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Open AccessArticle

A Visual Object Tracking Algorithm Based on Improved TLD

1
School of Automation, Southeast University, Nanjing 210096, China
2
School of Automation, Central South University, Changsha 410083, China
*
Author to whom correspondence should be addressed.
Algorithms 2020, 13(1), 15; https://doi.org/10.3390/a13010015
Received: 6 December 2019 / Revised: 28 December 2019 / Accepted: 31 December 2019 / Published: 1 January 2020
Visual object tracking is an important research topic in the field of computer vision. Tracking–learning–detection (TLD) decomposes the tracking problem into three modules—tracking, learning, and detection—which provides effective ideas for solving the tracking problem. In order to improve the tracking performance of the TLD tracker, three improvements are proposed in this paper. The built‐in tracking module is replaced with a kernelized correlation filter (KCF) algorithm based on the histogram of oriented gradient (HOG) descriptor in the tracking module. Failure detection is added for the response of KCF to identify whether KCF loses the target. A more specific detection area of the detection module is obtained through the estimated location provided by the tracking module. With the above operations, the scanning area of object detection is reduced, and a full frame search is required in the detection module if objects fails to be tracked in the tracking module. Comparative experiments were
conducted on the object tracking benchmark (OTB) and the results showed that the tracking speed and accuracy was improved. Further, the TLD tracker performed better in different challenging scenarios with the proposed method, such as motion blur, occlusion, and environmental changes.
Moreover, the improved TLD achieved outstanding tracking performance compared with common tracking algorithms.
Keywords: object tracking; tracking–learning–detection; kernelized correlation filters; histogram of oriented gradient; real time; robustness object tracking; tracking–learning–detection; kernelized correlation filters; histogram of oriented gradient; real time; robustness
MDPI and ACS Style

Zhen, X.; Fei, S.; Wang, Y.; Du, W. A Visual Object Tracking Algorithm Based on Improved TLD. Algorithms 2020, 13, 15.

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