Papers
1
Total Citations
28
H-Index
1
About
Hamid Sarmadi’s research lies at the intersection of computer vision, augmented reality, and robotics, with a focus on precise object tracking and pose estimation. His most cited work, “Simultaneous Multi-View Camera Pose Estimation and Object Tracking With Squared Planar Markers” (2019, 28 citations), introduces a novel framework that leverages squared planar markers—widely used for their robust corner-based pose estimation—to simultaneously track objects and estimate camera poses from multiple viewpoints. This contribution is particularly impactful in high-stakes fields like medical augmented reality, where tracking surgical instruments with sub-millimeter accuracy is critical, and in robotics for real-time navigation. By addressing the challenge of marker occlusion and multi-camera synchronization, Sarmadi’s method enhances reliability in dynamic environments. His work has been cited in subsequent studies on marker-based tracking systems, underscoring its influence on practical AR and robotic applications. Sarmadi’s research continues to push the boundaries of how visual markers can enable seamless interaction between digital and physical worlds, making him a notable figure in applied computer vision.
Research Focus
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Top Papers
- 1