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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/95924完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 趙鍵哲 | zh_TW |
| dc.contributor.advisor | Jen-Jer Jaw | en |
| dc.contributor.author | 王思涵 | zh_TW |
| dc.contributor.author | Szu-Han Wang | en |
| dc.date.accessioned | 2024-09-25T16:09:08Z | - |
| dc.date.available | 2024-09-26 | - |
| dc.date.copyright | 2024-09-25 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-08-11 | - |
| dc.identifier.citation | Agrawal, A., Ramalingam, S., Taguchi, Y., Chari, V., 2012. A theory of multi-layer flat refractive geometry, 2012 IEEE conference on computer vision and pattern recognition. IEEE, pp. 3346-3353.
Chari, V., Sturm, P., 2009. Multiple-view geometry of the refractive plane, BMVC 2009-20th British machine vision conference. The British Machine Vision Association (BMVA), pp. 1-11. Cho, W., Schenk, T., Madani, M., 1993. Resampling digital imagery to epipolar geometry. International Archives of Photogrammetry and Remote Sensing 29, 404-404. Elnashef, B., Filin, S., 2022. Target-free calibration of flat refractive imaging systems using two-view geometry. Optics and Lasers in Engineering 150, 106856. Elnashef, B., Filin, S., 2023a. Theory and closed-form solutions for three-and n-layer flat refractive geometry. International Journal of Computer Vision 131, 877-898. Elnashef, B., Filin, S., 2023b. A three-point solution with scale estimation ability for two-view flat-refractive underwater photogrammetry. ISPRS Journal of Photogrammetry and Remote Sensing 198, 223-237. Ferreira, R., Costeira, J.P., Santos, J.A., 2005. Stereo reconstruction of a submerged scene, Iberian Conference on Pattern Recognition and Image Analysis. Springer, pp. 102-109. Gedge, J., Gong, M., Yang, Y.-H., 2011. Refractive epipolar geometry for underwater stereo matching, 2011 Canadian Conference on Computer and Robot Vision. IEEE, pp. 146-152. Gracias, N., Santos-Victor, J., 2000. Underwater video mosaics as visual navigation maps. Computer Vision and Image Understanding 79, 66-91. Hartley, R., Zisserman, A., 2003. Multiple view geometry in computer vision. Cambridge university press. Hirschmuller, H., 2007. Stereo processing by semiglobal matching and mutual information. IEEE Transactions on pattern analysis and machine intelligence 30, 328-341. James, M.R., Robson, S., Smith, M.W., 2017. 3‐D uncertainty‐based topographic change detection with structure‐from‐motion photogrammetry: precision maps for ground control and directly georeferenced surveys. Earth Surface Processes and Landforms 42, 1769-1788. Jaroslaw Tuszynski, 2024. Triangle/Ray Intersection (https://www.mathworks.com/matlabcentral/fileexchange/33073-triangle-ray-intersection), MATLAB Central File Exchange. Retrieved August 1, 2024. Jordt, A., Köser, K., Koch, R., 2016. Refractive 3D reconstruction on underwater images. Methods in Oceanography 15, 90-113. Maas, H.-G., 2015. On the accuracy potential in underwater/multimedia photogrammetry. Sensors 15, 18140-18152. Möller, T., Trumbore, B., 1997. Fast, Minimum Storage Ray-Triangle Intersection. Journal of Graphics Tools 2, 21-28. Singh, H., Roman, C., Pizarro, O., Eustice, R., 2007. Advances in high resolution imaging from underwater vehicles, Robotics Research: Results of the 12th International Symposium ISRR. Springer, pp. 430-448. Telem, G., Filin, S., 2010. Photogrammetric modeling of underwater environments. ISPRS journal of photogrammetry and remote sensing 65, 433-444. Telem, G., Filin, S., 2013. Photogrammetric modeling of the relative orientation in underwater environments. ISPRS journal of photogrammetry and remote sensing 86, 150-156. Treibitz, T., Schechner, Y., Kunz, C., Singh, H., 2011. Flat refractive geometry. IEEE transactions on pattern analysis and machine intelligence 34, 51-65. van der Zwaan, S., Bernardino, A., Santos-Victor, J., 2002. Visual station keeping for floating robots in unstructured environments. Robotics and Autonomous Systems 39, 145-155. Zhang, C., Zhang, X., Zhu, Y., Li, J., Tu, D., 2018. Model and calibration of underwater stereo vision based on the light field. Measurement Science and Technology 29, 105402. Zhuang, S., Zhang, X., Tu, D., Zhang, C., Xie, L., 2020. A standard expression of underwater binocular vision for stereo matching. Measurement Science and Technology 31, 115012. 王俊凱,2024。具平玻璃介面成像系統水下物像對應及物點定位品質分析,碩士論文,國立臺灣大學土木工程學系,臺北,pp. 1-117。 姚欽舟、莊蘇鋒、屠大維、張旭、謝亮亮,2022。水下透視投影影像非線性畸變校正方法,儀器儀表學報,41。 黃聖日,2014。自空氣往水中之攝影測量相對方位解算,碩士論文,國立臺灣大學土木工程學系,臺北,pp. 1-70。 | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/95924 | - |
| dc.description.abstract | 搭載平玻璃防水保護殼的成像系統(Flat-refractive imaging system)在水下拍攝時,受到多介質環境的影響,光線依照司奈爾定律(Snell’s Law)發生折射,導致原本在單介質環境中共軛光線與基線向量之共面特性,變為四次曲線的共軛對應關係。為了使密匹配程序能夠在核線影像上施作,同時兼顧前方交會三維定位品質,過去文獻提出將匹配和交會拆分為兩個步驟之想法。通過去除匹配影像中的折射畸變,使其接近單介質成像幾何,完成匹配後,再回到原始水下成像幾何執行前方交會。因此,本研究首先提出一套基於近似物距之折射畸變改正方法,使水下影像能夠結合於一般的核線影像產製流程,獲致接近列對列對應之影像資料,本文稱之為「類核線影像」,以便施行密匹配演算法;其次,記錄匹配影像與交會影像間的像點對應關係,以便在匹配完成後,可快速連結至前方交會使用的像點坐標,依循水下成像幾何實現高精度的三維定位。本研究首先以定性和定量方法分析折射改正中關鍵影響因子,接著進行模擬實驗,模擬實務操作中的相關配置,並引入各參數誤差,計算共軛像對間的y視差,以探討本方法有效性。最後,於實際實驗中,使用與模擬實驗對照之相機配置和近似物距模擬方法,通過實際影像資料驗證本方法產製的類核線影像之有效性,並以像對間視差圖及密點雲進行成果分析。實驗成果顯示,當相機具備短玻璃距離時,該系統對於參數和近似物距誤差有較大的容忍度,當近似物距誤差在20%至30%時,仍可有效改正折射並使影像校正至符合列對列對應。對於長玻璃物距,由於本身對誤差的容忍度較低,考量加入參數誤差後,校正效果會下降,建議需提供10%之近似物距誤差,並搭配 1 m以上之物距進行拍攝,方可獲致良好的校正成效。密點雲成果顯示,經本方法改正後,即使在近似物距為50%的條件下,仍可獲得與地真物距改正所獲得的點雲相近的定位品質,且場景幾何並未出現明顯的變形量。 | zh_TW |
| dc.description.abstract | The flat-refractive imaging system is affected by the multi-medium environment during underwater photography, where light refraction occurs according to Snell’s Law. This refraction alters the coplanarity between conjugate rays and baseline vectors in a single-medium environment to a quartic curve conjugate correspondence. To enable dense matching on epipolar images while maintaining 3D positioning quality, previous research proposed a two-step approach separating matching and intersection. By correcting refractive distortion to approximate single-medium imaging geometry, and after matching is completed, the original underwater geometry is then used for forward intersection. Accordingly, this study first proposes a refraction distortion correction method based on approximate object distance, allowing underwater images to be integrated into a general epipolar image production process, resulting in image data with near row-to-row correspondence, referred to as quasi-epipolar images. This facilitates the execution of dense matching algorithms. Additionally, the correspondence between image points in the matching and intersection images is recorded, allowing for quick linkage to the image point coordinates used in forward intersection, thereby achieving high-precision 3D positioning following underwater imaging geometry. This study first qualitatively and quantitatively analyzes the key factors influencing refraction correction, followed by simulation experiments to model relevant configurations applicable to practical operations. The study introduces various parameter errors and calculates the y-parallax between conjugate image pairs to evaluate the effectiveness of this method. Finally, real-world experiments are conducted using camera setups and approximate object distance simulation methods comparable to those in the simulations. These real image data verify the effectiveness of the quasi-epipolar images produced by this method, and the results are analyzed using disparity maps and dense point clouds. Experimental results indicate that when the camera is equipped with a short glass distance, the system tolerates larger errors in parameters and approximate object distances. Even with approximate object distance errors of 20%-30%, refraction can still be effectively corrected, aligning the images to near row-to-row correspondence. For long glass object distances, due to lower tolerance for errors, the correction effect declines when parameter errors are considered. It is recommended to maintain approximate object distance errors within 10% and to shoot at object distances above 1 meter for optimal correction. Dense point cloud results demonstrate that even with a 50% approximation in object distance, the corrected point clouds achieve similar positioning quality to those corrected using the true object distance, with no significant geometric deformation observed in the scene. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-09-25T16:09:07Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-09-25T16:09:08Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 誌謝 i
摘要 iii ABSTRACT iv 目次 vi 圖次 ix 表次 xiii 第一章 緒論 1 1.1 研究動機與目的 1 1.2 研究方法與流程 2 1.3 論文架構 6 第二章 文獻回顧 7 2.1 單介質之核線幾何與核線影像 7 2.2 折射效應與水下成像模式 8 2.2.1 折射效應 8 2.2.2 水下成像模式 9 2.3 水下成像模式之共軛軌跡 10 2.3.1 光線追蹤法 11 2.3.2 軸向共面條件 14 2.3.3 小結 15 2.4 水下密匹配影像獲取 16 2.4.1 單介質模式 16 2.4.2 兩步驟方法 16 2.4.3 小結 17 第三章 研究方法 18 3.1 水下成像系統與光線計算方法 18 3.1.1 水下具平玻璃介面成像系統參數 18 3.1.2 折射效應與介面坐標系 18 3.1.3 折射向量計算方法 20 3.2 基於近似物距資訊之折射畸變改正方法 21 3.2.1 方法原理 21 3.2.2 產製去除折射畸變之介面影像 21 3.3 產製類核線影像 22 3.4 產製連結影像 24 3.5 本方法相關資料處理方法 26 3.5.1 控制點坐標平差 26 3.5.2 水下成像模式之光束法平差 28 3.5.3 近似深度計算 31 3.5.3.1 誤差添加與三角網格模型計算 31 3.5.3.2 深度圖計算 31 3.5.4 雙像前方交會 32 第四章 方法可行性及有效性之實驗分析與討論 34 4.1 折射畸變改正方法之定性與定量分析 34 4.1.1 折射畸變改正方法之影響因子變動量定性分析 34 4.1.2 折射畸變改正方法之影響因子變動量定量分析 36 4.1.3 小結 41 4.2 類核線影像產製共軛像對y視差分析 41 4.2.1 模擬實驗配置 42 4.2.2 近似物距品質探討 44 4.2.3 類核線影像產製之近似物距誤差探討 46 4.2.4 類核線影像產製之參數誤差探討 50 4.2.5 小結與討論 58 第五章 實際場景實驗成果分析與討論 59 5.1 小場域場景:水缸 59 5.1.1 實驗器材與場域介紹 59 5.1.2 資料處理 61 5.1.3 成果展示 65 5.1.4 實驗一:類核線影像產製品質評估 67 5.1.5 實驗二:比較是否改正折射畸變 69 5.1.6 實驗三:影像密匹配與密點雲產製 70 5.1.7 小結 73 5.2 大場域場景:水池 73 5.2.1 實驗場景、控制場及地真資料介紹 74 5.2.2 相機介紹及其內方位參數率定與影像獲取 78 5.2.2.1 相機一:GoPro Hero Black 7 78 5.2.2.2 相機二:Sony RX100M7 81 5.2.3 水下成像系統參數求解 85 5.2.3.1 控制點及檢核點像點量測 85 5.2.3.2 光束法平差解算成果 86 5.2.4 近似深度計算 89 5.2.4.1 誤差添加與三角網格模型計算 89 5.2.4.2 深度圖計算 90 5.2.5 實驗成果一:y視差與參數品質影響探討 92 5.2.5.1 去除透鏡畸變差共軛像對量測 92 5.2.5.2 y視差及參數誤差探討 94 5.2.6 實驗成果二:連結影像品質對交會點位坐標品質影響評估 104 5.2.7 實驗成果三:密匹配與密點雲評估 104 5.2.8 小結 113 第六章 結論與建議 115 6.1 結論 115 6.2 建議 116 參考文獻 117 附錄 120 | - |
| dc.language.iso | zh_TW | - |
| dc.title | 水下具平玻璃介面立體像對之類核線影像產製 | zh_TW |
| dc.title | Retrieving Quasi-Epipolar Imagery of Underwater Flat-refractive Stereo Pair | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 蔡展榮;邱式鴻;莊子毅 | zh_TW |
| dc.contributor.oralexamcommittee | Jaan-Rong Tsay;Shih-Hong Chio;Tzu-Yi Chuang | en |
| dc.subject.keyword | 影像密匹配,水下攝影測量,折射改正,核線影像,具平玻璃介面成像系統, | zh_TW |
| dc.subject.keyword | Dense image matching,Underwater photogrammetry,Refraction correction,Epipolar imagery,Flat-refractive imaging system, | en |
| dc.relation.page | 130 | - |
| dc.identifier.doi | 10.6342/NTU202402965 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2024-08-13 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 土木工程學系 | - |
| dc.date.embargo-lift | 2025-08-09 | - |
| 顯示於系所單位: | 土木工程學系 | |
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