請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74961完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 施吉昇 | |
| dc.contributor.author | Hao-Yu Chen | en |
| dc.contributor.author | 陳皓宇 | zh_TW |
| dc.date.accessioned | 2021-06-17T09:11:20Z | - |
| dc.date.available | 2019-09-03 | |
| dc.date.copyright | 2019-09-03 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-08-29 | |
| dc.identifier.citation | [1] D. Stoyanov, M. V. Scarzanella, P. Pratt, and G.-Z. Yang, “Real-time stereo reconstruction in robotically assisted minimally invasive surgery,” in International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, 2010, pp. 275–282.
[2] P.-L. Chang, D. Stoyanov, A. J. Davison et al., “Real-time dense stereo reconstruction using convex optimisation with a cost-volume for image-guided robotic surgery,” in International Conference on Medical Image Computing and ComputerAssisted Intervention. Springer, 2013, pp. 42–49. [3] X. Liu, A. Sinha, M. Unberath, M. Ishii, G. D. Hager, R. H. Taylor, and A. Reiter, “Self-supervised learning for dense depth estimation in monocular endoscopy,” in OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis. Springer, 2018, pp. 128–138. [4] A. Hosni, C. Rhemann, M. Bleyer, C. Rother, and M. Gelautz, “Fast cost-volume filteringforvisualcorrespondenceandbeyond,”IEEETransactionsonPatternAnalysis and Machine Intelligence, vol. 35, no. 2, pp. 504–511, 2012. [5] C.Schmalz,F.Forster,A.Schick,andE.Angelopoulou,“Anendoscopic3dscanner based on structured light,” Medical image analysis, vol. 16, no. 5, pp. 1063–1072, 2012. [6] J. Uhrig, N. Schneider, L. Schneider, U. Franke, T. Brox, and A. Geiger, “Sparsity invariant cnns,” in International Conference on 3D Vision (3DV), 2017. [7] D. Stoyanov, A. Darzi, and G. Z. Yang, “A practical approach towards accurate dense3ddepthrecoveryforroboticlaparoscopicsurgery,”ComputerAidedSurgery, vol. 10, no. 4, pp. 199–208, 2005. [8] Z. Zhang, “A flexible new technique for camera calibration,” IEEE Transactions on pattern analysis and machine intelligence, vol. 22, 2000. [9] J. Jung, J.-Y. Lee, Y. Jeong, and I. S. Kweon, “Time-of-flight sensor calibration for a color and depth camera pair,” IEEE transactions on pattern analysis and machine intelligence, vol. 37, no. 7, pp. 1501–1513, 2014. [10] P.-C. Su, J. Shen, W. Xu, S.-C. Cheung, and Y. Luo, “A fast and robust extrinsic calibration for rgb-d camera networks,” Sensors, vol. 18, no. 1, p. 235, 2018. [11] M. Lindner, I. Schiller, A. Kolb, and R. Koch, “Time-of-flight sensor calibration for accurate range sensing,” Computer Vision and Image Understanding, vol. 114, no. 12, pp. 1318–1328, 2010. [12] P.-C. Wu, R. Wang, K. Kin, C. Twigg, S. Han, M.-H. Yang, , and S.-Y. Chien, “Dodecapen: Accurate 6dof tracking of a passive stylus,” in ACM Symposium on User Interface Software and Technology (UIST), 2017. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74961 | - |
| dc.description.abstract | 在內視鏡手術中，醫生常常只能以二維的影像資訊進行三維的手
術操作，增添了不必要的執行難度，如果能提供準確的三維資訊輔以 恰當的顯示方式，將可讓內視鏡手術操作更加容易。但現今內視鏡手 術環境下的深度預測演算法，還有許多情境是無法正確預測立體資訊 的，包含鏡像反射、變動劇烈的視差、手術器械造成的遮蔽、煙霧和 液體等。此外目前的定量評估方法也有一些限制，包含目標物體不能 形變、畫面無法有手術器械以及沒有直接的真質等。 因此，我們提出一個外部的深度相機和內視鏡鏡頭的校正方法，藉 此能提供包含影像與深度資訊的資料。之後，將能進一步以這樣的資 料進行深度預測類神經網路的訓練，以及更無限制的內視鏡情境深度 預測演算法的定量評估。 | zh_TW |
| dc.description.abstract | This work proposes a calibration method between a narrow field of view cameraandadepthcamerainanendoscope-likescenario. Anendoscopy-like scenario has several properties including limited specular reflective surface, a camera with a narrow field of view. Instead of pushing the accuracy of the target marker with low-resolution data, we propose a solution with a loss function. The proposed loss function utilizes all of the 3 dimensions points of the checkerboard measured with the depth camera, and calculates the distance between projected 3D positions onto 2D image surface and the color image. The final re-projected error is improved to average under 1 millimeters, and further trainingand evaluation of depth estimation algorithms could be performed. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T09:11:20Z (GMT). No. of bitstreams: 1 ntu-108-R04944055-1.pdf: 5470332 bytes, checksum: 0edd309717a55d18e46c5345e97d3b51 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | Acknowledgments i
摘要 ii Abstract iii 1 Introduction 1 1.1 Motivation 1 1.2 Contribution 3 1.3 Thesis Organization 3 2 BackgroundandRelatedWork 4 2.1 Depth measurement/estimation mechanism 4 2.1.1 Stereo vision 4 2.1.2 Structure light 5 2.1.3 Time-of-flight 5 2.1.4 Depth estimation methods 5 2.2 Camera calibration 6 3 SystemArchitectureandProblemDefinition 8 3.1 System Architecture 8 3.2 Problem Definition 9 3.3 Challenges 9 3.3.1 Noisiness 9 3.3.2 Sparseness 10 3.3.3 Occlusions 11 3.3.4 Time synchronization 11 4 DesignandImplementation 12 4.1 Proposed method 12 4.2 Plane fitting 13 4.3 Two-dimensions corners matching 14 4.3.1 Color camera parameters 14 4.3.2 Color camera calibration 16 4.4 Three-dimension corners matching 17 4.5 Point-to-square optimization 18 5 PerformanceEvaluation 19 5.1 Experimental setting 19 5.2 Evaluation result 20 5.3 Quality result 24 6 Conclusion 26 Bibliography 27 | |
| dc.language.iso | en | |
| dc.title | 深度視覺相機與窄視野彩色相機之校正方法 | zh_TW |
| dc.title | An Extrinsic Calibration for Depth Camera to Narrow Field of View Color Camera | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 林忠緯,蔡欣穆 | |
| dc.subject.keyword | 內視鏡,深度資訊,相機校正,鏡面反射,真質, | zh_TW |
| dc.subject.keyword | endoscopy,depth,calibration,specularly re?ection,ground truth, | en |
| dc.relation.page | 28 | |
| dc.identifier.doi | 10.6342/NTU201904109 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-08-29 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
| 顯示於系所單位： | 資訊網路與多媒體研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-108-1.pdf 目前未授權公開取用 | 5.34 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。