Sriram Radhakrishna
Papers
1
Total Citations
4
H-Index
1
About
Sriram Radhakrishna is a researcher whose work sits at the intersection of computer vision, biomechanics, and human pose estimation. His primary focus is on developing efficient, cost-effective methods for extracting three-dimensional movement data from two-dimensional inputs—a critical challenge for applications ranging from sports analytics to rehabilitation. His most cited paper, "Economical Quaternion Extraction from a Human Skeletal Pose Estimate using 2-D Cameras" (2023, 4 citations), introduces a novel algorithm that bypasses the need for expensive stereo cameras or inertial measurement units. By deriving quaternion-based rotational data directly from a single 2-D camera frame, Radhakrishna’s work offers a practical, accessible solution for estimating contained human skeletal poses. This contribution is particularly notable for its potential to democratize motion capture technology, making it viable for low-resource settings. While his citation count is still growing, the foundational nature of this algorithm signals a promising trajectory in bridging the gap between high-fidelity biomechanical analysis and everyday camera systems.
Research Focus
Key Achievements
Top Papers
- 1