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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 歐陽明(Ming Ouhyoung) | |
| dc.contributor.author | Wai-Seng Ng | en |
| dc.contributor.author | 吳偉成 | zh_TW |
| dc.date.accessioned | 2021-06-15T01:19:50Z | - |
| dc.date.available | 2009-07-31 | |
| dc.date.copyright | 2009-07-31 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-07-27 | |
| dc.identifier.citation | [AS07] AVIDAN S., SHAMIR A.: Seam carving for content-aware image resizing.
10. (SIGGRAPH 2007 Conference Proceedings). [BC99] BURIAN P., CAPUTO R.: National Geographic Photography Field Guide, 2nd ed. National Geographic, 1999, pp. 24–33. [BE07] BANERJEE S., EVANS B.: In-camera automation of photographic composition rules. IEEE Transactions on Image Processing 16, 7 (2007), 1807– 1820. [Can86] CANNY J.: A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8, 6 (1986), 679–698. [CL01] CHANG C.-C., LIN C.-J.: LIBSVM: a library for support vector machines. Software available at http://www.csie.ntu.edu.tw/ cjlin/libsvm. [CO08] COHEN-OR D.: Private communication on photo composition. [COSG 06] COHEN-OR D., SORKINE O., GAL R., LEYVAND T., XU Y.-Q.: Color harmonization. 624–630. (SIGGRAPH 2006 Conference Proceedings). [CXF 03] CHEN L.-Q., XIE X., FAN X., MA W.-Y., ZHANG H., ZHOU H.-Q.: A visual attention model for adapting images on small displays. Multimedia Systems 9, 4 (2003), 353–364. [DH72] DUDA R. O., HART P. E.: Use of the hough transformation to detect lines and curves in pictures. Communications of the ACM 15, 1 (1972), 11–15. [DJLW06] DATTA R., JOSHI D., LI J., WANG J. Z.: Studying aesthetics in photographic images using a computational approach. In ECCV (3) (2006), pp. 288–301. [Goo] GOOGLE PICASA: Three crop suggestions provided by picasa. http://picasa.google.com. [GW87] GONZALEZ R. C., WOODS R. E.: Digital image processing. Addison- Wesley Reading, Mass, 1987. 43 [Hu07] HU C.-J.: A Real-Time Skin-Color-Enhanced Face Detection Algorithm. Master’s thesis, National Taiwan University, 2007. [IKN98] ITTI L., KOCH C., NIEBUR E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20, 11 (1998), 1254–1259. [JS06] JI G., SHEN H.-W.: Dynamic view selection for time-varying volumes. 1109–1116. (Visualization 2006 Conference Proceedings). [KMO08] KAO H.-C., MA W.-C., OUHYOUNG M.: Esthetics-based quantitative analysis of photo composition. In Pacific Graphics 2008 Conference Posters (Tokyo, Japan, 2008). [KTJ06] KE Y., TANG X., JING F.: The design of high-level features for photo quality assessment. In Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Washington, DC, USA, 2006), IEEE Computer Society, pp. 419–426. [LC09] LEE W.-T., CHEN H.-T.: Histogram-based interest point detectors. In Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Miami, USA, 2009), IEEE Computer Society. [LCODL08] LEYVAND T., COHEN-OR D., DROR G., LISCHINSKI D.: Data-driven enhancement of facial attractiveness. 1–9. (SIGGRAPH 2008 Conference Proceedings). [LT08] LUO Y., TANG X.: Photo and video quality evaluation: Focusing on the subject. In ECCV ’08: Proceedings of the 10th European Conference on Computer Vision (Berlin, Heidelberg, 2008), Springer-Verlag, pp. 386–399. [Pet03] PETERSON B.: Learning to See Creatively, revised ed. Amphoto Books, 2003, ch. 3, pp. 88–129. [SAD 06] SANTELLA A., AGRAWALA M., DECARLO D., SALESIN D., COHEN M.: Gaze-based interaction for semi-automatic photo cropping. In ACM CHI 2006 Conference Proceedings (2006), pp. 771–780. [SEL00] SAVAKIS A. E., ETZ S. P., LOUI A. C.: Evaluation of image appeal in consumer photography. In Proceedings of SPIE, Human Vision and Electronic Imaging V (2000), vol. 3959, pp. 111–120. 44 [SLBJ03] SUH B., LING H., BEDERSON B. B., JACOBS D. W.: Automatic thumbnail cropping and its effectiveness. In Proceedings of the 2003 ACM Symposium on User Interface Software and Technology (2003), pp. 95–104. [TLZ 04] TONG H., LI M., ZHANG H.-J., HE J., ZHANG C.: Classification of digital photos taken by photographers or home users. In Proceedings of the 2004 Pacific-Rim Conference on Multimedia (2004), pp. 198–205. [TLZZ04] TONG H., LI M., ZHANG H.-J., ZHANG C.: Blur detection for digital images using wavelet transform. In Proceedings of the 2004 IEEE International Conference on Multimedia and Expo (2004), pp. 17–20. [Tsa98a] TSAI M.-F.: Better Photography. Recreation Press, 1998, pp. 9–15, 17–21, 23–24, 32. [Tsa98b] TSAI M.-F.: How to Compose a Picture. Recreation Press, 1998, pp. 24– 32, 76–88, 108–117, 131. [WTSL08] WANG Y.-S., TAI C.-L., SORKINE O., LEE T.-Y.: Optimized scale-andstretch for image resizing. 1–8. (SIGGRAPH Asia 2008 Conference Proceedings). [Yam06] YAMAGUCHI T.: Photo Composition Determines All! Methods to Take Great Photos. Gakken Co., 2006, pp. 5–18. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/42689 | - |
| dc.description.abstract | 由於數位攝影的普及，現在拍照和保存照片可以成為一件容易的事
情。然而，並非很多人都熟悉照片的美學規則，如構圖和顏色分配。 作為一個工具，我們會介紹在傳統攝影學上，如何對構圖做一些量化 分析，一些情況例如水平線，照片平衡，主體位置，線條及形狀和人 臉與背景線穿透造成融合。每個規則的加權指數是實驗後才確定的， 包含來自Flickr網站500張照片和幾十個主題。支援向量迴歸演算法被首次使用來量化和“預測”人的喜好程度，然後，1萬多張來自Flickr的照片可再用於最後使用者分析。使用者分析與實驗證實了我們最初的假設，即自動照片排名是有效的。此外，我們總共用了2000張照片(dpchallenge網站)分別用於學習（ 1000 ）和測試（ 1000 ），並將這兩個類別分別出好的或不好的照片。可在上述實驗能夠獲得80.9%的準確度，比之前別人的結果好(3000張/72%, 2400張/74%, 1800張/76%)。 | zh_TW |
| dc.description.abstract | Due to the popularity of digital photography, taking, viewing, and preserving photos are much easier. Nevertheless, not many people are familiar with photo esthetics rules, such as composition and color distribution. As an tool, we introduce a quantitative analysis method of photo composition based on well-known photography rules, such as horizon balance, intensity balance, locations of region-of-interests (ROIs), line patterns and merger avoidance. The weighting factors for each of the rules are determined by an experiment involving 500 photos from Flickr sites and dozens of subjects. Support Vector Regression techniques are first used to quantify and ”predict” human evaluation, then results from more than 10,000 photos from Flickr are used for the
final user study. The user study experiment corroborates with our initial hypothesis that automatic photo ranking is effective. Furthermore, 2000 photos from dpchallenge website are used for training (1000) and test (1000), with two class classification to find the better and worse ones, and we are able to get 80.9% accuracy as compared to human rating. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T01:19:50Z (GMT). No. of bitstreams: 1 ntu-98-R96922038-1.pdf: 29893976 bytes, checksum: 4b373fccbee302bd2735be8d0ea4a5b1 (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | 致謝i
摘要iii Abstract iv 1 Introduction 1 2 Related Work 5 2.1 Automatic image cropping . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Two-class classification . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Feature detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.4 Learning of dataset approach . . . . . . . . . . . . . . . . . . . . . . . . 7 2.5 Restrictions of evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.6 Information theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3 System Overview 11 3.1 Canny Edge Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.2 Face Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.3 ROI Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.4 Feature Descritpor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.5 Training and Testing Phase . . . . . . . . . . . . . . . . . . . . . . . . . 15 4 Rules of Esthetics in Photo Composition 16 4.1 Photo Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 4.2 Color and Intensity Distribution . . . . . . . . . . . . . . . . . . . . . . 24 4.3 Accuracy of Individual Features . . . . . . . . . . . . . . . . . . . . . . 29 5 Automatic Ranking of Photos 30 5.1 Precision and Recall . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 5.2 User Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 5.3 Speed Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 6 Conclusions and Future work 41 Bibliography 43 | |
| dc.language.iso | en | |
| dc.subject | 顏色分佈 | zh_TW |
| dc.subject | 照片排序 | zh_TW |
| dc.subject | 照片構圖 | zh_TW |
| dc.subject | 美學規則 | zh_TW |
| dc.subject | photo composition | en |
| dc.subject | Image ranking | en |
| dc.subject | photography esthetics | en |
| dc.title | 以攝影美學為基礎之照片排序系統 | zh_TW |
| dc.title | Automatic Photo Ranking Based on Esthetics Rules of
Photography | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 林奕成(I-Chen Lin),梁容輝(Rung-Huei Liang) | |
| dc.subject.keyword | 照片排序,照片構圖,美學規則,顏色分佈, | zh_TW |
| dc.subject.keyword | Image ranking,photo composition,photography esthetics, | en |
| dc.relation.page | 47 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2009-07-27 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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| ntu-98-1.pdf 未授權公開取用 | 29.19 MB | Adobe PDF |
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