Matteo Zanetti
Papers
2
Total Citations
33
H-Index
2
About
Matteo Zanetti is a researcher whose work sits at the intersection of computer vision, assistive robotics, and human-computer interaction. His primary research areas include multi-camera calibration, 3D sensing, and the development of intelligent mobility aids for individuals with severe motor disabilities. Zanetti’s most significant contribution is his novel, automatic graph-based method for the spatiotemporal extrinsic calibration of multiple Time of Flight (ToF) cameras, such as the Kinect V2. This technique, published in 2017 and garnering 23 citations, simplifies the setup of complex motion capture systems by requiring only 3D point clouds and chromatic data, making it both fast and user-friendly. Building on this sensing expertise, Zanetti led the development of RoboEYE, a semi-autonomous, gaze-driven power wheelchair designed for domestic use. This 2021 work, with 10 citations, directly addresses the loss of mobility by enabling users to navigate their homes safely and efficiently using only eye movement. His work is notable for translating sophisticated computer vision algorithms into practical, life-changing assistive technologies, demonstrating a clear commitment to improving quality of life through robust, real-world engineering.
Research Focus
Key Achievements
Top Papers
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- 2