Kalman tracking of color objects
First Claim
1. A method of performing semi-automatic tracking of colored objects within a video image sequence comprising the steps of:
- separating objects within an initial frame of the video image sequence on the basis of color;
receiving a user-provided input that selects an object of interest from the separated objects by a user identifying a centroid of the object of interest; and
tracking the object of interest through successive frames of the video image sequence using a Kalman predictive algorithm applied to the centroid.
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Abstract
A semi-automatic method of tracking color objects in a video image sequence starts by separating the objects on the basis of color and identifying an object of interest to track. A Kalman predictive algotithm in used to predict the position of the centroid of the object of interest through successive frames. From the predicted position the actual centroid is measured and the position and velocity are smoothed using a Kalman filter. Error recovery is provided in the event the centroid falls outside the field of view or falls into an area of a different color, or in the event the tracking algorithm breaks down.
69 Citations
10 Claims
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1. A method of performing semi-automatic tracking of colored objects within a video image sequence comprising the steps of:
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separating objects within an initial frame of the video image sequence on the basis of color;
receiving a user-provided input that selects an object of interest from the separated objects by a user identifying a centroid of the object of interest; and
tracking the object of interest through successive frames of the video image sequence using a Kalman predictive algorithm applied to the centroid. - View Dependent Claims (2, 3)
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4. A method of tracking a colored object moving relative to a background within a sequence of video image frames, comprising the steps of:
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(a) in an initial frame of the sequence, separating objects from the background based on color;
(b) selecting a separated object by a user identifying a reference point within a boundary of the separated object; and
(c) tracking the selected object through successive frames of the video image sequence using a Kalman predictive algorithm applied to the reference point. - View Dependent Claims (5, 6, 7, 8, 9, 10)
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Specification