Real-Time Tracking Error Estimation for Augmented Reality for Registration with Linecode Markers

• Published in: IEICE Transactions on Information and Systems Vol. E91.D; no. 7; pp. 2041 - 2050
• Main Authors: BIAN, Zhiqiang, ISHII, Hirotake, SHIMODA, Hiroshi, IZUMI, Masanori
• Format: Journal Article
• Language: English
• Published: Oxford The Institute of Electronics, Information and Communication Engineers 01.07.2008; Oxford University Press
• Subjects: Accuracy; Algorithms; Applied sciences; Artificial intelligence; Augmented reality; Computer science; control theory; systems; error estimation; Exact sciences and technology; Image processing; Information, signal and communications theory; linecode marker; Markers; Pattern recognition. Digital image processing. Computational geometry; Real time; Signal processing; Tasks; Telecommunications and information theory; Tracking; tracking accuracy; tracking error; Tracking errors; tracking method; wheel tracking error computation method; Target tracking; linecode marker; tracking error tracking accuracy; Error estimation; Image processing; tracking method; wheel tracking error computation method; Algorithm; Real time system; Augmented reality; Computation time; Accuracy; Tracking error; Reliability; Computing method
• ISSN: 0916-8532; 1745-1361
• DOI: 10.1093/ietisy/e91-d.7.2041

Augmented reality tasks require a high-reliability tracking method. Large tracking error causes many problems during AR applications. Tracking error estimation should be integrated with them to improve the reliability of tracking methods. Although some tracking error estimation methods have been developed, they are not feasible to be integrated because of computational speed and accuracy. For this study, a tracking error estimation algorithm with screen error estimation based on the characteristic of linecode marker was applied. It can rapidly estimate tracking error. An evaluation experiment was conducted to compare the estimated tracking error and the actual measured tracking error. Results show that the algorithm is reliable and sufficiently fast to be used for real-time tracking error warning or tracking accuracy improvement methods.