Detection of abandoned objects using thermal and visible band tracking

In this study, an abandoned object detection algorithm which is based on individual tracking of multiple objects such as people and their belongings is presented. To track people and their belongings individually; in addition to the visible band data, thermal band data is used and these objects are tracked using an improved, adaptive mean shift algorithm. By using the information coming from fusion of different modalities and using the heat signatures, objects are discriminated as people and belongings, trajectories of these objects are found, owners of belongings are determined and abandoned objects are detected. In association with mean shift tracking, adaptive background modeling and local intensity operation are used for fully automatic tracking. The results show that our method is robust, comparable with other methods by low false alarm rates and could be used to assist surveillance operators in public indoor environments. © 2011 IEEE.