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.

Nuclear power plants (NPPs) must be maintained periodically. Their maintenance efficiency must be improved and human error must be reduced simultaneously to improve NPPs' competitive capability in electricity markets. Although Augmented Reality (AR) offers great possibilities to support NPP maintenance work, some difficulties exist for application of AR to actual work support because current AR systems cannot be implemented in NPP environments without technical improvement. There are several kinds of problems such as recognition distance, tracking accuracy, and a complex working environment when applying AR to NPP field work support. Considerable extension of tracking distance and improvement of accuracy are particularly desired because NPPs are large-scale indoor environments. This study designed a linecode marker, a new type of paper-based marker, along with recognition and tracking algorithms for it to resolve these problems. In contrast to conventional paper-based markers, such as square markers and circle markers, the linecode marker is not merely easier to set up in complex industrial environments: it also enables the use of AR in industrial plants because of its considerable tracking-performance improvement. To evaluate tracking accuracy, the trackable distance, and the tracking speed of the proposed tracking method, an evaluation experiment was conducted in a large room. The experiment results show that the tracking distance is extended extremely over that of the traditional marker-based tracking method: tracking accuracy improved to 20 cm over a 10 m distance. The running speed of the tracking can be as fast as 15 frames per second using a laptop PC.