政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/60249

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/60249

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政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 > Item 140.119/60249

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題名:	強健式視覺追蹤應用於擴增實境之研究 Robust visual tracking for augmented reality
作者:	王瑞鴻 Wang, Ruei Hong
貢獻者:	何瑁鎧 Hor, Maw Kae 王瑞鴻 Wang, Ruei Hong
關鍵詞:	擴增實境視覺追蹤立體視覺剛體運動 Augmented reality visual tracking stereo vision rigid body motion
日期:	2010
上傳時間:	2013-09-04 17:07:59 (UTC+8)
摘要:	視覺追蹤(visual tracking)一直是傳統電腦視覺研究中相當重要的議題，許多電腦視覺的應用都需要結合視覺追蹤的幫助才能實現。近年來擴增實境(augmented reality)能快速成功的發展，均有賴於視覺追蹤技術上之精進。擴增實境採用視覺追蹤的技術，可將虛擬的物件呈現在被追蹤的物體(真實場景)上，進而達成所需之應用。由於在視覺追蹤上，被追蹤之物體易受外在環境因素影響，例如位移、旋轉、縮放、光照改變等，影響追蹤結果之精確度。本研究中，我們設計了一套全新的圖形標記方法作為視覺追蹤之參考點，能降低位移、旋轉與光照改變所造成追蹤結果的誤差，也能在複雜的背景中定位出標記圖形的正確位置，提高視覺追蹤的精確度。同時我們使用立體視覺追蹤物體，將過去只使用單一攝影機於二維影像資訊的追蹤問題，提升至使用三維空間的幾何資訊來做追蹤。然後透過剛體(rigid)特性找出旋轉量、位移量相同的物件，並且結合一致性隨機取樣(random sample consensus)之技巧以估測最佳的剛體物件運動模型，達到強健性追蹤的目的。另外，我們可由使用者提供之影片資訊中擷取特定資料，透過建模技術將所產生之虛擬物件呈現於使用者介面(或被追蹤之物體)上，並藉由這些虛擬物件，提供真實世界外之資訊，達成導覽指引(或擴增實境)的效果。實驗結果顯示，我們的方法具有辨識時間快、抗光照變化強、定位準確度高的特性，適合於擴增實境應用，同時我們設計的標記圖形尺寸小，方便適用於導覽指引等應用。 Visual tracking is one of the most important research topics in traditional computer vision. Many computer vision applications can not be realized without the integration of visual tracking techniques. The fast growing of augmented reality in recent years relied on the improvement of visual tracking technologies. External environment such as object displacement, rotation, and scaling as well as illumination conditions will always influence the accuracy of visual tracking. In this thesis, we designed a set of markers that can reduce the errors induced by the illumination condition changes as well as that by the object displacement, rotation, and scaling. It can also correctly position the markers in complicated background to increase the tracking accuracy. Instead of using single camera tracking in 2D spaces, we used stereo vision techniques to track the objects in 3D spaces. We also used the properties of rigid objects and search for the objects with the same amount of rotation and displacement. Together with the techniques of random sample consensus, we can estimate the best rigid object motion model and achieve tracking robustness. Moreover, from the user supplied video, we can capture particular information and then generate the virtual objects that can be displaced on the user’s device (or on the tracked objects). Using these techniques we can either achieve navigation or guidance in real world or achieve augmented reality as we expected. The experimental results show that our mechanism has the characteristics of fast recognition, accurate positioning, and resisting to illumination changes that are suitable for augmented reality. Also, the size of the markers we designed is very small and good for augmented reality application.
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Campos, "On the Design and Evaluation of a Precise Scalable Fiducial Marker Framework," Conference on 23rd SIBGRAPI Graphics, Patterns and Images, pp. 216-223, 2010. [7] L. Di Stefano, S. Mattoccia, and F. Tombari, "ZNCC-based template matching using bounded partial correlation," Pattern Recognition Letters, vol. 26, pp. 2129-2134, 2005. [8] M. Fiala, "ARTag, a fiducial marker system using digital techniques," Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 590-596 ,2005. [9] M. Fiala, "Designing Highly Reliable Fiducial Markers," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, pp. 1317-1324, 2010. [10] J. Fischer, M. Eichler, and D. Bartz, "A hybrid tracking method for surgical augmented reality," Computers and Graphics, vol. 31, pp. 39-52, 2007. [11] M. A. Fischler and R. C. Bolles, "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography," Communications of the ACM, vol. 24, pp. 381-395, 1981. [12] D. Flohr and J. Fischer, "A lightweight ID-based extension for marker tracking systems," Proceedings of Eurographics Symposium on Virtual Environments, pp. 59-64, 2007. [13] Y. Genc, S. Riedel, F. Souvannavong, C. Akinlar, and N. Navab, "Marker-less tracking for AR: a learning-based approach," Proceedings of International Symposium on Mixed and Augmented Reality, pp. 295-304, 2002. [14] H. Grabner, J. Matas, L. Van Gool, and P. Cattin, "Tracking the invisible: Learning where the object might be," IEEE Conference on Computer Vision and Pattern Recognition, pp. 1285-1292, 2010. [15] G. D. Hager and P. N. Belhumeur, "Real-time tracking of image regions with changes in geometry and illumination," Proceedings of Computer Vision and Pattern Recognition, pp. 403-410, 1996. [16] C. Harris and M. Stephens, "A Combined Corner and Edge Detection," Proceedings of The Fourth Alvey Vision Conference, pp. 147-151, 1988. [17] H. Kato and M. Billinghurst, "Marker tracking and HMD calibration for a video-based augmented reality conferencing system," Proceedings of the 2nd International Workshop on Augmented Reality, pp. 85-94, 1999. [18] D. Lowe, "Distinctive image features from scale-invariant keypoints," International Journal of Computer Vision, vol. 60, pp. 91-110, 2004. [19] D. Marissa, A.-M. Moises, M.-G. Lourdes, and R. Isaac, "Multi-User Networked Interactive Augmented Reality Card Game," Proceedings of International Conference on Cyberworld , pp. 177-182, 2006. [20] W. Piekarski and B. H. Thomas, "Using ARToolKit for 3D hand position tracking in mobile outdoor environments," Proceedings of The First IEEE International Augmented Reality Toolkit Workshop, pp. 2 , 2002. [21] Z. Qi, S. Brennan, and T. Hai, "Differential EMD Tracking," Proceedings of International Conference on Computer Vision, pp. 1-8, 2007. [22] G. Reitmayr and T. W. Drummond, "Going out: robust model-based tracking for outdoor augmented reality," Proceedings of International Symposium on Mixed and Augmented Reality, pp. 109-118, 2006. [23] T. Sielhorst, M. Feuerstein, and N. Navab, "Advanced Medical Displays: A Literature Review of Augmented Reality," Journal of Display Technologyf, vol. 4, pp. 451-467, 2008. [24] G. Silveira and E. Malis, "Real-time Visual Tracking under Arbitrary Illumination Changes," Proceedings of Computer Vision and Pattern Recognition, pp. 1-6, 2007. [25] L. Taehee and T. Hollerer, "Handy AR: Markerless Inspection of Augmented Reality Objects Using Fingertip Tracking," Proceedings of the 2007 11th IEEE International Symposium on Wearable Computers, pp.1-8, 2007. [26] L. Taehee and T. Hollerer, "Multithreaded Hybrid Feature Tracking for Markerless Augmented Reality," IEEE Transactions on Visualization and Computer Graphics , vol. 15, pp. 355-368, 2009. [27] D. Wagner and D. Schmalstieg, "Artoolkitplus for pose tracking on mobile devices," Proceedings of 12th Computer Vision Winter Workshop, pp. 6-8, 2007. [28] Z. Xiang, S. Fronz, and N. Navab, "Visual marker detection and decoding in AR systems: a comparative study," Proceedings of the 1st International Symposium on Mixed and Augmented Reality, pp. 97-106, 2002. [29] S. You and U. Neumann, "Mobile Augmented Reality for Enhancing E-Learning and E-Business," International Conference on Internet Technology and Applications , pp. 1-4, 2010. [30] J.-Y. Bouguet. Camera Calibration Toolbox for Matlab. www.vision.caltech.edu/bouguetj/calib_doc/
描述:	碩士國立政治大學資訊科學學系 98753014 99
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0098753014
資料類型:	thesis
顯示於類別:	[資訊科學系] 學位論文

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