Qianlong Bai

Papers

Total Citations

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About

Qianlong Bai is a researcher focused on intelligent video analysis and human behavior understanding, with a particular emphasis on crowd anomaly detection for real-world surveillance applications. His most cited work, "An Analysis Method of Crowd Abnormal Behavior for Video Service Robot" (2019), addresses the critical challenge of rapidly and accurately identifying abnormal behaviors in crowded environments such as airports, shopping malls, and train stations—scenarios where timely detection is essential for public safety. By developing methods tailored for video service robots, Bai’s research bridges computer vision and robotics, aiming to enhance automated monitoring systems. With 15 citations, this paper has contributed to advancing practical solutions for crowd behavior analysis. His work underscores the importance of balancing detection speed and accuracy in dynamic, high-density settings, offering valuable insights for researchers and engineers developing intelligent surveillance technologies. Bai’s contributions are particularly relevant for students and practitioners interested in applying computer vision to real-time safety and security challenges.