Pedestrian Tracking Method under Occlusion and Scale Variation
A pedestrian tracking and scale change technology, applied in the field of computer vision, which can solve problems such as tracking failure
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[0029] A pedestrian tracking method in the case of occlusion and scale changes. The Kalman filter is used to predict the target position, and the prediction result is used in the KCF framework to accurately locate the target; according to the KCF tracking response value, it is judged whether the target is occluded. When occlusion occurs, the tracking result of KCF is invalid, the filter is not updated, and the prediction result of Kalman filtering is used for calibration; when no occlusion occurs, the filter is updated, and the tracking result of the filter is used for Kalman calibration to obtain the final target position.
[0030] The specific steps are as follows:
[0031] (1) select the video sequence to be tracked, including video sequence, groundfruth text file and frames text file;
[0032] (2) Initialize the correlation filter through the first frame information, and minimize the loss function to find α=(K+λI) -1 y, where I is the identity matrix, y represents the lab...
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