Yuling Hu

Papers

Total Citations

H-Index

About

Yuling Hu is a researcher in computer vision and 3D sensing, with a focus on improving the accuracy and reliability of consumer-grade RGBD sensors. Their most-cited work introduces a range-independent, disparity-based calibration model for structured light pattern-based RGBD sensors, addressing a critical limitation in depth measurement accuracy. This contribution is particularly valuable for applications in robotics control, localization, and mapping, where precise depth data is essential. Despite the early stage of their career, Hu's work has already garnered attention, with their top paper accumulating 4 citations, signaling growing recognition in the field. By tackling the inherent inadequacies of low-cost RGBD sensors, Hu is paving the way for more robust and accessible 3D sensing technologies. Their research holds promise for advancing autonomous systems and spatial understanding, making them a researcher to watch in the evolving landscape of computer vision and sensor calibration.