Smitha Lingadahalli Ravi
Papers
1
Total Citations
3
H-Index
1
About
Smitha Lingadahalli Ravi is a researcher whose work lies at the intersection of immersive media, computer vision, and intelligent video transmission. Her primary research focuses on depth estimation—a critical component for enabling realistic 3D experiences in applications ranging from immersive video and telepresence to autonomous driving and robotics. In her most cited work, "A Study of Conventional and Learning-Based Depth Estimators for Immersive Video Transmission" (2022, 3 citations), Ravi provides a comprehensive comparative analysis of traditional algorithmic approaches versus modern deep learning methods for generating accurate depth maps. This study is particularly valuable for researchers and engineers seeking to balance computational efficiency with precision in real-world transmission scenarios. By systematically evaluating the trade-offs between these two paradigms, Ravi has contributed foundational insights that help guide the selection of appropriate depth estimation techniques for bandwidth-constrained immersive video systems. Her work underscores the ongoing challenge of achieving high-fidelity 3D perception in dynamic environments, making her a notable voice in the advancement of next-generation visual communication technologies.
Research Focus
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Top Papers
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