- Lecturer: QI, Xin
*Lecturer Information: https://w-rdb.waseda.jp/html/100001986_en.html - Title: Public area security enhancement and person trajectory forecasting
- Day and Time: November 24 ,2022 6:00pm –
- Abstract:
The traditional public security systems need to conduct security checks at the entrance and rely heavily on human screeners’ ability to recognize suspicious objects. They face two main challenges: congestion and misjudgments. A non-stop suspicious object detecting and screening technology, an AI-based W-band suspicious object detection system, is developed to address these issues. A machine learning based person trajectory forecasting system is also proposed to solve the re-tracking issue caused by congestion release from the non-stop screening system. I will introduce the recently finished MIC project, “Research and development of radar fundamental technology for advanced recognition of moving objects for security enhancement”. Then I will discuss my extended research topic, “Machine learning based cross-area person trajectory forecasting technology”
