Abstract
An object tracking algorithm using the Mean Shift
framework is presented which is largely invariant to both partial
and full occlusions, complex backgrounds and change in scale.
Multiple features are used to gain a descriptive representation
of the target object. Image moments are used to determine the
scale of the target object. A kalman filter is used to successfully
track the target object through partial and full occlusions, the
Bhattacharyya coefficient is used to determine the measurement
noise estimation.