Baomin Yi
Papers
1
Total Citations
15
H-Index
1
About
Baomin Yi is a researcher specializing in intelligent perception, sensor fusion, and autonomous obstacle detection for outdoor environments. His work addresses critical challenges in robotics and computer vision, particularly the low recognition rates and poor robustness of existing detection systems. In his most cited paper, "A Simple Outdoor Environment Obstacle Detection Method Based on Information Fusion of Depth and Infrared" (2016, 15 citations), Yi proposes an innovative algorithm that fuses depth and infrared data to improve detection accuracy. By employing the mean-shift algorithm for scene segmentation and analyzing pixel gradients in the foreground, his method achieves a straightforward yet effective solution for real-world obstacle recognition. This contribution is notable for its practical simplicity and potential applications in autonomous navigation and assistive technologies. Though his citation count is modest, Yi’s work demonstrates a focused effort to enhance sensor-based perception systems, laying groundwork for more robust and reliable outdoor obstacle detection. His research is valuable for students and engineers exploring low-cost, efficient fusion techniques in robotics and intelligent transportation.
Research Focus
Key Achievements
Top Papers
- 1