請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/63928完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林達德 | |
| dc.contributor.author | Tsung-Cheng Lai | en |
| dc.contributor.author | 賴宗誠 | zh_TW |
| dc.date.accessioned | 2021-06-16T17:23:24Z | - |
| dc.date.available | 2012-08-19 | |
| dc.date.copyright | 2012-08-19 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-08-16 | |
| dc.identifier.citation | 洪國隆。2007。使用立體視覺建立網路虛擬實境之地理資訊系統。碩士論文。臺北：國立臺灣大學生物產業機電工程學研究所。
徐嘉鴻。2011。大尺度虛擬實境場景接合與修補演算法之研究。碩士論文。臺北：國立臺灣大學生物產業機電工程學研究所。 Agarwal, S., N. Snavely, I. Simon, S. M. Seitz and R. Szeliski. 2009. Building rome in a day. The International Conference on Computer Vision. 72-79. Bachrach, A., R. He and N. Roy. 2009. Autonomous flight in unknown indoor environments. The International Journal of Micro Air Vehicles. 1(4): 217-228. Barate, R. and A. Manzanera. 2007. Automatic design of vision-based obstacle avoidance controllers using genetic programming. Proceedings of the 8th International Conference on Evolution Artificielle. 25-36. Birchfield, S. and C. Tomasi. 1999. Depth discontinuities by pixel-to-pixel stereo. The International Journal of Computer Vision. 35(3): 269-293. Bolles, R. C., H. H. Baker and D. H. Marimont. 1987. Epipolar-plane image analysis: An approach to determining structure from motion. The International Journal of Computer Vision. 1(1): 7-55. Brown, D. C. 1966. Decentering distortion of lenses. Photogrammetric Engineering. 32(3): 444-462. Brown, D. C. 1971. Close-range camera calibration. Photogrammetric Engineering. 37(8): 855-866. Chen, S. E. 1995. Quicktime VR: An image-based approach to virtual environment navigation. In Computer Graphics. 29-38. Collins, T. 2004. Graph cut matching in computer vision. University of Edinburgh. Dong, A. and W. Hong. 2004. VPH: a new laser radar based obstacle avoidance method for intelligent mobile robots. The Fifth World Congress on Intelligent Control and Automation. 4681-4685. Ferrari, F., E. Grosso, G. Sandini and M. Magrassi. 1990. A stereo vision system for real time obstacle avoidance in unknown environment. Proceedings of IEEE International Conference on Intelligent Robots and Systems. 703-708. Gledhill, D., G. Y. Tian, D. Taylor and D. Clarke. 2003. Panoramic imaging-a review. Computers and Graphics. 27(3): 435-445. Hancock, J., M. Hebert and C. Thorpe. 1998. Laser intensity-based obstacle detection. The International Conference on Intelligent Robots and Systems. 1541-1546. Hemayed, E. E. 2003. A survey of camera self-calibration. Advanced Video and Signal Based Surveillance. 351-357. Henry, P., M. Krainin, E. Herbst, X. Ren and D. Fox. 2010. RGB-D Mapping: Using depth cameras for dense 3D modeling of indoor environments. The 12th International Symposium on Experimental Robotics. Hirschmuller, H. 2008. Stereo processing by semiglobal matching and mutual information. IEEE Transactions on Pattern Analysis and Machine Intelligence. 30(2): 328-341. Huang, A. S., A. Bachrach, P. Henry, M. Krainin, D. Maturana, D. Fox and N. Roy. 2011. Visual Odometry and Mapping for Autonomous Flight Using an RGB-D Camera. In Under Review. Huang, H. C. and Y. P. Hung. 1997. Spisy: The stereo panoramic imaging system. The Third Workshop on Real-time and Media Systems. 71-78. Koenderink, J. J. and A. J. Van Doorn. 1991. Affine structure from motion. The Journal of the Optical Society of America A. 8(2): 377-385. Lemaire, T., C. Berger, I. K. Jung and S. Lacroix. 2007. Vision-based slam: Stereo and monocular approaches. The International Journal of Computer Vision. 74(3): 343-364. Lucchese, L. and S. K. Mitra. 2002. Using saddle points for subpixel feature detection in camera calibration targets. Proceedings of Asia-Pacific Conference on Circuits and Systems. 191-195. Michels, J., A. Saxena and A. Y. Ng. 2005. High speed obstacle avoidance using monocular vision and reinforcement learning. Proceedings of the 22nd International Conference on Machine Learning. 593-600. Newman, P., G. Sibley, M. Smith, M. Cummins, A. Harrison, C. Mei, I. Posner, R. Shade, D. Schroeter and L. Murphy. 2009. Navigating, recognizing and describing urban spaces with vision and lasers. The International Journal of Robotics Research. 28(11-12): 1406. Ni, K., D. Steedly and F. Dellaert. 2007. Out-of-core bundle adjustment for large-scale 3d reconstruction. The International Conference on Computer Vision. Pollefeys, M., D. Nister, J. M. Frahm, A. Akbarzadeh, P. Mordohai, B. Clipp, C. Engels, D. Gallup, S. J. Kim and P. Merrell. 2008. Detailed real-time urban 3d reconstruction from video. The International Journal of Computer Vision. 78(2): 143-167. Sabe, K., M. Fukuchi, J. S. Gutmann, T. Ohashi, K. Kawamoto and T. Yoshigahara. 2004. Obstacle avoidance and path planning for humanoid robots using stereo vision. Proceedings of IEEE International Conference on Robotics and Automation. 592-597. Saez, J. M. and F. Escolano. 2004. A global 3D map-building approach using stereo vision. The International Conference on Robotics and Automation. 1197-1202. Scharstein, D. and R. Szeliski. 2002. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. The International Journal of Computer Vision. 47(1): 7-42. Sibley, G., L. Matthies and G. Sukhatme. 2008. A sliding window filter for incremental slam. Unifying Perspectives in Computational and Robot Vision: 103-112. Smith, R., M. Self and P. Cheeseman. 1990. Estimating uncertain spatial relationships in robotics. Autonomous Robot Vehicles. 1: 167-193. Snavely, N., S. M. Seitz and R. Szeliski. 2006. Photo tourism: exploring photo collections in 3D. 835-846. Sturm, P. F. and S. J. Maybank. 1999. On plane-based camera calibration: A general algorithm, singularities, applications. In Conference on Computer Vision and Pattern Recognition. 432-437. Thanh, T. N., Y. Sakaguchi, H. Nagahara and M. Yachida. 2006. Stereo slam using two estimators. The International Conference on Robotics and Biomimetics. 19-24. Thrun, S., W. Burgard and D. Fox. 2000. A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping. Proceedings of the IEEE International Conference on Robotics and Automation. 321-328. Tomasi, C. and T. Kanade. 1993. Shape and motion from image streams: a factorization method. Proceedings of the National Academy of Sciences. 90(21): 9795. Trucco, E. and A. Verri. 1998. Introductory techniques for 3-D computer vision. New Jersey: Prentice Hall. Zhang, Z. 1999. Flexible camera calibration by viewing a plane from unknown orientations. The International Conference on Computer Vision. 666-673. Zhang, Z. 2000. A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence. 22(11): 1330-1334. Zhang, Z. 2004. Camera calibration with one-dimensional objects. IEEE Transactions on Pattern Analysis and Machine Intelligence. 26(7): 892-899. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/63928 | - |
| dc.description.abstract | 本研究以多顆CCD攝影機實現遠距且廣角之即時三維地圖模型建立系統。相較於使用Kinect (MicrosoftR Co.) 攝影機，此裝置可在白天進行戶外拍攝，且可視距離較長、視角較廣，不僅可擷取到較豐富的特徵，也能減少誤差的累積，並更容易偵測Loop closure。除了使用加速強健特徵 (Speed Up Robust Features, SURF) 找出連續兩張影像之二維對應特徵點，本研究進一步以交叉比對方式做初步過濾，接著藉由隨機樣本一致性 (RANdom SAmple Consensus, RANSAC) 演算法先去除掉二維的錯誤匹配，再結合視差影像的深度資訊，重新執行三維的RANSAC過濾，消除估測距離錯誤的特徵，最後使用所有的inliers計算出最適當的投影矩陣，並獲得新進影像與地圖之間重疊區域，只將不重疊的部份加入地圖，大幅減少需要儲存的資料量，重複上述動作即可建構出目標空間的三維模型，若建完模型後有發生Loop closure問題，則以Graph-SLAM演算法加以修正。 | zh_TW |
| dc.description.abstract | In this study, a long-distance and wide-angle stereo system for real-time 3D model reconstruction was built. Compared with the Kinect (MicrosoftR Co.) camera, this device can work fine in the daytime outdoor, and the visual distance is longer, the viewing angle is wider. It can not only capture rich features, but also reduce the accumulation of errors and make the Loop closure much easier to be detected. In addition to using the SURF features to find two consecutive images of the two-dimensional corresponding feature points, this study further use cross check to do a preliminary filter in order to pick out the most appropriate corresponding map image. Then combine the feature points with the depth of information, using the RANSAC algorithm to remove the error of the corresponding point and calculate the most appropriate projection matrix to project the new image to map coordinates. After the model was reconstructed, and there is the loop closure detected, the algorithm of Graph-SLAM would be amended. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T17:23:24Z (GMT). No. of bitstreams: 1 ntu-101-R99631006-1.pdf: 67294479 bytes, checksum: 3063806ce1d5d3ca388d622a1cf8c83a (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | 中文摘要 i
Abstract ii 圖目錄 vi 表目錄 viii 第一章 緒論 1 1.1 前言 1 1.2 研究目的 3 第二章 文獻探討 5 2.1 環場影像 5 2.2 立體視覺 6 2.2.1 單攝影機校正 6 2.2.2 雙攝影機校正 8 2.2.3 對應點匹配 10 2.2.4 計算視差 11 2.3 由運動建立結構 (Structure from Motion) 12 2.4 即時建構地圖模型 15 2.4.1 同步定位與地圖構建 (SLAM) 15 2.4.2 視覺里程計 (Visual odometry) 18 2.5 車前障礙物偵測與導航 19 第三章 材料與方法 22 3.1 系統架構 22 3.1.1 硬體架構 23 3.1.2 軟體架構 27 3.2 立體視覺 31 3.2.1 攝影機校正 31 3.2.2 計算視差影像 35 3.3 單組立體視覺建立模型 37 3.3.1 搜尋影像特徵 38 3.3.2 特徵匹配 39 3.3.3 最佳化投影矩陣 40 3.3.4 刪除重疊區點雲 42 3.4 多組立體視覺建立模型 42 3.4.1 空間上的接合 42 3.4.2 時間上的接合 45 第四章 結果與討論 48 4.1 立體視覺 48 4.1.1 攝影機校正 48 4.1.2 計算視差影像 53 4.2 單組立體視覺建立模型 55 4.2.1 三維模型前處理 55 4.2.2 計算投影矩陣 57 4.2.3 點雲減量 60 4.2.4 封閉迴圈接合修正 62 4.3 多組立體視覺建立模型 66 4.3.1 空間上的接合 66 4.3.2 時間上的接合 71 4.4 單組與多組立體視覺的特性比較 81 4.4.1 過濾特徵 81 4.4.2 接合誤差 85 4.4.3 可用的角速度範圍 87 第五章 結論與建議 88 5.1 結論 88 5.2 建議 90 參考文獻 91 | |
| dc.language.iso | zh-TW | |
| dc.subject | 立體視覺 | zh_TW |
| dc.subject | stereo vision | en |
| dc.subject | SURF | en |
| dc.subject | RANSAC | en |
| dc.subject | Graph-SLAM | en |
| dc.title | 應用多組雙眼攝影機系統進行車前三維環境模型重建 | zh_TW |
| dc.title | 3D Model Reconstruction of Vehicle Front Environment Based on Multiple Stereo Cameras | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 連豊力,顏炳郎 | |
| dc.subject.keyword | 立體視覺, | zh_TW |
| dc.subject.keyword | stereo vision,SURF,RANSAC,Graph-SLAM, | en |
| dc.relation.page | 94 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2012-08-16 | |
| dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
| dc.contributor.author-dept | 生物產業機電工程學研究所 | zh_TW |
| 顯示於系所單位： | 生物機電工程學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-101-1.pdf 未授權公開取用 | 65.72 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。