Yanying Mei

Southwest University of Science and Technology

Papers

Total Citations

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About

Yanying Mei’s research lies at the intersection of computer vision, unmanned aerial systems, and intelligent control, with a focus on enabling robust, real-time outdoor target tracking for UAVs. Her most-cited work, “Using KCF and face recognition for outdoor target tracking UAV” (2019, 3 citations), addresses a critical challenge in autonomous drone navigation: maintaining stable, accurate tracking under dynamic outdoor conditions. Mei’s contribution integrates Kernelized Correlation Filters (KCF) with face recognition to enhance both the speed and reliability of target identification, while also developing precise position estimators and corresponding control strategies for the UAV system. This work is notable for its practical approach to a research hotspot—balancing computational efficiency with robustness in real-world environments. Though her citation count is modest, Mei’s research provides foundational insights into the synergy between tracking algorithms and UAV control, offering valuable pathways for students and researchers working on autonomous aerial systems, surveillance, or human-robot interaction. Her work underscores the importance of algorithm-hardware co-design in pushing the boundaries of outdoor UAV applications.