Viviana Elizabeth Cabrera

Universidade Federal do Rio Grande do Norte

Papers

1

Total Citations

97

H-Index

1

About

Viviana Elizabeth Cabrera is a leading researcher in robotics and 3D computer vision, with a primary focus on sensor modeling and autonomous navigation. Her most influential work centers on the rigorous characterization of commercial depth sensors, particularly the ZED stereo camera from Stereolabs. In her highly cited 2018 paper, which has garnered 97 citations, Cabrera proposed a comprehensive mathematical error model for depth data estimation, addressing a critical gap in the reliability of 3D perception systems. This contribution has direct applications in autonomous robot navigation, virtual reality, tracking, and motion analysis, where accurate spatial understanding is paramount. By quantifying and modeling sensor uncertainty, Cabrera's research enables more robust and predictable performance in real-world robotic systems. Her work bridges the gap between theoretical sensor physics and practical deployment, making her a key figure in advancing the precision of vision-based autonomous systems. Cabrera's impact is evident in the continued reliance on her error models by researchers and engineers developing next-generation robotic platforms and immersive technologies.

Research Focus

Key Achievements

1
H-Index
1
Papers
97
Total Citations
97
Avg Citations/Paper
🏆 Most Cited Paper
Depth Data Error Modeling of the ZED 3D Vision Sensor from Stereolabs
97 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Universidade Federal do Rio Grande do Norte

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago