Weather-adaptive flying target detection and tracking from infrared video sequences

This paper proposes a new computer-aided tracking method that can track multiple flying targets in an image sequence acquired from either an optical camera or an infrared camera system. The proposed method includes two major steps, which are flying target detection and flying target tracking. Because weather conditions greatly affect the detection of a flying target, we designed a fuzzy system that classifies the weather into two basic weather types. Based on the weather type, flying targets can be detected successfully. In tracking a flying target, we apply the dynamic layer representation method to represent the flying target and use a Kalman filter to predict the target’s position. The second fuzzy rule system is designed to identify the target states, which are visible, missing, or occluded, based on the layer and positional features. Thereafter, the identified state can help to select a suitable tracking strategy for the subsequent frames. experiments, we demonstrate the results applied to five real image sequences. The proposed method can successfully detect and track multiple flying targets perfectly in clear weather. It also achieves around 90% accuracy when the weather is not clear. The fuzzy methodology makes the proposed system more effective at detecting and tracking targets and more flexible to complex environmental conditions, since the rules can be easily added and modified.