Carl Olsson

Lund University

Papers

1

Total Citations

8

H-Index

1

About

Carl Olsson is a leading figure in computer vision, whose research focuses on 3D reconstruction, robust geometry estimation, and optimization methods for visual perception. His major contributions lie in advancing real-time, dense 3D modeling from consumer-grade sensors, addressing the long-standing challenge of acquiring accurate 3D models on the fly. Notably, his work on robust online 3D reconstruction, which combines depth sensor data with sparse feature points, has been pivotal in extending the capabilities of systems like KinectFusion, enabling more reliable and complete scene capture even in challenging environments. With over 8 citations on this specific paper and a broader impact across his field, Olsson’s research has influenced both academic understanding and practical applications in robotics, augmented reality, and autonomous navigation. His work is characterized by a rigorous approach to solving geometric and optimization problems, making him a key contributor to the next generation of real-time 3D vision systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
8
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Robust online 3D reconstruction combining a depth sensor and sparse feature points
8 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Lund University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago