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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 吳家麟(Ja-Ling Wu) | |
| dc.contributor.author | Jun-Cheng Chen | en |
| dc.contributor.author | 陳駿丞 | zh_TW |
| dc.date.accessioned | 2021-06-13T05:53:03Z | - |
| dc.date.available | 2008-07-17 | |
| dc.date.copyright | 2006-07-17 | |
| dc.date.issued | 2006 | |
| dc.date.submitted | 2006-07-03 | |
| dc.identifier.citation | [1] A.W.M. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain. Content-based image retrieval at the end of early year. IEEE Transaction on Pattern Analysis and Machine Intelligence, 22(12):1349–1380, 2000.
[2] J. Geigel and A. Loui. Using genetic algorithms for album page layouts. IEEE Multimedia, 10(4):16–27, 2003. [3] JC Platt, M. Czerwinski, and BA Field. PhotoTOC: automatic clustering for browsing personal photographs. the Fourth Pacific Rim Conference on Multimedia., 1:6–10, 2003. [4] ACDSee. http://www.acdsystems.com. [5] Picasa. http://picasa.google.com. [6] M. Cooper, J. Foote, A. Girgensohn, and L. Wilcox. Temporal event clustering for digital photo collections. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP), 1(3):269–288, 2005. [7] J. Luo, M. Boutell, and C. Brown. Pictures are not taken in a vacuum. Signal Processing Magazine, IEEE, 23(2):101–114, 2006. [8] X.S. Hua, L. Lu, and H.J. Zhang. Content based photograph slide show with incidental music. Proceedings of the 2003 International Symposium on Circuits and Systems., 2, 2003. [9] H. Tong, M. Li, H. Zhang, and C. Zhang. Blur detection for digital images using wavelet transform. 2004 IEEE International Conference on Multimedia and Expo, 2004. ICME’04., 1:17–20, 2004. [10] X.S. Hua, L. Lu, and H.J. Zhang. Automatically Converting Photographic Series into Video. ACM Multimedia 2004, pages 708–715, 2004. [11] Digital Still Camera Image File Format Standard. Japan Electronic Industry Development Association. 1998. [12] M. Ben-Ezra and S.K. Nayar. Motion-Based Motion Deblurring. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(6):689–699, 2004. [13] W.Q. Yan and M.S. Kankanhalli. Detection and removal of lighting & shaking artifacts in home videos. Proceedings of the tenth ACM international conference on Multimedia, pages 107–116, 2002. [14] Y.F. Ma, L. Lu, H.J. Zhang, and M. Li. A user attention model for video summarization. Proceedings of the tenth ACM international conference on Multimedia, pages 533–542, 2002. [15] E.D. Scheirer. Tempo and beat analysis of acoustic musical signals. The Journal of the Acoustical Society of America, 103:588, 1998. [16] A.Z. Vailaya, H.C.Y.F.I. Liu, and AK Jain. Automatic image orientation detection. IEEE Transactions on Image Processing, 11(7):746–755, 2002. [17] J. Luo and M. Boutell. Automatic image orientation detection via confidence-based integration of low-level and semantic cues. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(5):715–726, 2005. [18] D.G.J. Lowe. Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 60(2):91–110, 2004. [19] R. Molina, AK Katsaggelos, J. Abad, and J. Mateos. A Bayesian approach to blind deconvolution based on Dirichlet distributions. IEEE International Conference on Acoustics, Speech, and Signal Processing, 4:2809–2812, 1997. [20] AC Loui and A. Savakis. Automated event clustering and quality screening of consumer pictures for digital albuming. IEEE Transactions on Multimedia, 5(3):390–402, 2003. [21] U. Gargi. Modeling and clustering of photo capture streams. Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval, pages 47–54, 2003. [22] ISO/IEC 15938-3:2002(E), Information technology ¡ multimedia content description interface ¡ Part 3: Visual. 2002. [23] C. Christopoulos, A. Skodras, and T. Ebrahimi. The JPEG2000 still image coding system: an overview. IEEE Transactions on Consumer Electronics, 46(4):1103–1127, 2000. [24] C.M. Privitera and L.W. Stark. Algorithms for Defining Visual Regions-of-Interest: Comparison with Eye Fixations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(9):970–982, 2000. [25] A. Treisman and G. Gelade. A feature-integration theory of attention. Cognitive Psychology, 12(1):97–136, 1980. [26] C. Koch and S. Ullman. Shifts in selective visual attention: towards the underlying neural circuitry. Hum Neurobiol, 4(4):219–27, 1985. [27] L. Itti, C. Koch, and E. Niebur. A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(11):1254–1259, 1998. [28] Y.F. Ma and H.J. Zhang. Contrast-based image attention analysis by using fuzzy growing. Proceedings of the eleventh ACM international conference on Multimedia, pages 374–381, 2003. [29] K. Schill, E. Umkehrer, S. Beinlich, G. Krieger, and C. Zetzsche. Scene analysis with saccadic eye movements: Top-down and bottom-up modeling. Journal of Electronic Imaging, 10:152, 2001. [30] G.K. Deco and J.K. Zihl. A Neurodynamical Model of Visual Attention: Feedback Enhancement of Spatial Resolution in a Hierarchical System. Journal of Computational Neuroscience, 10(3):231–253, 2001. [31] P. Viola and M. Jones. Robust real-time object detection. International Journal of Computer Vision, 1(2), 2002. [32] R. Lienhart and J. Maydt. An extended set of Haar-like features for rapid object detection. Image Processing. 2002. Proceedings. 2002 International Conference on, 1, 2002. [33] Intel Open Source Computer Vision (OpenCV) library. http://www.intel.com/technology/computing/opencv/index.htm. [34] C. Panagiotakis and G. Tziritas. A speech/music discriminator based on RMS and zero-crossings. IEEE Transactions on Multimedia, 7(1):155–166, 2005. [35] Flickr. http://www.flickr.com/. [36] Photo Story 3. http://www.microsoft.com. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/34061 | - |
| dc.description.abstract | 這篇論文提出一種新的瀏覽媒介，複合式拼貼幻燈秀，以拼貼的方式展示照片，並配合襯底音樂的節拍播放。與傳統的照片幻燈秀比較，多張具相似特性的照片妥善地安排於相同版面中並播放。由科技寫作激發的靈感，每個版面配置由一張主題照片與多張修飾照片所組成。基於這想法，本幻燈秀系統由三個主要部分構成︰影像群集，音樂分析，版面配置。受限於展示的空間有限，我們考慮照片間的內容以及彼此的關係，並且將版面組織的轉變為一個條件最佳化的問題。
與單張照片播放的幻燈秀比較，實驗結果顯示我們的方法更能帶給使用者愉悅的照片瀏覽經驗。 | zh_TW |
| dc.description.abstract | This thesis presents a new medium, called tiling slideshow, to display photos in a tile-like manner, coordinating with the pace of background music. In contrast to conventional photo slideshow, multiple photos that have similar characteristics are well arranged and displayed at the same layout. Motivated by the guidelines of technical writing, each displaying layout is composed of a larger topic photo and several small-size supportive photos. Based on this idea, the proposed tiling slideshow system consists of three
major components: image clustering, music analyzer, and layout organizer. Given the limited displaying space, we consider the context and relationship between photos and model the layout organization as a constrainted optimization problem. Experiments on real consumer photograph collections show that the novel displaying method gives users more pleasant browsing experience than the methods that focus only on single photograph display. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T05:53:03Z (GMT). No. of bitstreams: 1 ntu-95-R93922025-1.pdf: 1202777 bytes, checksum: dcafe4f2f5ab2673100b162da18e1a03 (MD5) Previous issue date: 2006 | en |
| dc.description.tableofcontents | 1 Introduction ........................................... 1
1.1 Motivation ........................................... 1 1.2 Related Works ........................................ 3 1.3 The Proposed Solution ................................ 4 1.4 Thesis Organization .................................. 6 2 System Overview ........................................ 7 2.1 Essential Idea ....................................... 7 2.2 System Framework ..................................... 8 3 Visual Processing ...................................... 13 3.1 Photo Preprocess ..................................... 13 3.1.1 Orientation Correction ............................. 13 3.1.2 Underexposure/Overexposure Photo Detection ......... 15 3.1.3 Duplicate Photo Detection .......................... 15 3.1.4 Blur Photo Detection ............................... 16 3.2 Image Clustering ..................................... 19 3.2.1 Time-based Clustering .............................. 20 3.2.2 Content-based Clustering ........................... 22 3.3 Region of Interest Determination ..................... 27 3.3.1 Region of Interest ................................. 27 3.3.2 Bottom-up Attention Detection ...................... 28 3.3.3 Top-down Attention Detection ....................... 31 3.4 Summary .............................................. 32 4 Music Analysis ......................................... 33 4.1 Beat Detection ....................................... 33 4.2 Music Segmentation ................................... 37 4.3 Summary .............................................. 39 5 Tiling Slideshow Composition ........................... 40 5.1 Photo Importance ..................................... 42 5.1.1 Cluster-based Importance ........................... 42 5.1.2 Photo-based Importance ............................. 43 5.2 Cluster Selection .................................... 44 5.3 Tiling Frame Generation .............................. 44 5.4 Template Importance .................................. 45 5.5 Template Determination ............................... 46 5.6 Composition .......................................... 47 5.6.1 Region Selection ................................... 48 5.6.2 Implementation ..................................... 49 5.6.3 Discussion ......................................... 50 6 Experimental Results ................................... 51 6.1 The Photo Content Set ............................... 51 6.2 The Subjective User Evaluation ....................... 52 7 Conclusions and Future Work ............................ 56 7.1 Conclusions .......................................... 56 7.2 Future Work .......................................... 57 References ............................................... 58 | |
| dc.language.iso | en | |
| dc.subject | 幻燈秀 | zh_TW |
| dc.subject | 興趣區偵測 | zh_TW |
| dc.subject | 影像分群 | zh_TW |
| dc.subject | Region of interest detection | en |
| dc.subject | Slideshow | en |
| dc.subject | Image clustering | en |
| dc.title | 複合式拼貼音樂幻燈秀 | zh_TW |
| dc.title | Tiling Slideshow | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 94-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 莊永裕(Yung-Yu Chuang),陳炳宇(Bing-Yu Chen),林登彬(Lin Teng-Pin),許素朱(Su-Chu Hsu) | |
| dc.subject.keyword | 幻燈秀,影像分群,興趣區偵測, | zh_TW |
| dc.subject.keyword | Slideshow,Image clustering,Region of interest detection, | en |
| dc.relation.page | 62 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2006-07-04 | |
| 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-95-1.pdf 未授權公開取用 | 1.17 MB | Adobe PDF |
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