Abstract
Tracking moving objects with a moving camera is a challenging task. For unmanned aerial vehicle applications, targets of interest such as human and vehicles often change their location from image frame to frame. This paper presents an object tracking method based on accurate feature description and matching, using the SYnthetic BAsis descriptor, to determine a homography between the previous frame and the current frame. Using this homography, the previous frame can be transformed and registered to the current frame to find the absolute difference and locate the objects. Once the objects of interest are located, the Kalman filter is then used for tracking their movement. This proposed method is evaluated with three video sequences under image deformation: illumination change, blurring and camera movement (i.e. viewpoint change). These video sequences are taken from unmanned aerial vehicles (UAVs) for tracking stationary and moving objects with a moving camera.
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Desai, A., Lee, DJ., Zhang, M. (2014). Using Accurate Feature Matching for Unmanned Aerial Vehicle Ground Object Tracking. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8887. Springer, Cham. https://doi.org/10.1007/978-3-319-14249-4_41
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DOI: https://doi.org/10.1007/978-3-319-14249-4_41
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14248-7
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