Martin Geier

Technical University of Munich

Papers

2

Total Citations

15

H-Index

2

About

Martin Geier is a researcher at the forefront of embedded real-time systems, with a particular focus on the intersection of computer vision, industrial automation, and energy-efficient hardware design. His primary research areas include visual servoing, FPGA-based system integration, and real-time data acquisition over Gigabit Ethernet. Geier’s most cited work, “GigE Vision Data Acquisition for Visual Servoing using SG/DMA Proxying” (2016, 10 citations), addresses a critical challenge in robotics and industrial control: enabling real-time execution of vision-based control loops over GigE networks on low-power, embedded platforms. This contribution is foundational for modern visual servoing systems that demand both high bandwidth and deterministic timing. In his more recent work, “Insert & Save: Energy Optimization in IP Core Integration for FPGA-based Real-time Systems” (2021, 5 citations), Geier tackles the pressing need for energy-efficient design in battery-powered and high-temperature environments, such as autonomous robots and automotive systems. By optimizing IP core integration on FPGAs, he provides a practical pathway to reduce energy consumption without sacrificing real-time performance. Geier’s research is notable for bridging the gap between high-performance vision processing and the stringent constraints of embedded, energy-limited systems—a balance critical for next-generation autonomous and industrial applications.

Research Focus

Key Achievements

2
H-Index
2
Papers
15
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
GigE Vision Data Acquisition for Visual Servoing using SG/DMA Proxying
10 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Technical University of Munich

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago