GPS-Induced Disparity Correction for Accurate Object Placement in Augmented Reality
Source abstract
Abstract
The use of augmented reality (AR) continues to increase, particularly in marketing and advertising, where virtual objects are showcased in the AR world, thereby expanding its various applications. In this paper, a method of linking coordinate systems to connect the metaverse with the real world is proposed and a system for correcting and displaying virtual objects in the AR environment is implemented. The proposed method calculates errors to accurately represent virtual objects in AR and presents a method to show these objects without errors. The proposed method was verified through experiments to successfully display virtual objects in AR. To minimize localization errors, semantic segmentation was used to recognize objects and estimate buildings, thereby correcting the device location. An error correction expression is also presented. The proposed system is designed to correct and display virtual objects in AR, with confirmed functionality for location correction.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Robotics and Sensor-Based Localization · Augmented Reality Applications · Robotics and Automated Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Information & Communication Engineering, Wonkwang University, Iksan 54538, Republic of Korea
DAXIB Inc., Smart Building 321, Jeju 63309, Republic of Korea
Department of Computer Software Engineering, Wonkwang University, Iksan 54538, Republic of Korea
Funding
Wonkwang University
References (24)
Show source-provided references
1. Augmented reality and the digital twin: State-of-the-art and perspectives for cybersecurity10.3390/jcp1030026 ↗
2. Augmented reality in education and training10.1007/s11528-012-0559-3 ↗
3. Automotive augmented reality 3D head-up display based on light-field rendering with eye-tracking10.1364/OE.404318 ↗
4. Boboc, R.G., Gîrbacia, F., and Butilă, E.V. (2020). The application of augmented reality in the automotive industry: A systematic literature review. Appl. Sci., 10.10.3390/app10124259 ↗
5. 3D object recognition in cluttered scenes with local surface features: A survey10.1109/TPAMI.2014.2316828 ↗
6. How augmented reality impacts retail marketing: A state-of-the-art review from a consumer perspective10.1080/0965254X.2021.1972439 ↗
7. Choe, J., and Seo, S.A. (2020, January 16–18). A 3D real object recognition and localization on SLAM based augmented reality environment. Proceedings of the 2020 International Conference on Computational Science and Computational Intelligence (CSci), Las Vegas, NV, USA.10.1109/CSCI51800.2020.00140 ↗
8. Rao, J., Qiao, Y., Ren, F., Wang, J., and Du, Q. (2017). A mobile outdoor augmented reality method combining deep learning object detection and spatial relationships for geovisualization. Sensors, 17.10.3390/s17091951 ↗
9. Tracking for augmented reality10.1007/11919476_72 ↗
10. 3-D augmented reality for MRI-guided surgery using integral videography autostereoscopic image overlay10.1109/TBME.2010.2040278 ↗
11. Camera localization for augmented reality and indoor positioning: A vision-based 3D feature database approach10.1080/17538947.2018.1564379 ↗
12. Gao, Z., Hwang, A., Zhai, G., and Peli, E. (2018). Correcting geometric distortions in stereoscopic 3D imaging. PLoS ONE, 13.10.1371/journal.pone.0205032 ↗
13. Emmaneel, R., Oswald, M.R., De Haan, S., and Datcu, D. (2023). Cross-view outdoor localization in augmented reality by fusing map and satellite data. Appl. Sci., 13.10.3390/app132011215 ↗
14. Mithun, N.C., Minhas, K.S., Chiu, H.-P., Oskiper, T., Sizintsev, M., Samarasekera, S., and Kumar, R. (2023, January 25–29). Cross-view visual geo-localization for outdoor augmented reality. Proceedings of the 2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR), Shanghai, China.10.1109/VR55154.2023.00064 ↗
15. Experimental vibration analysis of large structures using 3D DIC technique with a novel calibration method10.1007/s13349-022-00549-5 ↗
16. Localization and tracking of stationary users for augmented reality10.1007/s00371-023-02777-2 ↗
17. A critical analysis of image-based camera pose estimation techniques10.1016/j.neucom.2023.127125 ↗
18. Thomas, J., and Rosenberg, E.S. (2020, January 22–26). Reactive Alignment of Virtual and Physical Environments Using Redirected Walking. Proceedings of the 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), Atlanta, GA, USA.10.1109/VRW50115.2020.00071 ↗
19. Wu, Y., Tang, F., Li, H., and Camera, I.-B. (2018). Image-based camera Localization: An overview. Vis. Comput. Ind. Biomed. Art, 1.10.1186/s42492-018-0008-z ↗
20. Du, Z., Liu, J., and Wang, T. (2022). Augmented reality marketing: A systematic literature review and an agenda for future inquiry. Front. Psychol., 13.10.3389/fpsyg.2022.925963 ↗
21. Coviello, R.G. (2022). Location-Based Augmented Reality Visualization of 3D Models Using a Mobile Application—izanagiXR. [Master’s Thesis, ZHAW School of Management and Law].
22. Kim, S.Y., and Kim, Y.S. (2024). A novel method using 3D interest points to place markers on a large object in augmented reality. Appl. Sci., 14.10.3390/app14020941 ↗
23. Jiang, J.R., and Subakti, H. (2023). An indoor location-based augmented reality framework. Sensors, 23.10.3390/s23031370 ↗
24. Singh, S., Singh, J., Shah, B., Sehra, S.S., and Ali, F. (2022). Augmented reality and GPS-based resource efficient navigation system for outdoor environments: Integrating device camera, sensors, and storage. Sustainability, 14.10.3390/su141912720 ↗