Using Multi-Scale Infrared Optical Flow-based Crowd motion estimation for Autonomous Monitoring UAV

Crowd motion estimation is an important part of detection and analysis of abnormal behavior of the crowd. Crowd motion Analysis in special places is a necessary for maintaining the safety and social stability in public place and there is a research difficulty in the field of intelligent video monitoring in an unexpected dynamic open environment. Unmanned Aerial Vehicles (UAVs) have become a flexible monitoring platform in recent years. Existing approaches for crowd motion estimation based on traditional visible light cameras have the limitation to find the warm object clearly in the night. This paper proposes a crowd motion estimation system based on the multiple scale optical flow and corner detection employing the advantages of working all day of infrared cameras and high flexibility of the UAV. Firstly, the original infrared images are captured with the airborne thermal infrared imager TAU2-336. And then the preprocessed images are obtained by Median filtering. Secondly, the corners detection and tracking process are completed by using multiscale analysis. Finally, the average velocity is calculated for crowd motion estimation. The experimental results show that the proposed approach is effective for estimating the motion speed and crowd behavior status.