Papers
2
Total Citations
28
H-Index
2
About
Xiuyuan Qi is a rising researcher in the field of embedded computer vision and hardware acceleration, with a focus on enabling real-time visual Simultaneous Localization and Mapping (VSLAM) for resource-constrained mobile platforms. His work sits at the critical intersection of algorithm design and digital hardware implementation, addressing the substantial computational bottlenecks that prevent advanced vision algorithms from running efficiently on edge devices. Qi’s major contributions include the development of "MobileSP," an FPGA-based hardware accelerator for CNN-driven keypoint extraction—a technique that significantly improves the accuracy of VSLAM systems. This work, published in 2022, has already garnered 24 citations, reflecting its timely impact on the mobile robotics and augmented reality communities. More recently, Qi advanced the field with a high-performance ORB accelerator, co-designed with algorithmic optimizations for visual localization. This work tackles the heavy computational load of feature point extraction and matching, achieving efficiency gains crucial for UAVs and AR/VR headsets. Through his innovative co-design methodology, Xiuyuan Qi is helping to bridge the gap between state-of-the-art computer vision and practical, real-time deployment on low-power hardware.
Research Focus
Key Achievements
Top Papers
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