H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 45 Citations 7,795 277 World Ranking 3627 National Ranking 163

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Pose, Motion capture and Tracking system. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning, Skinning and Pattern recognition. His work in Tracking, Motion estimation, Motion, Orientation and Structure from motion is related to Computer vision.

His work deals with themes such as Image processing, Motion analysis and Cluster analysis, which intersect with Pose. Bodo Rosenhahn works mostly in the field of Motion capture, limiting it down to concerns involving Animation and, occasionally, Nonlinear dimensionality reduction, Graphical model and Rendering. His studies examine the connections between Tracking system and genetics, as well as such issues in Object detection, with regards to Scale-invariant feature transform, Optical flow and Linear programming.

His most cited work include:

  • A Statistical Model of Human Pose and Body Shape (330 citations)
  • Motion capture using joint skeleton tracking and surface estimation (281 citations)
  • Automatic human model generation (218 citations)

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

His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Pose and Segmentation. His Artificial intelligence study frequently intersects with other fields, such as Machine learning. His study in Tracking, Tracking system, Motion estimation, Silhouette and Motion falls under the purview of Computer vision.

His Pattern recognition research integrates issues from Object detection, Image and Random forest. His 3D pose estimation and Articulated body pose estimation study in the realm of Pose interacts with subjects such as Conformal geometric algebra. His Segmentation study frequently draws connections between adjacent fields such as Subspace topology.

He most often published in these fields:

  • Artificial intelligence (79.35%)
  • Computer vision (51.39%)
  • Pattern recognition (24.18%)

What were the highlights of his more recent work (between 2016-2021)?

  • Artificial intelligence (79.35%)
  • Computer vision (51.39%)
  • Pattern recognition (24.18%)

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

Bodo Rosenhahn focuses on Artificial intelligence, Computer vision, Pattern recognition, Artificial neural network and Machine learning. His Artificial intelligence study focuses mostly on Convolutional neural network, Benchmark, Feature, Segmentation and Object detection. His study in Computer vision concentrates on Tracking, Tracking system, Pose, Monocular and Motion capture.

His Pose research includes elements of 2D to 3D conversion, Inertial measurement unit and Overfitting. His Pattern recognition research is multidisciplinary, incorporating elements of Vanishing point, Deep learning, Robustness and Contrast. His Artificial neural network research includes elements of Robust statistics and RANSAC.

Between 2016 and 2021, his most popular works were:

  • Recovering Accurate {3D} Human Pose in the Wild Using {IMUs} and a Moving Camera (203 citations)
  • Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs (121 citations)
  • Fusion of Head and Full-Body Detectors for Multi-object Tracking (97 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

His primary scientific interests are in Artificial intelligence, Computer vision, Convolutional neural network, Benchmark and Pattern recognition. The Artificial intelligence study combines topics in areas such as Machine learning and Detector. His studies in Tracking system, Tracking, Orientation, Inertial measurement unit and 3D pose estimation are all subfields of Computer vision research.

His study on Convolutional neural network also encompasses disciplines like

  • Ground truth which intersects with area such as Object detection, Feature learning, Cross entropy and Photogrammetry,
  • Feature extraction which intersects with area such as Feature, Class and Representation. His Benchmark research incorporates elements of MNIST database, Autoencoder, Data visualization and Visual surveillance. His research investigates the connection between Pattern recognition and topics such as Vanishing point that intersect with issues in Gaussian surface, Gnomonic projection, Robust statistics and RANSAC.

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

Motion capture using joint skeleton tracking and surface estimation

Juergen Gall;Carsten Stoll;Edilson de Aguiar;Christian Theobalt.
computer vision and pattern recognition (2009)

419 Citations

A Statistical Model of Human Pose and Body Shape

Nils Hasler;Carsten Stoll;Martin Sunkel;Bodo Rosenhahn.
Computer Graphics Forum (2009)

387 Citations

Automatic human model generation

Bodo Rosenhahn;Lei He;Reinhard Klette.
computer analysis of images and patterns (2005)

336 Citations

Optimization and Filtering for Human Motion Capture

Juergen Gall;Bodo Rosenhahn;Thomas Brox;Hans-Peter Seidel.
International Journal of Computer Vision (2010)

282 Citations

Everybody needs somebody: Modeling social and grouping behavior on a linear programming multiple people tracker

Laura Leal-Taixe;Gerard Pons-Moll;Bodo Rosenhahn.
international conference on computer vision (2011)

212 Citations

Recovering Accurate {3D} Human Pose in the Wild Using {IMUs} and a Moving Camera

Timo von Marcard;Roberto Henschel;Michael J. Black;Bodo Rosenhahn.
european conference on computer vision (2018)

203 Citations

Learning an Image-Based Motion Context for Multiple People Tracking

Laura Leal-Taixé;Michele Fenzi;Alina Kuznetsova;Bodo Rosenhahn.
computer vision and pattern recognition (2014)

200 Citations

Complementary Optic Flow

Henning Zimmer;Andrés Bruhn;Joachim Weickert;Levi Valgaerts.
energy minimization methods in computer vision and pattern recognition (2009)

163 Citations

Markerless Motion Capture with unsynchronized moving cameras

Nils Hasler;Bodo Rosenhahn;Thorsten Thormahlen;Michael Wand.
computer vision and pattern recognition (2009)

157 Citations

Three-Dimensional Shape Knowledge for Joint Image Segmentation and Pose Tracking

Bodo Rosenhahn;Thomas Brox;Joachim Weickert.
International Journal of Computer Vision (2007)

149 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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Top Scientists Citing Bodo Rosenhahn

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