Luis Baumela

Papers

Total Citations

H-Index

About

Luis Baumela is a computer vision researcher whose work bridges geometric modeling, robust estimation, and practical robotics. His key research areas include line segment detection, landmark recognition, and camera-based object tracking. Baumela made significant contributions to visual perception for mobile robots, particularly in low-textured environments like city and indoor settings. His 2018 paper "FSG: A statistical approach to line detection via fast segments grouping" (17 citations) advanced efficient line extraction methods, building on algorithms like LSD and EDLines. Earlier, his 2008 work "Improving RANSAC for fast landmark recognition" (17 citations) introduced a geometrical constraint to accelerate homography fitting for planar landmark localization, enhancing robot navigation reliability. He also developed an early geometric model for camera-based object tracking with a pan-tilt robotic head (1995, 4 citations), addressing an open problem in dynamic visual servoing. Beyond research, Baumela contributed to AI education with an undergraduate course featuring guide robot programming assignments (2011, 3 citations), integrating core AI topics into hands-on robotics projects. His work has been cited over 40 times, reflecting his impact on practical computer vision and autonomous systems.