A New Scheme for Vision Based Flying Vehicle Detection Using Motion Flow Vectors Classification

Deformable Contour-Based Maneuvering Flying Vehicle Tracking in Color Video Sequences

“…In order to localize, track, and recognize flying vehicles, some approaches have been presented recently. In this context, four main state-of-the-art methodologies are well known and applicable including (1) invisible spectrum-based methods like radio detection and ranging (RADAR) or light detection and ranging (LIDAR); (2) visible spectrum-based approaches [1][2][3][4][5][6][7][8] such as existing algorithms in infrared and thermal imaging systems in the wavelength range of 380 nm to 780 nm and even more in far infrared case; (3) global positioning system (GPS-) based methods; and (4) combination of visible and invisible spectrum-based methods. Feasibility of these categories is mostly dependent upon the distance of the imaging system to the target of interest.…”

“…In this method, the incipient location of the target was determined manually; then, the target was tracked automatically by optimizing the mesh energy functions. In [2], a visionbased scheme for automatic locating of a flying vehicle was 2 ISRN Machine Vision presented by means of extracting fuzzified edges features and matching edge pyramids as well as a motion flow vector classifier based on multilayer perceptrons (MLP) neural network. Ha et al [3] introduced a method for real time tracking of flying targets via the combination of the geometric active contour model and optical flow algorithm.…”