H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 32 Citations 8,043 60 World Ranking 7463 National Ranking 3532

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Robotics

The scientist’s investigation covers issues in Artificial intelligence, Computer vision, RGB color model, Odometry and Pixel. His study in Feature extraction, Robustness, Robotics, Probabilistic logic and Mobile robot is carried out as part of his studies in Artificial intelligence. His Computer vision research is multidisciplinary, incorporating perspectives in Robot, Visual odometry and Codebook.

His Tactile sensor study in the realm of Robot interacts with subjects such as GRASP. His Odometry study integrates concerns from other disciplines, such as Monocular, Outlier, Motion estimation, Image registration and Inertial measurement unit. Jürgen Sturm interconnects Depth map, Augmented reality, Image texture, Entropy and Similarity measure in the investigation of issues within Pixel.

His most cited work include:

  • An evaluation of the RGB-D SLAM system (541 citations)
  • Dense visual SLAM for RGB-D cameras (529 citations)
  • 3-D Mapping With an RGB-D Camera (527 citations)

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

His primary areas of study are Artificial intelligence, Computer vision, Robot, RGB color model and Mobile robot. Jürgen Sturm integrates Artificial intelligence and Trajectory in his studies. His Computer vision study is mostly concerned with 3D reconstruction, Object, Pose, Signed distance function and Tracking.

His Robot research is multidisciplinary, incorporating elements of Cognitive neuroscience of visual object recognition, Bayesian network, Probabilistic framework and Human–computer interaction. His biological study spans a wide range of topics, including Feature extraction, Color image and Benchmark. In the field of Mobile robot, his study on Robot control, Robot learning and Odometry overlaps with subjects such as Visual perception.

He most often published in these fields:

  • Artificial intelligence (82.67%)
  • Computer vision (76.00%)
  • Robot (40.00%)

What were the highlights of his more recent work (between 2014-2019)?

  • Artificial intelligence (82.67%)
  • Computer vision (76.00%)
  • Segmentation (8.00%)

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

His primary areas of investigation include Artificial intelligence, Computer vision, Segmentation, Robot and 3D reconstruction. Artificial intelligence is often connected to Margin in his work. His study of Signed distance function is a part of Computer vision.

The concepts of his Segmentation study are interwoven with issues in Data mining and Filter. His Robot research includes elements of Point of interest, Visual inspection and Feature. His research on 3D reconstruction also deals with topics like

  • Motion planning which is related to area like Solid modeling,
  • Iterative reconstruction, which have a strong connection to RGB color model, Object, Representation and Change detection.

Between 2014 and 2019, his most popular works were:

  • ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans (153 citations)
  • Fully-Convolutional Point Networks for Large-Scale Point Clouds (64 citations)
  • Collision Avoidance for Quadrotors with a Monocular Camera (54 citations)

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

  • Artificial intelligence
  • Computer vision
  • Robotics

Jürgen Sturm focuses on Segmentation, Artificial intelligence, Context, Cloud computing and Point. As part of his studies on Artificial intelligence, Jürgen Sturm often connects relevant areas like Computer vision. His Context investigation overlaps with other areas such as Pattern recognition, Semantics, Probabilistic logic, Inference and Margin.

His research links Filter with Pattern recognition. His Cloud computing research spans across into fields like Benchmark, Data mining, Spatial analysis, Process and Point cloud. He carries out multidisciplinary research, doing studies in Point and Network architecture.

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

An evaluation of the RGB-D SLAM system

Felix Endres;Jurgen Hess;Nikolas Engelhard;Jurgen Sturm.
international conference on robotics and automation (2012)

827 Citations

Dense visual SLAM for RGB-D cameras

Christian Kerl;Jurgen Sturm;Daniel Cremers.
intelligent robots and systems (2013)

674 Citations

3-D Mapping With an RGB-D Camera

Felix Endres;Jurgen Hess;Jurgen Sturm;Daniel Cremers.
IEEE Transactions on Robotics (2014)

651 Citations

Robust odometry estimation for RGB-D cameras

Christian Kerl;Jurgen Sturm;Daniel Cremers.
international conference on robotics and automation (2013)

558 Citations

Semi-dense Visual Odometry for a Monocular Camera

Jakob Engel;Jürgen Sturm;Daniel Cremers.
international conference on computer vision (2013)

530 Citations

Camera-based navigation of a low-cost quadrocopter

Jakob Engel;Jurgen Sturm;Daniel Cremers.
intelligent robots and systems (2012)

420 Citations

Real-time visual odometry from dense RGB-D images

Frank Steinbrucker;Jurgen Sturm;Daniel Cremers.
international conference on computer vision (2011)

387 Citations

Scale-aware navigation of a low-cost quadrocopter with a monocular camera

Jakob Engel;Jürgen Sturm;Daniel Cremers.
Robotics and Autonomous Systems (2014)

257 Citations

Object identification with tactile sensors using bag-of-features

Alexander Schneider;Jurgen Sturm;Cyrill Stachniss;Marco Reisert.
intelligent robots and systems (2009)

247 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

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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