Detecting Moving Objects in Aerial Imagery Captured from Unmanned Aerial Vehicles
Padma Venkataramanan, The University of Canberra
Detecting moving objects in video footage is a fundamental preprocessing step involved in object detection and tracking. It is used in many real-time applications such as surveillance and traffic monitoring. Detecting moving objects in videos captured from a camera mounted on an unmanned aerial vehicle (UAV) is a challenging task. The camera is constantly moving in addition to the moving objects, which is why there is a need to distinguish the movement of the camera, global movement, from the movement of the foreground, local movement. UAV data suffer scale variations (due to altitude change of the UAV) and viewpoint variations (due to roll, pitch, and yaw), and this needs to be addressed when compensating for global movement.
As part of the research in object detection and tracking, a camera movement compensation algorithm has been implemented successfully using MATLAB®, Image Processing Toolbox™, and Computer Vision Toolbox™. The method involves estimating the camera movement between frames using the Kanade-Lucas-Tomasi (KLT) point tracker algorithm and correcting for it. Once the camera movement is corrected, frame differencing and background modelling methods are used to detect moving foregrounds. Beneficial results were achieved with minimal coding and faster turnaround time by using the built-in methods available in MATLAB.
Recorded: 18 May 2017
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