Yin-Wei Chang

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About

Yin-Wei Chang is a computer vision researcher whose work centers on panoramic imaging and sensor calibration, with a particular focus on the geometric and optical challenges of multi-camera systems. His most cited paper, "Rotating sensor-matrix camera calibration" (2010), addresses a critical bottleneck in panoramic imaging: the precise calibration of rotating sensor arrays to produce seamless, high-quality panoramic images. This contribution is foundational for applications spanning computer vision, graphics, visualization, and robotics, where accurate 360-degree perception is essential. Though his citation count is modest, Chang’s work is notable for tackling the practical calibration issues that underpin reliable panoramic sensor deployment—a prerequisite for advances in autonomous navigation, immersive media, and surveillance. His research reflects a deep engagement with the hardware-software interface, bridging theoretical calibration models with real-world sensor constraints. For students and researchers entering the field of computational imaging, Chang’s contributions offer a clear example of how rigorous calibration methodology enables the next generation of panoramic sensing technologies.