Mean Shift Object Tracking with Occlusion Handling
نویسندگان
چکیده
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.
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