Re‐detection object tracking algorithm in the cyber physical system

Cyber physical system (CPS) is a complex system combining computation, network and physics; object tracking is an important application of CPS. To solve the problem that the traditional kernel correlation filtering tracking algorithm cannot recover the lost object, the authors propose a re‐detection...

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Bibliographic Details
Published in:IET cyber-physical systems Vol. 5; no. 3; pp. 253 - 262
Main Authors: Hu, Zhaohua, Huang, JiaJing
Format: Journal Article
Language:English
Published: Southampton The Institution of Engineering and Technology 01.09.2020
John Wiley & Sons, Inc
Wiley
Subjects:
Adaptive algorithms
adaptive detection criterion
Algorithms
Boxes
Complex systems
CPS
Criteria
cyber physical system
Cyber-physical systems
Deep learning
Distance learning
edge boxes algorithm
filtering theory
lost object
Neural networks
object detection
object tracking
physics
re-detection object tracking algorithm
Target detection
target tracking
Tracking
tracking procedure
ISSN:2398-3396, 2398-3396
Online Access:Get full text
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Summary:Cyber physical system (CPS) is a complex system combining computation, network and physics; object tracking is an important application of CPS. To solve the problem that the traditional kernel correlation filtering tracking algorithm cannot recover the lost object, the authors propose a re‐detection object tracking algorithm. The proposed algorithm mainly designs a new adaptive detection criterion. By comparing the value of detection criterion and the value of the experience threshold, it can be judged whether the current target is lost or not. When the object tracking fails, the proposed method can generate target candidate boxes by using the edge boxes algorithm and select the best target location by applying the non‐maximum suppression and the Euclidean metric methods. In addition, a fast multi‐scale estimation method and an adaptive updating method are added to the tracking procedure to further improve the overall performance of the algorithm. Experimental results show that the proposed approach has a good performance in terms of precision and success rates.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2398-3396
2398-3396
DOI:10.1049/iet-cps.2019.0086