Aiquan Li

Guangxi University of Finance and Economics

Papers

Total Citations

H-Index

About

Aiquan Li is a researcher focused on intelligent video analysis and computer vision, with a particular emphasis on crowd behavior understanding for service robotics. His most cited work, “An Analysis Method of Crowd Abnormal Behavior for Video Service Robot” (2019, 15 citations), addresses the critical challenge of detecting anomalies in crowded, real-world environments such as airports, shopping malls, and train stations. Li’s contributions center on developing rapid and accurate algorithms that enable robots to identify suspicious or dangerous crowd activities in real time—a key requirement for public safety and autonomous surveillance systems. By tackling the trade-off between detection speed and precision, his research advances the practical deployment of video service robots in high-traffic areas. Li’s work holds significant impact for smart city applications, where timely anomaly detection can prevent incidents and enhance security. His findings provide a foundation for future studies in automated crowd monitoring, making him a notable contributor to the intersection of robotics, computer vision, and public safety.