Aerial Video Surveillance System for Small-Scale UAV Environment Monitoring

Change detection algorithms are commonly used to detect novelties for surveillance purposes in public and private places equipped by static or Pan-Tilt-Zoom (PTZ) cameras. Often, these techniques are also used as prerequisite to support more complex algorithms, including event recognition, object classification, person re-identification, and many others. With regard to small-scale Unmanned Aerial Vehicles (UAVs) at low-altitude, the change detection techniques require further investigation. In fact, most of the works currently available in the literature process video sequences acquired at very high-altitude for large-scale operations, such as vegetation monitoring, mapping of buildings, and so on. In a wide range of application contexts that require, for example, frequent monitoring or high spatial resolution for detecting small objects, video sequences acquired at high-altitude are not suitable. This paper presents a change detection system based on histogram equalization and RGB-Local Binary Pattern (RGB-LBP) operator for monitoring of wide areas by small-scale UAVs at low-altitude. Extensive experimental results show the robustness of the proposed pipeline. These latter were performed by using challenging video sequences of the public UAV Mosaicking and Change Detection (UMCD) dataset and measured a set of well-known statistical metrics. Finally, a performance analysis of the proposed algorithm is also provided.