H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 39 Citations 5,732 153 World Ranking 4709 National Ranking 36

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Geometry

Fredrik Kahl mostly deals with Artificial intelligence, Mathematical optimization, Algorithm, Computer vision and Global optimization. His studies in Mathematical optimization integrate themes in fields like Perspective, Geometry, Computational geometry and Cut. His Algorithm research includes elements of Segmentation and Photometric stereo.

His work on Computer vision is being expanded to include thematically relevant topics such as Robotics. His Global optimization research is multidisciplinary, relying on both Branch and bound, Optimization problem, Maxima and minima and Convex optimization. Fredrik Kahl interconnects Ground truth, Augmented reality and Visualization in the investigation of issues within Robot.

His most cited work include:

  • Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions (259 citations)
  • Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions (259 citations)
  • Multiple-View Geometry Under the {$L_\infty$}-Norm (214 citations)

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

His primary areas of investigation include Artificial intelligence, Computer vision, Mathematical optimization, Algorithm and Pattern recognition. His is involved in several facets of Artificial intelligence study, as is seen by his studies on Segmentation, Pose, Feature, Iterative reconstruction and Image segmentation. He works mostly in the field of Pose, limiting it down to topics relating to Augmented reality and, in certain cases, Ground truth.

In his work, Outlier is strongly intertwined with Robustness, which is a subfield of Computer vision. His Mathematical optimization research is multidisciplinary, relying on both Convex optimization and Maxima and minima. The Algorithm study combines topics in areas such as Transformation, Geometry, Rank and RANSAC.

He most often published in these fields:

  • Artificial intelligence (69.20%)
  • Computer vision (39.73%)
  • Mathematical optimization (25.00%)

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

  • Artificial intelligence (69.20%)
  • Computer vision (39.73%)
  • Pattern recognition (22.32%)

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

Fredrik Kahl mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Pose. His Convolutional neural network, Deep learning, Feature, Robustness and Ground truth investigations are all subjects of Artificial intelligence research. His Ground truth study incorporates themes from Augmented reality and Affine transformation.

The various areas that Fredrik Kahl examines in his Pattern recognition study include Gradient descent, Image, Invariant and Visual localization. His study in Pose is interdisciplinary in nature, drawing from both Outlier and Rendering. In his study, which falls under the umbrella issue of Outlier, Branch and bound and Mathematical optimization is strongly linked to Computational complexity theory.

Between 2015 and 2021, his most popular works were:

  • Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions (259 citations)
  • Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions (259 citations)
  • City-Scale Localization for Cameras with Known Vertical Direction (117 citations)

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

  • Artificial intelligence
  • Computer vision
  • Geometry

Artificial intelligence, Segmentation, Pattern recognition, Pose and Computer vision are his primary areas of study. His research on Artificial intelligence frequently links to adjacent areas such as Machine learning. His Segmentation study combines topics from a wide range of disciplines, such as Magnetic resonance imaging, Convolutional neural network, Computed tomography and Medical imaging.

His Pattern recognition study integrates concerns from other disciplines, such as Image and Invariant. He has included themes like Ground truth, Outlier and Augmented reality in his Pose study. His biological study spans a wide range of topics, including Intersection and Mobile robot.

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

Multiple-View Geometry Under the {$L_\infty$}-Norm

F. Kahl;R. Hartley.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2008)

327 Citations

Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions

Torsten Sattler;Will Maddern;Carl Toft;Akihiko Torii.
computer vision and pattern recognition (2018)

259 Citations

Global Optimization through Rotation Space Search

Richard I. Hartley;Fredrik Kahl.
International Journal of Computer Vision (2009)

231 Citations

Real-Time Camera Tracking and 3D Reconstruction Using Signed Distance Functions

Erik Bylow;Jürgen Sturm;Christian Kerl;Fredrik Kahl.
robotics science and systems (2013)

205 Citations

A minimal solution for relative pose with unknown focal length

Henrik Stewénius;David Nistér;Fredrik Kahl;Frederik Schaffalitzky.
Image and Vision Computing (2008)

163 Citations

Globally Optimal Estimates for Geometric Reconstruction Problems

Fredrik Kahl;Didier Henrion.
International Journal of Computer Vision (2007)

140 Citations

Branch-and-Bound Methods for Euclidean Registration Problems

C. Olsson;F. Kahl;M. Oskarsson.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

129 Citations

Cloud-Based Evaluation of Anatomical Structure Segmentation and Landmark Detection Algorithms: VISCERAL Anatomy Benchmarks

Oscar Jimenez-del-Toro;Henning Muller;Markus Krenn;Katharina Gruenberg.
IEEE Transactions on Medical Imaging (2016)

127 Citations

Non-sequential structure from motion

Olof Enqvist;Fredrik Kahl;Carl Olsson.
international conference on computer vision (2011)

126 Citations

City-Scale Localization for Cameras with Known Vertical Direction

Linus Svarm;Olof Enqvist;Fredrik Kahl;Magnus Oskarsson.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2017)

126 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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