H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 42 Citations 13,815 158 World Ranking 4037 National Ranking 186

Research.com Recognitions

Awards & Achievements

2019 - IEEE Fellow For contributions to machine vision for automated driving

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Algorithm

Christoph Stiller focuses on Artificial intelligence, Computer vision, Trajectory, Object detection and Advanced driver assistance systems. His Artificial intelligence research includes themes of Machine learning and Global Positioning System. His study in the fields of Stereopsis, Stereo cameras and Image segmentation under the domain of Computer vision overlaps with other disciplines such as Reliability.

His Trajectory research is multidisciplinary, relying on both Partially observable Markov decision process, Probabilistic logic, Solver and Motion planning. His Object detection research incorporates themes from Optical flow, Robotics, Inertial navigation system and Inertial measurement unit. He interconnects Bayesian network, Inference, Vehicle dynamics and Vehicle safety in the investigation of issues within Advanced driver assistance systems.

His most cited work include:

  • Vision meets robotics: The KITTI dataset (3500 citations)
  • StereoScan: Dense 3d reconstruction in real-time (766 citations)
  • Making Bertha Drive?An Autonomous Journey on a Historic Route (488 citations)

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

Christoph Stiller spends much of his time researching Artificial intelligence, Computer vision, Trajectory, Motion planning and Object detection. His Artificial intelligence study combines topics in areas such as Lidar, Machine learning and Pattern recognition. The Computer vision study combines topics in areas such as Kalman filter and Robustness.

His Trajectory research includes elements of Mathematical optimization and Vehicle dynamics. His work in Motion planning covers topics such as Real-time computing which are related to areas like Autonomous system. His study in Object detection is interdisciplinary in nature, drawing from both Grid, Detector and Benchmark.

He most often published in these fields:

  • Artificial intelligence (53.14%)
  • Computer vision (40.96%)
  • Trajectory (11.44%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (53.14%)
  • Computer vision (40.96%)
  • Trajectory (11.44%)

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

His primary areas of study are Artificial intelligence, Computer vision, Trajectory, Grid and Object detection. The study incorporates disciplines such as Task and Pattern recognition in addition to Artificial intelligence. His research integrates issues of Lidar and Grid reference in his study of Computer vision.

The various areas that Christoph Stiller examines in his Trajectory study include Matching, Overtaking and Vehicle dynamics. His research investigates the connection with Object detection and areas like Detector which intersect with concerns in Sensor fusion, Pyramid, Robustness and Feature. Christoph Stiller combines subjects such as Collision, Obstacle, Collision avoidance and Motion planning with his study of Control theory.

Between 2018 and 2021, his most popular works were:

  • INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps. (66 citations)
  • Realtime 3D Object Detection for Automated Driving Using Stereo Vision and Semantic Information (21 citations)
  • Accurate and Efficient Self-Localization on Roads using Basic Geometric Primitives (19 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, Motion planning, Object detection and Grid. He has researched Artificial intelligence in several fields, including Collision, Machine learning and GNSS applications. He has included themes like Salient, Convolutional neural network and Odometry in his Computer vision study.

His Motion planning research integrates issues from Automation, Systems engineering, Real-time computing, Intelligent driver model and Upstream. In his research, Data set is intimately related to Sensor fusion, which falls under the overarching field of Object detection. His biological study spans a wide range of topics, including Transformation, Segmentation, Image segmentation and Grid reference.

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

Vision meets robotics: The KITTI dataset

A Geiger;P Lenz;C Stiller;R Urtasun.
The International Journal of Robotics Research (2013)

3231 Citations

StereoScan: Dense 3d reconstruction in real-time

Andreas Geiger;Julius Ziegler;Christoph Stiller.
ieee intelligent vehicles symposium (2011)

1124 Citations

Making Bertha Drive?An Autonomous Journey on a Historic Route

Julius Ziegler;Philipp Bender;Markus Schreiber;Henning Lategahn.
IEEE Intelligent Transportation Systems Magazine (2014)

752 Citations

Three Decades of Driver Assistance Systems: Review and Future Perspectives

Klaus Bengler;Klaus Dietmayer;Berthold Farber;Markus Maurer.
ieee intelligent transportation systems (2014)

726 Citations

Estimating motion in image sequences

C. Stiller;J. Konrad.
IEEE Signal Processing Magazine (1999)

648 Citations

3D Traffic Scene Understanding From Movable Platforms

Andreas Geiger;Martin Lauer;Christian Wojek;Christoph Stiller.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2014)

381 Citations

Trajectory planning for Bertha — A local, continuous method

Julius Ziegler;Philipp Bender;Thao Dang;Christoph Stiller.
intelligent vehicles symposium (2014)

342 Citations

Segmentation of 3D lidar data in non-flat urban environments using a local convexity criterion

Frank Moosmann;Oliver Pink;Christoph Stiller.
ieee intelligent vehicles symposium (2009)

307 Citations

Team AnnieWAY's autonomous system for the 2007 DARPA Urban Challenge

Sören Kammel;Julius Ziegler;Benjamin Pitzer;Moritz Werling.
Journal of Field Robotics (2008)

292 Citations

Velodyne SLAM

Frank Moosmann;Christoph Stiller.
ieee intelligent vehicles symposium (2011)

232 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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