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About

X. Lebegue is a computer vision researcher whose work has centered on mobile robotics, visual scene understanding, and architectural modeling. Over the course of the 1990s and early 2000s, Lebegue made notable contributions to the problem of enabling mobile robots to perceive and interpret their indoor environments using a single camera — a technically challenging constraint that shaped much of the research agenda. His most influential work, "Significant Line Segments for an Indoor Mobile Robot" (1993), garnered 51 citations and introduced novel algorithms for detecting and semantically interpreting linear features in real scenes, laying a foundation for structured indoor navigation. This research was revisited and extended a decade later, demonstrating its enduring relevance to the field. Lebegue also pioneered methods for automatically generating architectural CAD models from mobile robot imagery, with related papers from 2002 accumulating over 35 combined citations. By combining segment detection, 3D reconstruction, and tracking across image sequences, this work bridged the gap between robotic perception and practical architectural documentation. His early contributions to mobile camera calibration further underscored a career-long commitment to robust, real-world computer vision systems. Collectively, his publications reflect a focused and technically rigorous body of work that influenced how autonomous robots understand and model structured environments.