Surface Vessel Tracking in Airborne Infrared Imagery

Cakiroglu, Ahmet
Ulusoy, İlkay
Visual target tracking has been studied for decades and still remains a challenging problem. Ship tracking on infrared images has numerous challenges compared to conventional target tracking such as fast changing of appearance. Rapid appearance change caused by the manoeuvring movement of the target of image acquiring platform, confusion and occlusion caused by the active countermeasures employed by the target and disguise by cooling systems causes the target tracking algorithms to have low performance. In this work, a convolutional neural network and correlation filter based algorithm which tracks surface vessels on infrared imagery is proposed. Performance of the proposed algorithm is compared against the distinguished, popular target tracking algorithms from the literature. Performances are evaluated on a specially created infrared ship images dataset.


Target tracking with correlated measurement noise
Okşar, Yeşim; Demirbaş, Kerim; Department of Electrical and Electronics Engineering (2007)
A white Gaussian noise measurement model is widely used in target tracking problem formulation. In practice, the measurement noise may not be white. This phenomenon is due to the scintillation of the target. In many radar systems, the measurement frequency is high enough so that the correlation cannot be ignored without degrading tracking performance. In this thesis, target tracking problem with correlated measurement noise is considered. The correlated measurement noise is modeled by a first-order Markov m...
Random Matrix Based Extended Target Tracking with Orientation: A New Model and Inference
Tuncer, Barkın; Özkan, Emre (2021-02-01)
In this study, we propose a novel extended target tracking algorithm which is capable of representing the extent of dynamic objects as an ellipsoid with a time-varying orientation angle. A diagonal positive semi-definite matrix is defined to model objects' extent within the random matrix framework where the diagonal elements have inverse-Gamma priors. The resulting measurement equation is non-linear in the state variables, and it is not possible to find a closed-form analytical expression for the true poste...
3D Extended Object Tracking Using Recursive Gaussian Processes
Kumru, Murat; Özkan, Emre (2018-07-10)
In this study, we consider the challenging task of tracking dynamic 3D objects with unknown shapes by using sparse point cloud measurements gathered from the surface of the objects. We propose a Gaussian process based algorithm that is capable of tracking the dynamic behavior of the object and learn its shape in 3D simultaneously. Our solution does not require any parametric model assumption for the unknown shape. The shape of the objects is learned online via a Gaussian process. The proposed method can joi...
Extended target tracking using reduced rank gaussian processes
Özcan , Mustafa Buğra; Özkan, Emre; Department of Electrical and Electronics Engineering (2021-2-12)
Conventional tracking algorithms are predominantly based on point target assumption; however, this assumption is challenged as a result of the advents in sensor resolutions. Improvements on processors and rapid advances in sensor capabilities has enabled to the perception of target characteristics beyond the kinematics. Extended target tracking is the ability to learn target shapes that occupy multiple resolution cells and to track the motion of the target in a recursive framework. Gaussian process, a non-p...
Surface vessel tracking in airborne infrared imagery
Çakıroğlu, Ahmet; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2019)
Target tracking can be defined as continuously locating the object of interest in consequent images. Tracking surface vessels in infrared imagery is an exceptionally challenging case of visual target tracking. In a typical scenario both the target and imaging platform exhibit manoeuvring movement, causing the appearance of the target to change rapidly and significantly during the course of tracking. Furthermore there are cases where target actively attempts to avoid being tracked by firing hot flares to con...
Citation Formats
A. Cakiroglu and İ. Ulusoy, “Surface Vessel Tracking in Airborne Infrared Imagery,” 2019, Accessed: 00, 2020. [Online]. Available: