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This can be achieved using the mean shift algorithm.
Here, we first describe the mean shift algorithm.
The detected objects are then tracked using an adaptive mean shift algorithm.
The mean shift algorithm [2] uses the repeated movement of data points to the sample means.
The mean shift algorithm is generally used to find high-density regions (clusters) in multidimensional spaces.
In this section, we describe the image perception/segmentation based on the mean shift algorithm.
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Up to 295 university students took part in the experiments and all trajectories were extracted using the mean-shift algorithm.
In the part of eye tracking, cam-shift based mean-shift algorithm is used to track the eyes.
A mean-shift algorithm using bilateral filtering is also used for real-time and robust object tracking.
Mean-shift algorithm tracks the target correctly.
Mean-shift algorithm has a significant error in vehicle tracking.
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