Yusuke Matsumoto
Papers
1
Total Citations
8
H-Index
1
About
Yusuke Matsumoto is a researcher in computer vision and sensor fusion, with a focus on robust multi-person tracking and distributed sensing systems. His most cited work, "Scalable and robust multi-people head tracking by combining distributed multiple sensors" (2009), has garnered 8 citations, establishing a foundation for scalable tracking in crowded environments. Matsumoto's contributions lie in developing algorithms that integrate data from multiple distributed sensors to achieve reliable, real-time tracking of individuals, even under challenging conditions like occlusions or varying lighting. This work is particularly notable for its emphasis on scalability and robustness, addressing key limitations in traditional single-sensor approaches. By enabling efficient multi-person tracking across large spaces, his research has implications for surveillance, human-computer interaction, and autonomous systems. Matsumoto's approach demonstrates a practical balance between computational efficiency and accuracy, making his methods applicable to real-world deployments. His achievements reflect a commitment to advancing sensor-based tracking technologies, with potential to influence future work in smart environments and crowd analysis.
Research Focus
Key Achievements
Top Papers
- 1