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About

Jacky Chow is a researcher specializing in 3D sensing, photogrammetry, and sensor calibration, with particular expertise in the integration of low-cost imaging technologies for spatial measurement and indoor navigation. His most influential work, a 2012 performance analysis of the Microsoft Kinect system (43 citations), critically evaluated the capabilities and limitations of consumer-grade depth cameras for 3D modelling and motion tracking — arriving at a pivotal moment when such sensors were rapidly gaining traction in research and industry. Complementing this, his investigation into point-based versus plane-based self-calibration of terrestrial laser scanners (25 citations) advanced the field's understanding of systematic error modelling in high-precision 3D measurement systems. Chow further extended his work into multi-sensor integration for indoor 3D reconstruction, addressing the growing demand for indoor navigation solutions analogous to GPS-based outdoor systems. His research into wide-angle lens camera calibration using K-nearest neighbour regression reflects a sustained commitment to improving visual perception for robotic applications. Collectively, Chow's contributions bridge low-cost consumer hardware and rigorous metrological methodology, making his work particularly valuable for researchers developing accessible yet accurate spatial sensing systems.