Mihai Negru
Papers
1
Total Citations
7
H-Index
1
About
Mihai Negru is a researcher whose work lies at the intersection of computer vision, robotics, and advanced driver assistance systems. His primary focus is on stereo reconstruction—the process of extracting 3D information from two or more camera images—a critical technology for autonomous driving and robotic navigation. In his most cited work, "Improving local stereo algorithms using binary shifted windows, fusion and smoothness constraint" (2015), Negru tackles the persistent challenge of balancing reconstruction accuracy with computational efficiency. He introduces novel techniques, including binary shifted windows and fusion strategies, to enhance the quality of depth maps while maintaining the real-time performance essential for safety-critical applications. This paper has garnered 7 citations, reflecting its influence on researchers seeking to optimize stereo algorithms for embedded systems. Negru’s contributions are particularly notable for addressing the memory and speed bottlenecks that have historically limited stereo vision in real-world deployment. His work continues to inform the development of more robust, efficient perception systems, making him a valuable voice in the ongoing effort to bring reliable 3D sensing to autonomous vehicles and intelligent robots.
Research Focus
Key Achievements
Top Papers
- 1