摘要
In order to improve the user’s satisfaction with the augmented reality (AR) technology and the accuracy of the service, it is important to obtain the exact position of the user. Frequently used techniques for finding outdoors locations is the global positioning system (GPS), which is less accurate indoors. Therefore, an indoor position is measured by comparing the reception level about access point (AP) signal of wireless fidelity (Wi-Fi) or using bluetooth low energy (BLE) tags. However, Wi-Fi and Bluetooth require additional hardware installation. In this paper, the proposed method of estimating the user’s position uses an indoor image and indoor coordinate map without additional hardware installation. The indoor image has several feature points extracted from fixed objects. By matching the feature points with the feature points of the user image, we can obtain the position of the user on the Indoor map by obtaining six or more pixel coordinates from the user image and solving the solution using the perspective projection formula. The experimental results show that the user position can be obtained more accurately in the indoor environment by using only the software without additional hardware installation.
In order to improve the user’s satisfaction with the augmented reality (AR) technology and the accuracy of the service, it is important to obtain the exact position of the user. Frequently used techniques for finding outdoors locations is the global positioning system (GPS), which is less accurate indoors. Therefore, an indoor position is measured by comparing the reception level about access point (AP) signal of wireless fidelity (Wi-Fi) or using bluetooth low energy (BLE) tags. However, Wi-Fi and Bluetooth require additional hardware installation. In this paper, the proposed method of estimating the user’s position uses an indoor image and indoor coordinate map without additional hardware installation. The indoor image has several feature points extracted from fixed objects. By matching the feature points with the feature points of the user image, we can obtain the position of the user on the Indoor map by obtaining six or more pixel coordinates from the user image and solving the solution using the perspective projection formula. The experimental results show that the user position can be obtained more accurately in the indoor environment by using only the software without additional hardware installation.
