Object tracking for surveillance applications using thermal and visible band video data fusion

Beyan, Çiğdem
Individual tracking of objects in the video such as people and the luggages they carry is important for surveillance applications as it would enable deduction of higher level information and timely detection of potential threats. However, this is a challenging problem and many studies in the literature track people and the belongings as a single object. In this thesis, we propose using thermal band video data in addition to the visible band video data for tracking people and their belongings separately for indoor applications using their heat signatures. For object tracking step, an adaptive, fully automatic multi object tracking system based on mean-shift tracking method is proposed. Trackers are refreshed using foreground information to overcome possible problems which may occur due to the changes in object’s size, shape and to handle occlusion, split and to detect newly emerging objects as well as objects that leave the scene. By using the trajectories of objects, owners of the objects are found and abandoned objects are detected to generate an alarm. Better tracking performance is also achieved compared a single modality as the thermal reflection and halo effect which adversely affect tracking are eliminated by the complementing visible band data.