臺灣博碩士論文加值系統

本研究為探討Image-based lighting應用於密集都市與複雜地形環境所遭遇到的問題，並利用遙控感測的方式解決攝影裝置因空間移動的限制而衍生出不易到達檢測點的狀況。Image-based lighting是以影像紀錄光源作為照明模擬的技術，其特色為透過高動態範圍攝影可準確紀錄具有獨特性且輝度範圍完整的極端光環境之外，甚至能將完整場景內容以影像紀錄的方式製作Light Probe Image，在照明領域可作為室內建築採光之數位模擬的環境照明來源。其捕捉光源的過程需對同一處場景拍攝多張不同曝光範圍的影像，操作期間多以腳架裝設相機保持在相同位置可減少影像合成所產生殘影現象。但因應密集都市趨勢與複雜地形環境光源捕捉的需求，其攝影裝置需更有機動性與空間移動的能力，故在本研究提出遙控感測的方案以解決上述發現的問題。採取使用自製飛行載具攜帶攝影器材的方式達到懸停之功能，其方法可將進而探討利用無人機以水平向度之魚眼鏡頭視野，紀錄都市複雜建築環境的日光輝度分佈。本研究最終目的為延伸現有的Image-based lighting技術發展，利用四軸無人載具將讓小尺度空間可精準地模擬出真實的照明環境。
本研究分三面向進行研究：研發輕量級高動態範圍Light Probe Image遙控光測系統；以數位製造技術及開源系統整合客製無人機飛行載具；利用已驗證的光源捕捉系統與本研究所開發的遙控光測系統互相比較，同以相同照明模擬軟體渲染後進行影像輝度準確評估。原型機以兩部分進行開發：iPhone外掛魚眼鏡頭之高動態範圍影像應用程式設計；配掛於四軸飛行器之橫向攝影穩定雲台與配重模組。
實測結果為本研究所開發的系統在都市中的光環境所測得輝度，包含天空照明與兩樓之間光線漫反射，於照度30000 lux以下誤差小於5%；8000 lux以下，可將誤差範圍縮小2%。本研究提出一可行之系統可應用於天空狀況為非劇烈正午日光直射的環境下，可採集到與已驗證過的數位相機系統所捕捉較相同光源數據，透過此系統可為研究者提供具有機動性的捕捉光源方案，以克服相關領域應用拍攝之移動限制的不足。

Image-based lighting is a digital technique that captures an omnidirectional representation of real-world light information as an image. When it is a High Dynamic Range image, it can provide real-world illumination in a virtual scene and generate light probe images. However, this method is limited to the setting of a flat landscape with an unobstructed view. Therefore, this paper presents an innovative image-capturing system, which was simulated in a dense urban environment and implemented using a lightweight smart phone camera equipped with a fish-eye lens on a customized unmanned aerial vehicle. These captured images were then assembled into a high dynamic range light probe image and used as the image-based lighting source for daylighting simulations. Thus, the aim of this study is to prove that these generated light probe images can provide reasonable accuracy in daylight simulations, while the use of the modified unmanned aerial vehicle can overcome previous limitations whereby stationary equipment were needed to capture said images.

摘要 i
ABSTRACT iii
章節目錄 v
表目錄 ix
圖目錄 x
第一章、緒論 1
1.1 研究背景與動機 1
1.2 研究目標與規劃 3
1.3 研究流程與架構 4
第二章、文獻探討 5
2.1 光源模擬系統 5
2.1.1 實體環境照明模擬 6
2.1.2 數位環境照明模擬 8
2.2 天空照明之測量方法 10
2.2.1 人工照明與自然照明 10
2.2.2 測量天空光源與分析模型 11
2.2.3 以影像光源紀錄光環境 13
2.2.4 高動態範圍影像技術 15
2.2.5 微地形對照明環境的影響 17
2.3 遙控感測 19
2.3.1 使用無人機進行環境防災與監測 20
2.3.2 航照影像用於地形與精度分析 21
2.3.3 無人機之小尺度空間運用 22
2.3.4 多軸機探討與選用評估 23
2.5 文獻探討小結 24
第三章、系統前置流程實作與評估 25
3.1 四軸飛行器 25
3.1.1 飛行運動原理探討 26
3.1.2 硬體元件與通訊設備 27
3.1.3 韌體與操作軟體 30
3.2 室內光環境建置模擬流程 33
3.2.1 實景光環境捕捉 33
3.2.2 高動態範圍影像 35
3.2.3 Light Probe Image 36
3.3 RADIANCE操作模擬 37
3.3.1 建構虛擬場景實驗空間 38
3.3.2 影像光源環境設定與模擬呈現 39
3.3.3 影像光源之平均輝度比較 41
3.4 魚眼鏡頭安置於機身下方之評估 41
3.4.1 前測步驟與器材規劃 44
3.4.2 前測實驗 45
3.4.3 前測模擬分析 46
3.4.4 前測分析與改善方式 48
第四章、遙控光感系統之原型開發 49
4.1 機載高動態影像攝影之系統開發 49
4.1.1 機載攝影裝置評估 50
4.1.2 遠端遙控攝影應用程式 51
4.1.3 高動態範圍之遙控攝影系統開發 55
4.1.4 手機的魚眼鏡頭之選用限制 56
4.2 攝影雲台配掛設計 58
4.2.1 攝影雲台設計 60
4.2.2 卡榫設計 62
4.2.3 配重設計 63
第五章、飛行實測 65
5.1 實驗規劃 65
5.2 比較iPhone與Canon相機系統之影像光源測試 67
5.2.1 單項比較測試之地點與操作規劃 67
5.2.2 影像光源模擬與分析 67
5.3 載具穩定度測試與飛行拍攝影像評估 68
5.3.1 飛行器負載滯空測試 68
5.3.2 飛測影像拍攝與殘影校正 70
5.4 Canon相機與機載iPhone滯空拍攝實測 71
5.4.1 實測步驟 71
5.4.2 機載實測之結果分析 72
5.5 影像光源之儀器校正實測 74
5.5.1 照度計簡介 74
5.5.2 輝度計簡介 75
5.5.3 以灰卡校正之數值分析 75
5.5.4 校正後飛行實拍或校正數據重新渲染比較 77
5.6 實測結果小結 78
第六章、結論與建議 80
6.1 研究結論 80
6.1.1 機載拍攝系統 80
6.1.2 攝影雲台之數位自造應用 81
6.1.3 行動互聯應用 82
6.2 後續研究建議與發展 83
6.2.1 飛行器部分改良建議 83
6.2.2 以增設影像定位系統輔助GPS定位系統 84
6.2.3 遙控光測未來發展 85
參考文獻 86
外文文獻 86
中文文獻 92

外文文獻
Apple Inc. (2016, September 15). AVCamManual: Extending AVCam to Use Manual
Capture API [samplecode].
Avery, T. E., & Berlin, G. L. (1992). Fundamentals of remote sensing and air photo
interpretation.
Baertschi, S. W., Clapham, D., Foti, C., Jansen, P. J., Kristensen, S., Reed, R. A., …
Tønnesen, H. H. (2013). Implications of In-Use Photostability: Proposed
Guidance for Photostability Testing and Labeling to Support the Administration of Photosensitive Pharmaceutical Products, Part 1: Drug Products Administered by Injection. Journal of Pharmaceutical Sciences, 102(11), 3888–3899.
Bloch, C. (2013). The HDRI Handbook 2.0: High Dynamic Range Imaging for
Photographers and CG Artists. Rocky Nook, Inc.
Bradski, G., & Kaehler, A. (2008). Learning OpenCV: Computer vision with the
OpenCV library. O’Reilly Media, Inc.
Campbell, J. B., & Wynne, R. H. (2011). Introduction to remote sensing. Guilford
Press.
CIE. (1955). Natural daylight, Official recommendation. Compte Rendu, CIE 13th
Session, Committee E-3.2, vol. II, parts 3–2, II–IV&35–37.
CIE. (1973). Standardization of luminance distribution on clear skies. CIE
Publication, (22), TC-4.2.
CIE, S. (2003). Spatial distribution of daylight – CIE Standard General Sky. CIE
Standard General Sky, S001/E:2003.
Darula, S., & Kittler, R. (2002). CIE general sky standard defining luminance
distributions. Proceedings eSim, 11–13.
Debevec, P. (2002). Image-based lighting. IEEE Computer Graphics and
Applications, 22(2), 26–34.
Debevec, P. E., & Malik, J. (1997). Recovering high dynamic range images. In
proceeding of the SPIE: Image Sensors (Vol. 3965, pp. 392–401).
Debevec, Paul. (1998). Rendering Synthetic Objects into Real Scenes: Bridging
Traditional and Image-based Graphics with Global Illumination and High Dynamic Range Photography. In Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques (pp. 189–198). New York, NY, USA: ACM.
Debevec, Paul E., & Malik, J. (2008). Recovering High Dynamic Range Radiance
Maps from Photographs. In ACM SIGGRAPH 2008 Classes (p. 31:1–31:10).
New York, NY, USA: ACM.
Hertel, D., Betts, A., Hicks, R., & Brinke, M. ten. (2008). An adaptive multiple-reset
CMOS wide dynamic range imager for automotive vision applications. In 2008 IEEE Intelligent Vehicles Symposium (pp. 614–619).
IESNA Computer Committee, & others. (1986). ÍESNA recommended standard file
format for electronic transfer of photometric data. IESNA. LM-63-1986.
Inanici, M. (2009). Applications of image based rendering in lighting simulation:
Development and evaluation of image based sky models. In Building Simulation
(Vol. 7, pp. 27–30).
Inanici, M. (2010). Evalution of high dynamic range image-based sky models in
lighting simulation. Leukos, 7(2), 69–84.
Jones, R., Haufe, P., Sells, E., Iravani, P., Olliver, V., Palmer, C., & Bowyer, A.
(2011). RepRap – the replicating rapid prototyper. Robotica, 29(1), 177–191.
Kajiya, J. T. (1986). The Rendering Equation. In Proceedings of the 13th Annual
Conference on Computer Graphics and Interactive Techniques (pp. 143–150). New York, NY, USA: ACM.
Kanasaki, K., & Tanaka, H. (2013). Traditional Wood Joint System in Digital
Fabrication. In eCAADe 2013: Computation and Performance–Proceedings of
the 31st International Conference on Education and research in Computer Aided Architectural Design in Europe, Delft, The Netherlands, September 18-20, 2013.
Kittler, R. (1967). Standardisation of outdoor conditions for the calculation of
daylight factor with clear skies. In Proc. CIE Intercessional Conference on Sunlight and Buildings (pp. 273–286).
Kittler, R., Darula, S., & Perez, R. (1998). A set of standard skies characterising
daylight conditions for computer and energy conscious design. Res Report of the American-Slovak Grant Project US-SK, 92, 240.
Kittler, Richard, Kocifaj, M., & Darula, S. (2011). Daylight Science and Daylighting
Technology. Springer Science & Business Media.
Mardaljevic, J. (1995). Validation of a lighting simulation program under real sky
conditions. International Journal of Lighting Research and Technology, 27(4),
181–188.

Mistrick, R. G. (2000). Desktop radiance overview. The Pennsylvania State
University, USA, Pacific Gas and Electric.
Moon, P., & Spencer, D. E. (1942). Illumination from a non-uniform sky. Illuminating
Engineering, 37(10), 707–726.
Nagakura, T., Tsai, D., & Pinochet, D. (2015). Capturing History Bit by Bit –
Architectural Database of Photogrammetric Model and Panoramic Video. In Martens, B, Wurzer, G, Grasl T, Lorenz, WE and Schaffranek, R (eds.), Real Time - Proceedings of the 33rd eCAADe Conference - Volume 1, Vienna University of Technology, Vienna, Austria, 16-18 September 2015, pp. 685-694.
Ochoa Morales, C. E., Aries, M. B. C., & Hensen, J. L. M. (2010). Current
perspectives on lighting simulation for building science. Proceedings IBPSA-NVL, 9.
Panitz, K., & Garcia-Hansen, V. R. (2013). Daylighting design and simulation : ease
of use analysis of digital tools for architects. In K. Manley, S. L. Kajewski, & K. D. Hampson (Eds.), Proceedings of the 19th CIB World Building Congress, Brisbane 2013 : Construction and Society (pp. 1–13).
Perez, R., Seals, R., & Michalsky, J. (1993). All-weather model for sky luminance
distribution—preliminary configuration and validation. Solar Energy, 50(3), 235–245.
Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G., & Myszkowski, K.
(2010). High dynamic range imaging: acquisition, display, and image-based lighting. Morgan Kaufmann.
Reinhart, C. F., & Herkel, S. (2000). The simulation of annual daylight illuminance
distributions—a state-of-the-art comparison of six RADIANCE-based methods. Energy and Buildings, 32(2), 167–187.
Reinhart, C., & Fitz, A. (2006). Findings from a survey on the current use of daylight
simulations in building design. Energy and Buildings, 38(7), 824–835.
Schanz, M., Nitta, C., Bussmann, A., Hosticka, B. J., & Wertheimer, R. K. (2000). A
high-dynamic-range CMOS image sensor for automotive applications. IEEE Journal of Solid-State Circuits, 35(7), 932–938.
Stumpfel, J., Tchou, C., Jones, A., Hawkins, T., Wenger, A., & Debevec, P. (2004).
Direct HDR Capture of the Sun and Sky. In Proceedings of the 3rd International Conference on Computer Graphics, Virtual Reality, Visualisation and Interaction in Africa (pp. 145–149). New York, NY, USA: ACM.
Tchou, C., & Debevec, P. (2001). HDR shop. In SIGGRAPH 2001 Conference
Abstracts and Applications.
Torres, S. (2003). Experiences with luminance mapping for daylighting simulations.
In 2nd International Scientific Radiance Workshop, Berkeley, USA.
Tymrak, B. M., Kreiger, M., & Pearce, J. M. (2014). Mechanical properties of
components fabricated with open-source 3-D printers under realistic environmental conditions. Materials & Design, 58, 242–246.
Ubbelohde, M. S., & Humann, C. (1998). Comparative evaluation of four daylighting
software programs. Proceedings of ACEE Summer Study on Energy Efficiency in Buildings, Pacific Grove, CA, 23–28.
van Bommel, W., & van den Beld, G. (2004). Lighting for work: a review of visual
and biological effects. Lighting Research & Technology, 36(4), 255–266.
Ward, G. (2005). Photosphere. Computer software,[Online], Available:< Http://Www.
Anyhere. Com/>.[26 February 2016].
Ward, G. J. (1994). The RADIANCE Lighting Simulation and Rendering System. In
Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques (pp. 459–472). New York, NY, USA: ACM.
Ward, G. J., Rubinstein, F. M., & Clear, R. D. (1988). A Ray Tracing Solution for
Diffuse Interreflection. In Proceedings of the 15th Annual Conference on Computer Graphics and Interactive Techniques (pp. 85–92). New York, NY, USA: ACM.
Ward, Greg, & Shakespeare, R. (1998). Rendering with Radiance: the art and science
of lighting visualization.
中文文獻
內政部國土測繪中心(2012, April)。航拍作業流程。取自
https://www.nlsc.gov.tw/UAS/3-1_flow.html。
周鼎金(2003)。人工光及自然光實驗室建置之研究。內政部建築研究所。
張庭榮、何淑枝、李良輝(2014)。無人飛行載具於自然災害之防救災應用。水
保技術，9(2)，16–22。
林彥輝、莊舜弘、李建璁(2005)。室外工作場所採光照明與作業安全之研究。
勞工安全衛生研究所。
楊明德、陳韋廷、黃凱翔(2015)。應用 UAV 影像建置現地堰塞壩三維模型。
中華水土保持學報，46(2)，88–95。
白絜成、劉益誠、蕭宇伸、連惠邦、林秉賢(2015)。無人飛行載具掛載消費型
攝影機應用於防災可行性研究。中華水土保持學報，46(3)，142–149。
蕭震洋、安軒霈、陳俊愷、饒見有、陳樹群(2015)。應用UAV量化台東金崙溪
河川型態演變及致災特性。中國土木水利工程學刊，27(3)，213–222。
藍艁昕、賴維祥(2015)。防災用長滯空無人飛機之設計與應用。中國土木水利
工程學刊，27(3)，191–199。
賈澤民(2016)。無人飛航載具監測環境污染之功能。航測及遙測學刊，21(3)，
163–182。