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研究生:蔡協宏
研究生(外文):Tsai, Hsieh-Hung
論文名稱:立體攝影機即時預覽與分析系統
論文名稱(外文):The instant preview and analysis system of stereo vision camera
指導教授:余興政
口試委員:張忠誠陳進富黃加恩
口試日期:2016-01-07
學位類別:碩士
校院名稱:國立臺灣海洋大學
系所名稱:系統工程暨造船學系
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:中文
論文頁數:87
中文關鍵詞:自動校正對位即時預覽參數最佳化立體攝影機立體影像串流
外文關鍵詞:Automatic alignmentInstant previewParameter optimizationStereo cameraStereo video stream
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本文所建立的立體攝影機即時預覽與分析系統具有拍攝前自動校正對位立體相機與即時不斷截取具有立體感的深度串流影像,該分析系統能夠即時繪製深度灰階圖與畫面景深錯誤資訊,因此能夠有效輔助影視人員縮短立體影像拍攝時間,不僅可以降低製作成本之外,亦可確保拍攝出優良的立體影片品質;且該系統所發展的校正對位流程能夠同時考量理論正確性及實際應用性從而因應環境較差的拍攝環境,例如:低光源、無明確校正物(校正板)等;另一方面,該系統也提供自動的調整視差演算法及控制機構達成簡化視差校正時間並且獲得更合適的實驗結果。立體攝影機即時預覽與分析系統為達到最佳化立體感的呈現,故採用硬體控制機構實現自動校正對位與自動調整雙攝影機間距與夾角,不僅可提高立體內容的拍攝效率及品質,亦可大幅減少影片後製調整的時間,及降低現場因拍攝環境惡劣所造成的景深誤差,故可有效提昇立體影片的製作效率,且大幅降低調整影片的後製成本。
This thesis develops an instant preview and analysis system of stereo vision camera, and the system has an automatic alignment function before making films and can capture continually stereo video streams with controlled depth of field in real time. The system not only can assist film-makers in reducing filmed time and cost effectively, but also can make sure the quality of stereo films. In accordance with the system, a novel alignment schedule that considers theoretical accuracy and actual application has been developed. It adopts in harsh filmed environment, e.g. low light source, indefinite calibrator, and etc. In addition, the tuning disparity algorithm and control mechanism with high precision have been developed to achieve correct adjusted results effectively. That prototype with parameter optimization can adopt hardware mechanism to achieve automatic alignment function, and to obtain optimal stereo function by adjusting the included gap and angle between two cameras. Consequently, that with parameter optimization can enhance the quality of stereo films effectively and can reduce filmed errors and save retouched cost in harsh filmed environment.
目錄
摘要 iv
Abstract v
致謝 vi
目錄 vii
圖目錄 ix
表目錄 xi
第一章 緒論 1
1.1 研究動機 1
1.2 研究目的 2
1.3 文獻回顧 3
1.4 現況分析 6
1.5 研究流程說明 9
1.5.1 研究流程 9
1.5.2 研究架構 10
第二章 立體影像系統 11
2.1 立體影像系統基本架構 11
2.2 系統剖析與相關理論探討 12
2.2.1 立體攝影機與附屬設備 12
2.2.1.1 立體攝影機參數效正 13
2.2.1.2 立體攝影機同步測試 17
2.2.2 立體影像預覽與重播系統 19
2.2.3 立體影像分析系統 22
2.2.4 可程式控制攝影機支架 24
第三章 研究方法 26
3.1 系統分析 26
3.1.1 硬體設備分析 26
3.1.1.1 立體攝影機 27
3.1.1.2 2D即時顯示器 28
3.1.1.3 立體重播與分析監視器 29
3.1.1.4 個人電腦及其附屬設備 30
3.1.1.5 立體攝影機支架 32
3.1.2 軟體程式分析 33
3.1.2.1 視差分析程式 33
3.1.2.2 對比分析程式 34
3.1.2.3 垂直視差分析程式 34
3.1.2.4 專注效果分析程式 35
3.1.2.5 立體浮雕效果分析程式 35
3.1.2.6 色彩浮雕效果分析程式 36
3.2 系統整合 37
3.2.1 硬體設備整合 37
3.2.2 軟體程式整合 38
第四章 研究成果 40
4.1 實驗方法與流程 40
4.2 實驗結果與分析 40
4.2.1 立體攝影機參數校正 41
4.2.1.1 攝影機光軸校正 41
4.2.2 立體影像立體效果分析 42
4.2.2.1 左右影像特徵顏色高對比偵測 42
4.2.2.2 左右影像對位校正輔助測 43
4.2.2.3 左右影像疊合資訊 44
4.2.2.4 鬼影分析 45
4.2.2.5 邊框效應分析 46
4.2.3 立體亮度減損分析 47
4.2.4 立體攝影機支架自動控制設計 55
4.2.4.1 支架可程式化控制 56
4.2.4.2 馬達控制 58
4.2.4.3 立體參數可程式化控制 60
第五章 結論與建議 63
5.1 結論 63
5.2 未來展望 63
參考文獻 65
附件1 69



圖目錄
圖1 傳統立體攝影系統架構 1
圖2 立體攝影機自動控制系統概念 2
圖3 全世界立體頻道分佈圖 6
圖4 立體攝影整合系統(Sony公司) 7
圖5 立體影音監製介面(Sony公司) 7
圖6 立體訊號擷取系統(3ality公司) 8
圖7 立體參數控制器(3ality公司) 8
圖8 研究流程 10
圖9 立體攝像系統基本架構 12
圖10 一般2D攝影的工作原理 13
圖11 立體攝影的工作原理 14
圖12 立體攝影機系統示意 15
圖13 時間碼同步設備 20
圖14 最佳立體視覺效果調整示意 21
圖15 約2%的視差虛線區間 21
圖16 風景模式的工作原理 22
圖17 動態辨識模式的工作原理 23
圖18 動態辨識模式調整過程與結果 23
圖19 多重動態模式的工作原理 24
圖20 立體串流差異分析 24
圖21 立體人因要素分析 25
圖22 可程式控制立體攝影機校正參數 25
圖23 可程式控制立體攝影機支架系統 26
圖24 立體攝影即時預覽與分析系統架構 27
圖26 RED EPIC攝影機 28
圖27 立體攝影鏡頭組 29
圖28 RED EPIC攝影機預留的同步輸入插座 29
圖29 2D即時顯示器 30
圖30 立體重播與分析監視器 30
圖31 立體影像多工器 31
圖32 影像分流器 31
圖33 立體攝影機支架 33
圖34 自行研發之可程式控制器 34
圖35 視差分析程式 35
圖36 對比分析程式 35
圖37 垂直視差分析程式 36
圖38 專注效果分析程式 36
圖39 立體浮雕效果分析程式 37
圖40 色彩浮雕效果分析程式 37
圖41 硬體設備整合實體架構 38
圖43 實驗方法與流程 41
圖44 光軸校正硬體架構 42
圖45 左右畫面特徵顏色高對比偵測,以藍色框標記高對比結果。 43
圖46 左右畫面對位校正輔助,右下角窗格顯示調整指示訊息。 44
圖47 大字體校正指示畫面 44
圖49 鬼影的形成與分析 45
圖52 拍攝環境空間 48
圖53 亮度測量暗房擺放示意圖 49
圖54 標準化殘差直方圖 51
圖55 迴歸標準化殘差的常態P-P圖 51
圖56 立體攝影機自動校正架構圖 55
圖57 反射攝影機旋鈕 56
圖59 控制手把旋鈕 57
圖61 立體攝影支架可程式化扭力控制原型示意圖 58
圖62 閉迴路控制法則 59
圖63 透過調整雙攝影機間之間距d及夾角θ來控制畫面立體感及零平面位置 59
圖64 以雙攝影機間之間距d及夾角θ調整方法 60
圖65 (a)於馬達控制下a與b移動距離相同,可控制x軸自由度;(b)於馬達控制下a與b移動距離不同,無法順利控制x軸自由度 61
圖66 控制參數腳位 62
圖67 馬達驅動模組介面 62
圖68 立體攝影支架可程式化控制原型 63


表目錄
表1 美國專利報告與本研究研究方向之差異性 4
表2 三種機型個人電腦及其附屬設備特性評估比較 31
表3 硬體設備的廠牌型號與功能說明 37
表4 軟體程式開發廠商與功能說明 39
表5 環境與硬體參數設定 48
表6 依變數與自變數變項設計 49
表7 迴歸模型摘要 50
表8 變異數分析 50
表9 迴歸模型的統計係數 52
表10 光圈F5.6實驗結果 54
表11 光圈F10的實驗結果 54
表12 減損幅度的合理範圍 55


[1]Tsai, R.Y., “An efficient and accurate camera calibration technique for 3D machine vision,” IEEE Conference on Computer Vision and Pattern Recognition, Miami Beach, Florida, USA, pp. 364-374, 1986.
[2]Zhang, Z., “Flexible camera calibration by viewing a plane from unknown orientations,” IEEE International Conference on Computer Vision, Vol. 1, pp. 666-673, 1999.
[3]Zhang, Z., “A flexible new technique for camera calibration,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, pp. 1330-1334, 2000.
[4]Miyagawa, I., Arai, H., and Koike, H., “Simple camera calibration from a single image using five points on two orthogonal 1-D objects,” IEEE Transactions on Image Processing, Vol. 19, No. 6, pp. 1528-1538, 2010.
[5]Hamzah, R.A. and Salim, S.I.M., “Software calibration for stereo camera on stereo vision mobile robot using Tsai’s Method,” International Journal of Computer Theory and Engineering, Vol. 2, No. 3, pp. 390-394, 2010.
[6]Stelmach, L., Tam, W.J., Meegan, D., and Vincent, A., “Stereo image quality: effects of mixed spatio-temporal resolution,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 10, No. 2, pp. 188-193, 2000.
[7]謝銘倫,「室內場景之特徵點擷取與追蹤」,交通大學資訊科學研究所碩士班,碩士論文,2003。
[8]Georgescu, B. and Meer, P., “Point matching under large image deformations and illumination changes,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 26, No. 6, pp. 188-193, 2004.
[9]陳彥良,「即時立體視覺物體追蹤系統」,中原大學機械工程學系碩士班,碩士論文,2003。
[10]Knight, J., “Active visual alignment of a mobile stereo camera platform,” IEEE International Conference, San Francisco, CA, Vol. 4, pp. 3203-3208, 2000.
[11]Lim, D.H., “Self-aligning calibration of a stereo vision system,” International Conference on Control and Automation-Systems Society of Instrument and Control Engineers Conference (ICCAS-SICE), Fukuoka, pp. 5413-5416, 2009.
[12]Zhe, G.Y.N., Zhang, Y.X., Lin, Z.G., Fan, Y.Y., and Fang, D.D., “Multi-pose 3D face recognition based on 2D sparse representation,” J. Vis. Commune. Image Represent, Vol. 24, pp. 117-126, 2013.
[13]Zhang, Y., Guo, Z., Xia, Y., Lin, Z., and Feng, D.D., “2D representation of facial surfaces, for multi-pose 3D face recognition,” Pattern Recognit. Lett., Vol. 33, pp. 530-536, 2012.
[14]Berretti, S., Bimbo, A.D., and Pala, P., “3D face recognition using iso-geodesic stripes,” IEEE Trans. Pattern Anal. Mach. Intell., Vol. 32, pp. 2162-2177, 2010.
[15]Queirolo, C.C., Silva, L., Segundo, O.R.B., and Segundo, M.P., “3D face recognition using simulated annealing and the surface interpenetration measure,” IEEE Trans. Pattern Anal. Mach. Intell., Vol. 32, pp. 206-219, 2010.
[16]Teng, C.H., Chen, Y.S., and Hsu, W.H., “Constructing a 3D trunk model from two images,” Graph. Model, Vol. 69, pp. 33-56, 2007.
[17]Lenz, R.K. and Tsai, R.Y., “Techniques for calibration of the scale factor and image center for high accuracy 3-D machine vision,” IEEE Trans. Pattern Anal. Mach. Intell., Vol. 10, pp. 713-720, 1988.
[18]Lau, M.H. and Armstrong, T.J., “The effect of viewing angle on wrist posture estimation from photographic images using novice raters,” Applied Ergonomics, Vol. 42, pp.634-643, 2011.
[19]Lowe, B.D., “Accuracy and validity of observational estimates of wrist and forearm posture,” Ergonomics, Vol. 47, pp. 527-554, 2004.
[20]Nawrot, M. and Joyce, L., “The pursuit theory of motion parallax,” Vision Res., Vol. 46, pp. 4709-4725, 2006.
[21]David, G., Woods, V., Li, G.Y., and Buckle, P., “The development of the quick exposure check (QEC) for assessing exposure to risk factors for work-related musculoskeletal disorders,” Appl. Ergon., Vol. 39, pp. 57-69, 2008.
[22]Banno, A. and Ikeuchi, K., “Omnidirectional texturing based on robust 3D registration through Euclidean reconstruction from two spherical images,” Comput. Vis. Image Underst., Vol. 114, pp. 491-499, 2010.
[23]Zhang, Y.N., Guo, Z., Xia, Y., Lin, Z.G., and Feng, D.D., “2D representation of facial surfaces, for multi-pose 3D face recognition,” Pattern Recognit. Lett., Vol. 33, pp. 530-536, 2012.
[24]Berretti, S., Bimbo, A.D., and Pala, P., “3D face recognition using iso-geodesic stripes,” IEEE Trans. Pattern Anal. Mach. Intell., Vol. 32, pp. 2162-2177, 2010.
[25]Queirolo, C.C., Silva, L., Segundo, O.R.B., and Segundo, M.P., “3D face recognition using simulated annealing and the surface interpenetration measure,” IEEE Trans. Pattern Anal. Mach. Intell., Vol. 32, pp. 206–219, 2010.
[26]Teng, C.H., Chen, Y.S., and Hsu, W.H., “Constructing a 3D trunk model from two images,” Graph., Vol. 69, pp. 33-56, 2007.
[27]Lenz, R.K. and Tsai, R.Y., “Techniques for calibration of the scale factor and image center for high accuracy 3-D machine vision,” IEEE Trans. Pattern Anal. Mach. Intell., Vol. 10, pp. 713–720, 1988.
[28]Nawrot, M. and Joyce, L., “The pursuit theory of motion parallax,” Vision Res., Vol. 46, pp. 4709-4725, 2006.
[29]Zhang, J., Li, S., Shen, L., and Hou, C., “A comparison of testing metrics between 3D LCD TV and 3D PDP TV,” Commun. Comput. Inf. Sci., Vol. 331, pp. 125-132, 2012.
[30]Zhao, X., Song, H., Zhang, S., Huang, Y., Sun, Q., Fan, K., Hu, J., and Fan, G., “3D definition certification technical specifications for digital TV displays,” Center for Education Simulation Innovation (CESI001), China, pp. 5-8, 2011.
[31]Mei, X., Sun, X., Zhou, M., Jiao, S., Wang, H., and Zhang, X., “On building an accurate stereo matching system on graphics hardware,” IEEE International Conference on Computer Vision Workshops (ICCV Workshops), Barcelona, pp. 467-474, 2011.
[32]Rhemann, C., Hosni, A., Bleyer, M., Rother, C., and Gelautz, M., “Fast cost-volume filtering for visual correspondence and beyond,” in Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, pp. 3017-3024, 2011.
[33]Yang, Q., Engels, C., and Akbarzadeh, A., “Near real-time stereo for weakly-textured scenes,” in Proceedings of the British Machine Vision Conference (BMVC), Leeds, pp. 72 1-10, 2008.
[34]Grady, L. “Random walks for image segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, No. 11, pp. 1768-1783, 2006.
[35]Grady, L., “Multilabel random walker image segmentation using Prior models, ” IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), Princeton, Vol. 1, pp. 763-770, 2005.
[36]Shen, R., Cheng, I., Li, X., and Basu, A., “Stereo matching using random walks,” in Proceedings of the 19th International Conference on Pattern Recognition 2008 (ICPR 2008), Tampa, FL, pp. 1-4, 2008.
[37]Fang, C.Y., Chen, S.W., and Fuh, C.S., “Automatic change detection of driving environments in a vision-based driver assistance system,” IEEE Transactions on Neural Networks, Vol. 14, No. 3, pp. 646-657, 2003.
[38]Ma, Y.F. and Zhang, H.J., “Contrast-based image attention analysis by using fuzzy growing,” in Proceedings of the IEEE International Conference on Multimedia, New York, USA, pp. 374-381, 2003.
[39]Liu, F. and Gleicher, M., “Region enhanced scale-invariant saliency detection,” in Proceedings of the 2006 IEEE International Conference on Multimedia and Expo, Toronto, Ont, pp. 1477-1480, 2006.
[40]Lang, M., Hornung, A., Wang, O., Poulakos, S., Smolic, A., and Gross, M., “Nonlinear disparity mapping for stereoscopic 3D,” ACM Transactions on Graphics, Vol. 29, pp. 1-75, 2010.
[41]Chang, C.H., Liang, C.K., and Chuang, Y.Y., “Content-aware display adaptation and interactive editing for stereoscopic images,” IEEE Transactions on Multimedia, Vol. 13, No. 4, pp. 589-601, 2011.
[42]Stan, B. and Carlo, T., “Depth discontinuities by pixel-to-pixel stereo,” in Proceedings of the 1998 Sixth International Conference on Computer Vision, Bombay, India, pp. 1073-1080, 1998.
[43]Zhai, Y. and Shah, M., “Visual attention detection in video sequences using spatiotemporal cues,” in Proceedings of the ACM Multimedia, New York, USA, pp. 815-824, 2006.
[44]Ma, Y.F., Lu, L., Zhang, H.J., and Li, M.J., “A user attention model for video summarization,” in Proceedings of the 10th ACM International Conference on Multimedia, New York, USA, pp. 1-6, 2002.
[45]C.W Lin, W.H. Huang, W. J. Huang, A. C. Luo, and W. C. Chen, “Blur-based extending visual comfort without reducing disparity range,” in Proceedings of the 3DSA2012, Lakeshore Hotel, Hsinchu, pp. 272-274, 2012.
[46]W.J. Huang, A.C. Luo, W.C. Chen, and W.H. Huang, “Perceptual based stereoscopic content analysis using salient information, dense disparity maps, and modified random walk framework,” in Proceedings of the International Workshop on 3-D Cinematography, Conference on Computer Vision and Pattern Recognition (CVPR), Lakeshore Hotel, Hsinchu, pp. 8-15, 2012.
[47]S. Esquivel, F. Woelk and R. Koch, “Calibration of a multi-camera rig from non-overlapping views,” Pattern Recognition, Lecture Notes in Computer Science, Vol. 4713, pp. 82-91, 2007.
[48]Hamzah, R.A. and Salim, S.I.M., “Software calibration for stereo camera on stereo vision mobile robot using Tsai’s method,” International Journal of Computer Theory and Engineering , Vol. 2, No. 3, pp 390-394, 2010.
[49]Resko, B. and Baranyi, P., “Stereo camera alignment based on disparity selective cells in the visual cortex,” IEEE 3rd International Common Criteria Conference (ICCC), Hungary, pp. 285-290, 2005.
[50]Lim, D.H. and Kuc, T.Y., “Self-aligning-calibration of a stereo vision system,” in Proceedings of the Institute of Control, Robotics and Systems-Society of Instrument and Control Engineers (ICROS-SICE), Fukuoka, pp. 5413-5416, 2009.

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