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About

Anup Basu is a computer vision and robotics researcher whose work spans camera calibration, robot navigation, human gesture and pose recognition, and surgical augmented reality. His foundational 1997 paper on active camera calibration using pan, tilt, and roll (49 citations) established robust methods for modeling the geometric relationship between 2D images and 3D environments — a critical challenge in robot vision systems. Building on this, his research into panoramic tracking and stereo imaging systems advanced autonomous robot navigation, with his 2004 panoramic navigation paper attracting 41 citations. Basu made notable contributions to human-computer interaction through innovative applications of the Radon transform, developing effective methods for recognizing air traffic control hand gestures (36 citations) and human body poses (28 citations) — work with clear implications for robotics teleoperation and virtual environments. His research portfolio further extends into mobile robot path planning under uncertainty and, more recently, augmented reality frameworks for endovascular surgical training, demonstrating a consistent drive to apply vision technologies to real-world safety-critical problems. Across more than two decades, Basu has maintained a productive research trajectory that bridges fundamental computer vision theory with practical engineering applications.