Victor Fragoso
Papers
1
Total Citations
12
H-Index
1
About
Victor Fragoso is a leading researcher in computer vision and geometric estimation, with a focus on enabling robust and efficient 3D perception for augmented reality (AR), robotics, and mapping. His most notable contribution is the development of the **gDLS* (Generalized Pose-and-Scale Estimation Given Scale and Gravity Priors)** method, a groundbreaking algorithm that simultaneously estimates camera pose and scale with high speed and accuracy, even when leveraging priors like gravity direction. This work directly addresses a critical bottleneck in real-world AR and multi-camera systems, where fast, reliable pose estimation is essential. With over a dozen citations, gDLS* has already influenced subsequent research in geometric computer vision. Fragoso’s research bridges the gap between theoretical rigor and practical deployment, making him a key figure in advancing real-time 3D understanding. His contributions are particularly valued in applications ranging from handheld AR to autonomous navigation, where his algorithms help machines perceive and interact with the physical world more naturally.
Research Focus
Key Achievements
Top Papers
- 1gDLS*: Generalized Pose-and-Scale Estimation Given Scale and Gravity Priors12 citations · 2020