BMVC 2004, Kingston, 7th-9th Sept, 2004

Motion based 3D Target Tracking with Interacting Multiple Linear Dynamic Models
Z. Jia and A. Balasuriya (Nanyang Technological University,

In this paper, an algorithm is proposed for vision-based object identifi-
cation and tracking by autonomous vehicles. In order to estimate the
speed of the tracking object, this algorithm fuses information captured by
on-board sensors such as camera and inertial sensors. To formulate the
tracking algorithm it is necessary to use a proper model which describes
the dynamics of the tracking object. However due to complex nature of
the moving object, it is necessary to have di?erent dynamic models. Here,
several simple and basic linear dynamic models are combined to approximate
unpredictable, complex dynamics of the moving target. With these
basic linear dynamic models, a detailed description of the three dimensional
(3D) target tracking scheme using an interacting multiple model
(IMM) along with an Extended Kalman Filtering is presented. The final
state of the target is estimated as a weighted combination of the outputs
from each di?erent dynamic model. Performance of the proposed interacting
multiple dynamic model tracking algorithm is demonstrated through
experimental results.
(pdf article)