NDLI: Moving vehicle tracking based on improved tracking–learning

Content Provider	IET Digital Library
Author	Dong, Enzeng Deng, Mengtao Tong, Jigang Jia, Chao Du, Shengzhi
Abstract	This study addresses the tracking–learning–detection (TLD) algorithm for long-term single-target tracking of moving vehicle from video streams. The problems leading to tracking failures in existing TLD methods are discovered, and an improved TLD (ITLD) tracking algorithm is proposed which is more robust to object occlusion and illumination variation. A square root cubature Kalman filter (SRCKF) is employed in the tracker of TLD to predict the position of the object when occlusion occurs. Besides, this study introduces fast retina keypoint (FREAK) feature into the tracker to alleviate the instability caused by illumination variation or scale variation. The overlap comparison and the normalised cross-correlation coefficient (NCC) are introduced to the integrator of the TLD to obtain reliable bounding boxes with improved tracking precision. Experiments are conducted to compare the performance of the state-of-the-art trackers and the proposed method, using the object tracking benchmark that includes 50 video sequences (OTB-50) and TLD datasets. The experimental results show that the proposed ITLD outperforms on both tracking accuracy and robustness. The proposed method can track a moving vehicle even when it is temporally totally occluded.
Starting Page	730
Ending Page	741
Page Count	12
ISSN	17519632
Volume Number	13
e-ISSN	17519640
Issue Number	Issue 8, Dec (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/13/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2018.5787
Journal	IET Computer Vision
Publisher Date	2019-10-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Fast Retina Keypoint Feature Filtering Method in Signal Processing Illumination Variation Improved TLD Tracking Algorithm Improved Tracking Precision Improved Tracking–learning–detection Algorithm ITLD Kalman Filter Knowledge Engineering Technique Learning in AI Long-term Single-target Moving Vehicle Tracking Normalised Cross-correlation Coefficient Object Detection Object Occlusion Object Tracking Optical, Image And Video Signal Processing Square Root Cubature Kalman Filter Target Tracking TLD Datasets TLD Method Tracking Accuracy Tracking Failure Traffic Engineering Computing Video Signal Processing Video Streaming Video Streams
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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