Xavier Hubbard

Papers

Total Citations

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About

Xavier Hubbard is a researcher in computer vision and robotics, with a focus on motion capture and real-time localization systems. His most-cited work, "Mobile MoCap: Retroreflector Localization On-The-Go" (2023), addresses a critical gap in pose estimation by enabling accurate, marker-based tracking without the need for static camera arrays. This contribution bridges the gap between commercial motion capture systems and flexible fiducial marker methods like AprilTags, offering a portable solution for dynamic environments. With 5 citations, this paper has already garnered attention for its practical implications in robotics and augmented reality. Hubbard’s work is notable for its emphasis on on-the-go localization, which enhances the autonomy of mobile robots and wearable devices. His research demonstrates a commitment to making high-precision tracking accessible in unstructured settings, a key step toward more adaptable robotic systems. As a rising voice in his field, Hubbard’s contributions are poised to influence future developments in real-time spatial computing and human-robot interaction.