Papers
1
Total Citations
15
H-Index
1
About
Xuehui Yin is a computer vision researcher whose work focuses on advancing camera calibration techniques, particularly in data-constrained environments. Their most-cited paper, "Camera calibration from very few images based on soft constraint optimization" (2020, 15 citations), introduces a novel approach that relaxes traditional rigid constraints, enabling accurate calibration from as few as two to three images. This contribution addresses a critical bottleneck in practical applications like augmented reality, robotics, and 3D reconstruction, where acquiring extensive calibration datasets is often infeasible. By leveraging soft constraint optimization, Yin’s method balances geometric accuracy with algorithmic flexibility, offering a robust solution for real-world scenarios with limited input data. While their citation count reflects a focused, emerging impact, this work has been recognized for its potential to streamline calibration pipelines in resource-limited settings. Yin’s research underscores a commitment to making computer vision tools more accessible and efficient, bridging the gap between theoretical precision and practical usability. Their contributions are particularly valuable for students and researchers seeking to understand how optimization techniques can overcome data scarcity in vision systems.
Research Focus
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Top Papers
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