Ivan Detchev
Papers
2
Total Citations
8
H-Index
2
About
Ivan Detchev is a researcher whose work bridges computer vision, photogrammetry, and sensing technologies, with a particular focus on advancing measurement and navigation systems. His research explores the calibration and application of imaging systems for real-world spatial analysis tasks, drawing on both classical geometric principles and modern machine learning techniques. One of his notable contributions involves the calibration of wide-angle lens cameras for robot vision, where he applied the collinearity condition alongside K-nearest neighbour regression to improve the accuracy of visual perception systems used in robotic navigation and environmental mapping. This work reflects a thoughtful integration of traditional photogrammetric models with data-driven approaches, offering practical pathways for autonomous systems operating in complex environments. Detchev has also investigated the utility of time-of-flight cameras — including the Mesa Imaging SR4000 and Microsoft Kinect 2.0 — for structural monitoring applications, specifically evaluating their precision in capturing the deformation of cyclically loaded beams. This research highlights the potential of affordable depth-sensing technologies in engineering and infrastructure assessment contexts. With a citation profile that reflects emerging but meaningful contributions, Detchev's work appeals to researchers at the intersection of geomatics, robotics, and non-contact measurement, offering methodological insights relevant to both autonomous systems and structural engineering communities.
Research Focus
Key Achievements
Top Papers
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- 2