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研究生:李穎忠
研究生(外文):Weng Chong Lei
論文名稱:應用於DNA解煉曲線分析的高效互動式粒子追蹤方法
論文名稱(外文):An Effective & Interactive Approach to Particle Tracking for DNA Melting Curve Analysis
指導教授:張智星張智星引用關係
口試委員:盧彥文葉梅珍
口試日期:2015-07-30
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:資訊工程學研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:中文
論文頁數:42
中文關鍵詞:DNA解煉曲線分析影片標記粒子追蹤
外文關鍵詞:DNA melting curve analysisVideo annotationParticle tracking
相關次數:
  • 被引用被引用:0
  • 點閱點閱:47
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
DNA解煉曲線分析是一種研究DNA序列變異的重要技術,但是研究人員必須標記螢光顯微鏡拍下的實驗影片才能得到實驗數據,這是一個很花時間的工作。本論文提出一個互動式的影片標記系統,這系統利用粒子追蹤方法自動替使用者標記實驗影片,並設有互動機制,讓使用者只需要標記一小部分,就可以完成整個標記工作。我們的系統經過實驗驗證其有效性。

DNA melting curve analysis is an important technique for the detection of DNA sequence variants. However, it requires object annotation in video from fluorescence microscopy, which is tedious. In this thesis, we present an interactive video annotation system that tracks the particles in video interactively and provides all the labels with little manual effort. Evaluations on realistic video data demonstrate the effectiveness of our system.

口試委員會審定書 i
中文摘要 ii
ABSTRACT iii
目錄 iv
圖目錄 vi
表目錄 ix
1 導論 1
1.1 研究動機 1
1.2 相關研究 2
1.3 論文架構 3
2 影片特性 4
3 系統設計 7
3.1 粒子圓心位置和半徑的估計方法 7
3.2 粒子追蹤 10
3.2.1 相關濾波器追蹤法 11
3.2.2 正規化互相關比對法 15
3.2.3 結合正規化互相關比對法和線性外推法 16
3.3 互動式標記方法 19
4 實驗 23
4.1 調整系統參數 25
4.2 實驗結果 34
4.3 錯誤分析 37
5 總結 40
參考文獻 41



[1]J. C. Crocker and D. G. Grier, “Methods of digital video microscopy for colloidal studies,” Journal of Colloid and Interface Science, vol. 179, no. 1, pp. 298–310, 1996.
[2]K. Jaqaman, D. Loerke, M. Mettlen, H. Kuwata, S. Grinstein, S. L. Schmid, and G. Danuser, “Robust single-particle tracking in live-cell time-lapse sequences,” Nature Methods, vol. 5, no. 8, pp. 695–702, 2008.
[3]P. J. Lu, P. A. Sims, H. Oki, J. B. Macarthur, and D. A. Weitz, “Target-locking acquisition with real-time confocal (TARC) microscopy,” Optics Express, vol. 15, pp. 8702–8712, 2007.
[4]I. Sbalzarini and P. Koumoutsakos, “Feature point tracking and trajectory analysis for video imaging in cell biology,” Journal of Structural Biology, vol. 151, no. 2, pp. 182–195, 2005.
[5]N. Chenouard, I. Smal, F. de Chaumont, M. Maska, I. F. Sbalzarini, Y. Gong, J. Cardinale, C. Carthel, S. Coraluppi, M. Winter, A. R. Cohen, W. J. Godinez, K. Rohr, Y. Kalaidzidis, L. Liang, J. Duncan, H. Shen, Y. Xu, K. E. G. Magnusson, J. Jalden, H. M. Blau, P. Paul-Gilloteaux, P. Roudot, C. Kervrann, F. Waharte, J.-Y. Tinevez, S. L. Shorte, J. Willemse, K. Celler, G. P. van Wezel, H.-W. Dan, Y.-S. Tsai, C. O. de Solorzano, J.-C. Olivo-Marin, and E. Meijering, “Objective comparison of particle tracking methods,” Nature Methods, vol. 11, no. 3, pp. 281–289, Mar. 2014.
[6]J. Yuen, B. C. Russell, C. Liu, and A. Torralba, “LabelMe video: Building a video database with human annotations,” in International Conference on Computer Vision (ICCV), 2009, pp. 1451–1458.
[7]A. M. Buchanan and A. W. Fitzgibbon, “Interactive feature tracking using K-D trees and dynamic programming,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2006, vol. 1, pp. 626–633.
[8]C. Vondrick and D. Ramanan, “Video annotation and tracking with active learning,” in Neural Information Processing Systems (NIPS), 2011, pp. 28–36.
[9]C. Vondrick, D. Ramanan, and D. Patterson, “Efficiently scaling up video annotation with crowdsourced marketplaces,” in European Conference on Computer Vision (ECCV), 2010, pp. 610–623.
[10]A. Yao, J. Gall, C. Leistner, and L. Van Gool, “Interactive object detection,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012, pp. 3242–3249.
[11]K. Zhang, L. Zhang, Q. Liu, D. Zhang, and M.-H. Yang, “Fast visual tracking via dense spatio-temporal context learning,” in European Conference on Computer Vision (ECCV), 2014, pp. 127–141.
[12]D. S. Bolme, J. R. Beveridge, B. A. Draper, and Y. M. Lui, “Visual object tracking using adaptive correlation filters,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010, pp. 2544–2550.
[13]J. F. Henriques, R. Caseiro, P. Martins, and J. Batista, “High-speed tracking with kernelized correlation filters,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 3, pp. 583–596, 2015.
[14]J. F. Henriques, R. Caseiro, P. Martins, and J. Batista, “Exploiting the circulant structure of tracking-by-detection with kernels,” in European Conference on Computer Vision (ECCV), 2012, pp. 702–715.

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