ABSTRACT
For an augmented reality application to be realistic, exact tracking of target objects is essential. However, recent mobile augmented reality applications such as location-based applications or recognition-based applications, showed less quality of realistic augmentation due to inexact tracking methods. Vision based tracking is capable of being exact and robust, but as a mobile augmented reality system, the number of objects it can augment was far limited. In this paper, we propose a new framework that overcomes limitations of previous works in two points. One, our framework is scalable to the number of objects being augmented. Two, our framework provides improved realistic augmentation adopting real-time accurate visual tracking method. To our best knowledge, there has been no system proposed successfully integrating both properties. To achieve scalability, bag of visual words based recognition module with large database runs on remote server and mobile phone tracks and augments the target object by itself. The server and mobile phone is connected through conventional Wi-Fi. Including network latency, our implementation takes 0.2sec for initiating AR service on 10,000 object database, which is acceptable in real-world augmented reality application.
- Chum, O., Philbin J., Sivic J., Isard M., Zisserman A. 2007, Total Recall - Automatic Query Expansion with a Generative Feature Model for Object Retrieval IEEE International Conference on Computer Vision, (Rio de Janeiro, Brazil, October 14--20, 2007)Google Scholar
- Hartley, R., Zisserman, A. 2003, A. Multiple View Geometry, and 2nd ed., Cambridge University Press, pp. 616--622. Google ScholarDigital Library
- Klein, G., Murray, D. 2007. Parallel Tracking and Mapping for Small AR Workspaces 6th IEEE and ACM International Symposium on Mixed and Augmented Reality.(Nara, Japan 13--16 November) Google ScholarDigital Library
- Lowe, D. 2004. Distinctive Image Features from Scale-Invariant Keypoints International Journal of Computer Vision, vol 60, no 2, pp 91--110 Google ScholarDigital Library
- Nister, D., Stewenius, H. 2008, Scalable recognition with vocabulary tree. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (New-York, USA, June. 17--22, 2006) Google ScholarDigital Library
- Wagner, D., Reitmayr, G., Mulloni, A, Drummond, T., Schmalstieg, D. 2008. Real-Time Detection and Tracking for Augmented Reality on Mobile Phones. IEEE Transactions on Visualization and Computer graphics, vol 16, no. 3, pp 355--368. Google ScholarDigital Library
- Wagner, D., Schmalstieg, D., Bischof, H. 2009. Multiple Target Detection and Tracking with Guaranteed Framerates on Mobile Phones. IEEE International Symposium on Mixed and Augmented Reality (Florida, USA, October 19--22, 2009) Google ScholarDigital Library
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