本篇論文簡介一個雲端資料庫影像定位系統的雛形，再細項說明裝置端搭載立體相機擁有深度量測能力並已從雲端資料庫取得相似影像後如何利用影像中的共同特徵進行極線幾何運算，得到兩相機拍攝位置的連線在相平面上的點，再使用立體視覺相機的基線幾何關係求得資料庫相片拍攝位置對立體相機之間的距離關係。實驗的部份，將以室內為實驗環境，利用已知的參考影像與載具上bumblebee2立體視覺相機行進間拍攝的影像進行本論文的演算，呈現裝置端定位的可行性。

What we want to present in this thesis is that matching the correct feature from images in the same place but in different positions. We get the position of camera takes image in image database on image plane of stereo camera by using epipolar geometry. We have two images with the position of the same image in image database. With stereo vision correspondence, we get depth between stereo camera and image in image database. In the experiment, we present our novel method that it works. In conclusion and future work, we discuss some future task after we have the results.

1. Angeli, A., et al. Visual topological SLAM and global localization. in Robotics and Automation, 2009. ICRA '09. IEEE International Conference on. 2009.
2. Bailey, T., J. Nieto, and E. Nebot. Consistency of the FastSLAM algorithm. in Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on. 2006.
3. Cummins, M. and P. Newman, FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance. Int. J. Rob. Res., 2008. 27(6): p. 647-665.
4. Maybeck, P.S., Stochastic models, estimation, and control. Vol. 3. 1982: Access Online via Elsevier.
5. Montemerlo, M., et al. FastSLAM: A factored solution to the simultaneous localization and mapping problem. in AAAI/IAAI. 2002.
6. Montemerlo, M., et al. FastSLAM 2.0: An improved particle filtering algorithm for simultaneous localization and mapping that provably converges. in In Proc. of the Int. Conf. on Artificial Intelligence (IJCAI. 2003.
7. Ranganathan, A. and F. Dellaert, Online probabilistic topological mapping. Int. J. Rob. Res., 2011. 30(6): p. 755-771.
8. Glover, A.J., et al. FAB-MAP+ RatSLAM: appearance-based SLAM for multiple times of day. in Robotics and Automation (ICRA), 2010 IEEE International Conference on. 2010. IEEE.
9. Maddern, W., M. Milford, and G. Wyeth, CAT-SLAM: probabilistic localisation and mapping using a continuous appearance-based trajectory. The International Journal of Robotics Research, 2012. 31(4): p. 429-451.
10. Milford, M.J. and G.F. Wyeth. SeqSLAM: Visual route-based navigation for sunny summer days and stormy winter nights. in Robotics and Automation (ICRA), 2012 IEEE International Conference on. 2012.
11. Besl, P.J. and N.D. McKay. Method for registration of 3-D shapes. in Robotics-DL tentative. 1992. International Society for Optics and Photonics.
12. Henry, P., et al., RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments. The International Journal of Robotics Research, 2012. 31(5): p. 647-663.
13. Klein, G. and D. Murray. Parallel Tracking and Mapping for Small AR Workspaces. in Mixed and Augmented Reality, 2007. ISMAR 2007. 6th IEEE and ACM International Symposium on. 2007.
14. Zhang, Z., Iterative point matching for registration of free-form curves and surfaces. International journal of computer vision, 1994. 13(2): p. 119-152.
15. Lowe, D.G., Distinctive image features from scale-invariant keypoints. International journal of computer vision, 2004. 60(2): p. 91-110.
16. Yan, K. and R. Sukthankar. PCA-SIFT: a more distinctive representation for local image descriptors. in Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on. 2004.
17. Bay, H., T. Tuytelaars, and L. Gool, SURF: Speeded Up Robust Features, in Computer Vision – ECCV 2006, A. Leonardis, H. Bischof, and A. Pinz, Editors. 2006, Springer Berlin Heidelberg. p. 404-417.
18. Calonder, M., et al., BRIEF: binary robust independent elementary features, in Proceedings of the 11th European conference on Computer vision: Part IV2010, Springer-Verlag: Heraklion, Crete, Greece. p. 778-792.
19. Leutenegger, S., M. Chli, and R.Y. Siegwart. BRISK: Binary Robust invariant scalable keypoints. in Computer Vision (ICCV), 2011 IEEE International Conference on. 2011.
20. Filliat, D. Interactive learning of visual topological navigation. in Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on. 2008.
21. Glover, A., et al. OpenFABMAP: An open source toolbox for appearance-based loop closure detection. in Robotics and Automation (ICRA), 2012 IEEE International Conference on. 2012.
22. Tsai, R.Y., A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. Robotics and Automation, IEEE Journal of, 1987. 3(4): p. 323-344.
23. Agrawal, M., K. Konolige, and L. Iocchi, Real-Time Detection of Independent Motion using Stereo, in Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 022005, IEEE Computer Society. p. 207-214.
24. Zhang, Z., Determining the Epipolar Geometry and its Uncertainty: A Review. International Journal of Computer Vision, 1998. 27(2): p. 161-195.
25. Luong, Q.-T. and O.D. Faugeras, The fundamental matrix: Theory, algorithms, and stability analysis. International Journal of Computer Vision, 1996. 17(1): p. 43-75.
26. Longuet-Higgins, H., A computer algorithm for reconstructing a scene from two projections. Readings in Computer Vision: Issues, Problems, Principles, and Paradigms, MA Fischler and O. Firschein, eds, 1987: p. 61-62.
27. Hartley, R.I., In defense of the eight-point algorithm. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1997. 19(6): p. 580-593.
28. Tsai, R.Y. An efficient and accurate camera calibration technique for 3D machine vision. in Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 1986. 1986.
29. Zhang, Z., A flexible new technique for camera calibration. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2000. 22(11): p. 1330-1334.
30. Pollefeys, M., Self calibration and metric 3d reconstruction from uncalibrated image sequences, 1999, Leuven.
31. http://ww2.ptgrey.com/stereo-vision/bumblebee-2