Saumik Bhattacharya
Papers
1
Total Citations
3
H-Index
1
About
Dr. Saumik Bhattacharya is a computer vision researcher whose work focuses on depth estimation, image processing, and video analysis. His most-cited paper, "Depth filtering using total variation based video decomposition" (2015, 3 citations), addresses a fundamental challenge in vision-based applications: improving the accuracy of depth maps for tasks ranging from 3D rendering to automation. By introducing a total variation-based filtering technique, he proposed a method to refine noisy depth estimates, contributing to more reliable scene understanding. Though his citation count is modest, this work reflects a targeted effort to enhance precision in depth measurement—a critical component in autonomous systems and augmented reality. Dr. Bhattacharya’s research sits at the intersection of computational imaging and practical deployment, where even small improvements in depth accuracy can have outsized impacts on system performance. His contributions are particularly relevant for students and researchers exploring robust depth estimation pipelines, offering a foundation for further innovation in real-world vision technologies.
Research Focus
Key Achievements
Top Papers
- 1Depth filtering using total variation based video decomposition3 citations · 2015