Stefan Gehrig

About

Stefan Gehrig is a distinguished researcher whose work sits at the intersection of computer vision, stereo perception, and intelligent transportation systems. Over more than a decade of prolific research, he has made foundational contributions to how autonomous and semi-autonomous vehicles perceive and respond to their environment. Gehrig's most celebrated work, "6D-Vision: Fusion of Stereo and Motion for Robust Environment Perception" (2005, 201 citations), established a powerful framework for combining depth and motion cues — a cornerstone concept that continues to influence modern autonomous driving pipelines. His investigations into vehicle-following systems and collision avoidance (105 citations) directly shaped the development of adaptive cruise control and platooning technologies deployed in real-world intelligent vehicles today. A recurring theme across his portfolio is making stereo vision faster, more reliable, and practically deployable. His contributions to Semi-Global Matching optimization (74 citations), stereo confidence estimation (90 citations), and robustness under calibration imperfections (56 citations) reflect a researcher deeply committed to bridging algorithmic theory and real-world performance. His work on adverse weather stereo vision further demonstrates his drive to address challenging edge cases critical for safety. With nearly 700 total citations, Gehrig's research has meaningfully advanced the field of driver assistance and autonomous perception.

Research Focus

Key Achievements

Top Papers

1. 1
   6D-Vision: Fusion of Stereo and Motion for Robust Environment Perception

   201 citations · 2005
2. 2
   Collision Avoidance for Vehicle-Following Systems

   105 citations · 2007
3. 3
   Exploiting the Power of Stereo Confidences

   90 citations · 2013
4. 4
   Real-time Semi-Global Matching on the CPU

   74 citations · 2010
5. 5
   Fast detection of moving objects in complex scenarios

   65 citations · 2007
6. 6
   Stereo matching in the presence of sub-pixel calibration errors

   56 citations · 2009
7. 7
   Performance Evaluation of Stereo Algorithms for Automotive Applications

   42 citations · 2009
8. 8
   Elastic bands to enhance vehicle following

   31 citations · 2002
9. 9
   Stereo matching in the presence of sub-pixel calibration errors

   15 citations · 2009
10. 10
    Stereo vision during adverse weather — Using priors to increase robustness in real-time stereo vision

    15 citations · 2017

Key Collaborators

Contact & Links