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A Comprehensive Survey of the Vehicle Motion Detection and Tracking Methods for Aerial Surveillance Videos


Hussam Saleh Abu Karaki, Saleh Ali Alomari and Mohammed Hayel Refai


Vol. 19  No. 1  pp. 93-106


Currently, object tracking and motion detection are considered challenging areas in the domain of computer vision where the complexity of tracking and object detection is increased by several factors. For examples, the illumination modification due to external factors, the parallax motion that is based on objects’ movements including the camera motion produces a complicated overview within the sight including the forecast pertaining to the 3D sights through the 2D image. Hence, this leads to reduce the image quality and loss of video details. Other factors that include real-time video processing, distance, imagery noise, occlusions, viewpoint, surrounding context overlapping and several other factors limits the ability to precisely identify and track a detected object. Therefore, this paper highlights and explains a different method of identifying the movements of objects in captured frames and the suitability, limitations, and possible techniques for the methods of background subtracting temporal differencing, statistical models and optical flow, where the optical flow method is selected as the most appropriate for aerial videos in this paper. Three main issues are identified in this paper for tracking, categorization and object detection within aerial videos that form the parallax motion, which is created by the camera’s dual movement and the objects over the ground, the impact of the camera altitude modification over the object representation in the captured frame and the impact of the illumination modification over the optical flow field.


Vehicle detection, object motion detection, object tracking, aerial surveillance videos