Viviana Ávila
Papers
1
Total Citations
14
H-Index
1
About
Viviana Ávila is a researcher whose work centers on advancing the accuracy and reliability of 3D sensing technologies, particularly for stereo and RGB-D systems. Her most-cited paper, "A Generic Approach for Error Estimation of Depth Data from (Stereo and RGB-D) 3D Sensors" (2017), introduces a novel, sensor-agnostic methodology for quantifying depth measurement errors. By capturing images and analyzing the resulting depth maps, Ávila’s framework enables researchers and engineers to calibrate and validate a wide range of 3D sensors—from consumer-grade RGB-D cameras to industrial stereo setups—without relying on proprietary hardware. This contribution is critical for applications in robotics, autonomous navigation, and augmented reality, where precise depth perception is essential. With 14 citations, the work has already informed subsequent studies in sensor fusion and error correction. Ávila’s research bridges the gap between theoretical metrology and practical deployment, offering a standardized tool for improving the fidelity of 3D data. Her approach stands out for its generality, making it a valuable resource for anyone working with depth sensors in dynamic or uncontrolled environments.
Research Focus
Key Achievements
Top Papers
- 1