Sumana Gupta
Papers
1
Total Citations
3
H-Index
1
About
Sumana Gupta is a researcher whose work lies at the intersection of computer vision and image processing, with a particular focus on depth estimation and video analysis. Her key contributions center on improving the accuracy and reliability of depth maps—a critical component for applications ranging from 3D rendering to autonomous systems. In her notable 2015 paper, "Depth filtering using total variation based video decomposition," Gupta introduced a novel approach to refine depth measurements by leveraging total variation regularization, a technique that separates video content into structural and textural components to reduce noise and errors in depth estimation. While her most-cited work has garnered 3 citations, it represents a foundational step in addressing the persistent challenge of precision in depth capture for vision-based applications. Her research underscores the importance of robust filtering methods in enhancing the performance of depth-dependent technologies, contributing to the broader goal of making automated systems more reliable in real-world environments.
Research Focus
Key Achievements
Top Papers
- 1Depth filtering using total variation based video decomposition3 citations · 2015