Object tracking in video with correlation filter and using histogram of gradient feature

Document Type : Persian Original Article

Authors

Department of Electronics and Communications Engineering, Faculty of Engineering, University of Birjand, Birjand, Iran.

Abstract

Nowadays, one of the most principal processes of perceiving the content of videos is the moving object tracking, in which the tracking process of a moving object is implemented in each video frame. The use of filters in this field has been increased during the last decade. Correlation filters are one of the most widely used filters in this field, however, using this filter, as usual, may cause the problem of target drifting. The present study proposes a novel method to improve the performance of the correlation filter. The advanced searching strategy can greatly overcome to the problem of target drifting with examining a threshold level by calculating the average and variance in each frame. In this regard, if the level of the threshold is reduced, a mechanism will be activated to recover the target in the current frame. In order to describe the target, the histogram of the oriented gradients feature has been used because this feature shows the changes in illumination variation better than other features. The proposed method has been examined in single-camera mode on the TB50 and TB100 datasets. To evaluate the proposed method, several criteria including precision, correct detection rate (CDR), average location error (ALE), and frame per second are used. The obtained results on the TB50 show that the proposed method, compared to the KCF method, has achieved an improvement around 9% in the precision criterion, improvement 6% in the success rate criterion and a 50% reduction in the ALE criterion. Also, the obtained results on TB100 have increased the precision criterion by approximately 15%, the success rate by 12%, and a favorable reduction of 50% on the ALE.

Keywords


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