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Moving object tracking employing rigid body motion on matrix Lie groups (CROSBI ID 635093)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Ćesić, Josip ; Marković, Ivan ; Petrović, Ivan Moving object tracking employing rigid body motion on matrix Lie groups // 19th International Conference on Information Fusion (FUSION), Special Session on Directional Estimation. Heidelberg, 2016. str. 2109-2115

Podaci o odgovornosti

Ćesić, Josip ; Marković, Ivan ; Petrović, Ivan

engleski

Moving object tracking employing rigid body motion on matrix Lie groups

In this paper we propose a novel method for estimating rigid body motion by modeling the object state directly in the space of the rigid body motion group SE(2). It has been recently observed that a noisy manoeuvring object in SE(2) exhibits banana-shaped probability density contours in its pose. For this reason, we propose and investigate two state space models for moving object tracking: (i) a direct product SE(2)×R 3 and (ii) a direct product of the two rigid body motion groups SE(2)×SE(2). The first term within these two state space constructions describes the current pose of the rigid body, while the second one employs its second order dynamics, i.e., the velocities. By this, we gain the flexibility of tracking omnidirectional motion in the vein of a constant velocity model, but also accounting for the dynamics in the rotation component. Since the SE(2) group is a matrix Lie group, we solve this problem by using the extended Kalman filter on matrix Lie groups and provide a detailed derivation of the proposed filters. We analyze the performance of the filters on a large number of synthetic trajectories and compare them with (i) the extended Kalman filter based constant velocity and turn rate model and (ii) the linear Kalman filter based constant velocity model. The results show that the proposed filters outperform the other two filters on a wide spectrum of types of motion.

Lie groups ; Special Euclidean group ; Moving object tracking

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Podaci o prilogu

2109-2115.

2016.

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objavljeno

978-0-9964527-4-8

Podaci o matičnoj publikaciji

19th International Conference on Information Fusion (FUSION), Special Session on Directional Estimation

Heidelberg:

Podaci o skupu

19th International Conference on Information Fusion (FUSION), Special Session on Directional Estimation

pozvano predavanje

05.07.2016-08.07.2016

Heidelberg, Njemačka

Povezanost rada

Elektrotehnika, Računarstvo, Temeljne tehničke znanosti