David Demirdjian

Institut national de recherche en sciences et technologies du numérique, Vecna Technologies (United States)

Papers

Total Citations

H-Index

About

David Demirdjian is a computer vision researcher whose work bridges geometric reconstruction and human-robot interaction. His most cited contribution, "Finding the Collineation between Two Projective Reconstructions" (1999, 28 citations), addresses a fundamental problem in 3D computer vision: aligning projective reconstructions from uncalibrated cameras. This work provides a robust method for computing the collineation (projective transformation) between two scenes, enabling more accurate 3D modeling from multiple views—a key step for applications in augmented reality and autonomous navigation. Demirdjian’s research demonstrates a deep understanding of projective geometry, offering practical solutions for structure-from-motion pipelines. Later, he shifted focus to applied robotics, co-authoring "Handheld operator control unit" (2012, 4 citations), which tackles the challenge of teleoperating unmanned ground vehicles in military contexts. This work proposes a compact, intuitive interface that reduces operator cognitive load, allowing soldiers to control robots with minimal training. By combining theoretical rigor with real-world usability, Demirdjian’s contributions have influenced both academic computer vision and practical robotic systems, showcasing how geometric principles can enhance human-robot collaboration in high-stakes environments.