Luca Mussi

Papers

Total Citations

H-Index

About

Luca Mussi is a researcher in computer vision and robotics, specializing in omnidirectional and hybrid camera systems. His work focuses on developing novel visual sensors that combine wide-angle, panoramic views with high-resolution imaging, enabling more robust environmental perception for autonomous systems. Mussi’s major contribution is the design and calibration of a hybrid stereo sensor that integrates perspective and omnidirectional vision to achieve a full 360-degree field of view while retaining the ability for high-resolution 3D metric reconstruction. This innovation, detailed in his most-cited paper (9 citations), addresses a critical challenge in robotics and surveillance: maintaining situational awareness without sacrificing detail. His research draws inspiration from biological vision systems, such as the compound eyes of dragonflies, which naturally achieve wide fields of view through thousands of individual sensing units. Mussi’s work on hybrid dual-camera systems (2 citations) further explores this bio-inspired approach, advancing the design of compact, multi-modal sensors. Though his citation counts are modest, his contributions are foundational for applications in autonomous navigation, environmental monitoring, and robotic perception, offering practical solutions for integrating panoramic awareness with precise depth sensing.