Tracking non-ellipsoidal extended objects using sequential Monte- Carlo

Kara, Süleyman Fatih
The problem of extended target tracking is considered in which the target extent is represented with multiple ellipses. The resulting inference problem, which is considered in the sequential Monte Carlo (SMC) framework, includes association of the measurements between sub-objects. We make use of different particle filtering approaches to solve the aforementioned association problem under the assumption of known extent. When the extent is unknown, parameters of the multiple ellipses should also be estimated. For this purpose, a particle filter based method is derived for joint estimation of target's kinematic and extent states. The proposed method uses variational Bayes technique to obtain an approximate conditional analytical expression, which enables the use of Rao-Blackwellization (a.k.a. marginalization) idea in particle filtering.


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...
Multi-Ellipsoidal Extended Target Tracking With Variational Bayes Inference
Tuncer, Barkın; Orguner, Umut; Özkan, Emre (2022-01-01)
In this work, we propose a novel extended target tracking algorithm, which is capable of representing a target or a group of targets with multiple ellipses. Each ellipse is modeled by an unknown symmetric positive-definite random matrix. The proposed model requires solving two challenging problems. First, the data association problem between the measurements and the sub-objects. Second, the inference problem that involves non-conjugate priors and likelihoods which needs to be solved within the recursive fil...
Multi-Ellipsoidal Extended Target Tracking Using Sequential Monte Carlo
Kara, Süleyman Fatih; Özkan, Emre (2018-07-10)
In this paper, we consider the problem of extended target tracking, where the target extent cannot be represented by a single ellipse accurately. We model the target extent with multiple ellipses and solve the resulting inference problem, which involves data association between the measurements and sub-objects. We cast the inference problem into sequential Monte Carlo (SMC) framework and propose a simplified approach for the solution. Furthermore, we make use of the Rao-Blackwellization, aka marginalization...
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...
Multitarget tracking performance metric: deficiency aware subpattern assignment
Oksuz, Kemal; CEMGİL, ALİ TAYLAN (2018-03-01)
Multitarget tracking is a sequential estimation problem where conditioned on noisy sensor measurements, state variables of several targets need to be estimated recursively. In this study, the authors propose a novel performance measure for multitarget tracking named as Deficiency Aware Subpattern Assignment (DASA), that can be used to consistently compare algorithms in a broad spectrum of formulations ranging from conventional data association methods to random finite set based multitarget tracking algorith...
Citation Formats
S. F. Kara, “Tracking non-ellipsoidal extended objects using sequential Monte- Carlo,” M.S. - Master of Science, Middle East Technical University, 2018.