Thomas Sarmis
Papers
1
Total Citations
5
H-Index
1
About
Thomas Sarmis is a researcher in computational vision and robotics, with a focus on camera calibration and 3D reconstruction. His most cited work, "A checkerboard detection utility for intrinsic and extrinsic camera cluster calibration" (2009, 5 citations), developed at FORTH’s Computational Vision and Robotics Laboratory, provides a robust tool for calibrating multi-camera systems. This utility automates the detection of checkerboard patterns, enabling precise estimation of both intrinsic parameters (e.g., focal length, distortion) and extrinsic parameters (e.g., camera positions and orientations) across clusters. The work is foundational for applications in augmented reality, motion capture, and autonomous navigation, where accurate multi-camera alignment is critical. Sarmis’s contributions streamline calibration workflows, reducing manual intervention and error. His research, though modest in citation count, addresses a persistent challenge in computer vision, offering practical solutions for labs and industry. By enhancing the reliability of camera clusters, Sarmis supports advances in spatial understanding and robotic perception, making his work a valuable resource for students and engineers building multi-view systems.
Research Focus
Key Achievements
Top Papers
- 1