

He most often published in these fields:

  • Artificial intelligence (48.77%)
  • Computer vision (42.90%)
  • Rendering (25.31%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (48.77%)
  • Computer vision (42.90%)
  • Visualization (11.73%)

In recent papers he was focusing on the following fields of study:

Reinhard Klein mainly focuses on Artificial intelligence, Computer vision, Visualization, Deep learning and Rendering. His Artificial intelligence study combines topics from a wide range of disciplines, such as Graphics and Pattern recognition. His studies deal with areas such as Surface and Surface reconstruction as well as Computer vision.

His Visualization study combines topics in areas such as Point cloud, Animation and Augmented reality, Human–computer interaction. He has included themes like Image resolution and Convolutional neural network in his Deep learning study. Computer graphics covers Reinhard Klein research in Rendering.

Between 2015 and 2021, his most popular works were:

  • Automatic reconstruction of parametric building models from indoor point clouds (138 citations)
  • A Two-Streamed Network for Estimating Fine-Scaled Depth Maps from Single RGB Images (116 citations)
  • State of the Art on 3D Reconstruction with RGB-D Cameras (98 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Algorithm

His scientific interests lie mostly in Artificial intelligence, Computer vision, Rendering, 3D reconstruction and RGB color model. He works mostly in the field of Artificial intelligence, limiting it down to concerns involving Pattern recognition and, occasionally, Motion estimation and Structure from motion. He performs multidisciplinary study in the fields of Computer vision and Focus via his papers.

His work in the fields of Rendering, such as Real-time rendering, overlaps with other areas such as Robot teleoperation. He focuses mostly in the field of RGB color model, narrowing it down to matters related to Depth map and, in some cases, Set, Convolutional neural network and Feature. His Integer research is multidisciplinary, incorporating perspectives in Algorithm and Point cloud.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Efficient RANSAC for Point‐Cloud Shape Detection

Ruwen Schnabel;Roland Wahl;Reinhard Klein.
Computer Graphics Forum (2007)

1718 Citations

3D zernike descriptors for content based shape retrieval

Marcin Novotni;Reinhard Klein.
acm symposium on solid modeling and applications (2003)

420 Citations

Octree-based point-cloud compression

Ruwen Schnabel;Reinhard Klein.
eurographics (2006)

365 Citations

3D Shape Matching with 3D Shape Contexts

Marcel Körtgen;Gil-Joo Park;Marcin Novotni;Reinhard Klein.
(2003)

360 Citations

Mesh reduction with error control

R. Klein;G. Liebich;W. Strasser.
ieee visualization (1996)

332 Citations

Shape retrieval using 3D Zernike descriptors

Marcin Novotni;Reinhard Klein.
Computer-aided Design (2004)

322 Citations

Acquisition, Synthesis, and Rendering of Bidirectional Texture Functions

Gero Müller;Jan Meseth;Mirko Sattler;Ralf Sarlette.
Computer Graphics Forum (2005)

227 Citations

Simple and efficient compression of animation sequences

Mirko Sattler;Ralf Sarlette;Reinhard Klein.
symposium on computer animation (2005)

214 Citations

Efficient and realistic visualization of cloth

Mirko Sattler;Ralf Sarlette;Reinhard Klein.
eurographics (2003)

195 Citations

Automatic reconstruction of parametric building models from indoor point clouds

Sebastian Ochmann;Richard Vock;Raoul Wessel;Reinhard Klein.
Computers & Graphics (2016)

195 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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