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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 歐陽明(Ming Ouhyoung) | |
dc.contributor.author | Wan-Ling Yang | en |
dc.contributor.author | 楊宛玲 | zh_TW |
dc.date.accessioned | 2021-06-08T02:55:01Z | - |
dc.date.copyright | 2017-08-10 | |
dc.date.issued | 2017 | |
dc.date.submitted | 2017-08-07 | |
dc.identifier.citation | [1] Indiana state university: Art department: Web archive of children's art. http://childart.indstate.edu/. (Accessed on 04/18/2017).
[2] Machinamenta: Drawing like a child. http://machinamenta.blogspot.tw/2013/08/drawing-like-child.html. (Accessed on 05/09/2017). [3] P. Arbelaez, M. Maire, C. Fowlkes, and J. Malik. Contour detection and hierarchical image segmentation. IEEE transactions on pattern analysis and machine intelligence, 33(5):898–916, 2011. [4] S. Belongie, J. Malik, and J. Puzicha. Shape context: A new descriptor for shape matching and object recognition. In Advances in neural information processing systems, pages 831–837, 2001. [5] I. Berger, A. Shamir, M. Mahler, E. Carter, and J. Hodgins. Style and abstraction in portrait sketching. ACM Transactions on Graphics (TOG), 32(4):55, 2013. [6] S. D. Bhattacharjee and A. Mittal. Part-based deformable object detection with a single sketch. Computer Vision and Image Understanding, 139:73–87, 2015. [7] E. Burton. Representing representation: making a computer draw like a child: an ma computing in design research project. ACM SIGGRAPH Computer Graphics, 29(3):28–32, 1995. [8] H. Chen, N.-N. Zheng, L. Liang, Y. Li, Y.-Q. Xu, and H.-Y. Shum. Pictoon: a personalized image-based cartoon system. In Proceedings of the tenth ACM international conference on Multimedia, pages 171–178. ACM, 2002. [9] J. P. Collomosse and P. M. Hall. Cubist style rendering from photographs. IEEE Transactions on Visualization and Computer Graphics, 9(4):443–453, 2003. [10] J. P. Collomosse, D. Rowntree, and P. M. Hall. Stroke surfaces: Temporally coherent artistic animations from video. IEEE transactions on visualization and computer graphics, 11(5):540–549, 2005. [11] D. DeCarlo and A. Santella. Stylization and abstraction of photographs. In ACM transactions on graphics (TOG), volume 21, pages 769–776. ACM, 2002. [12] E. Del Giudice, D. Grossi, R. Angelini, A. F. Crisanti, F. Latte, N. A. Fragassi, and L. Trojano. Spatial cognition in children. i. development of drawing-related (visuospatial and constructional) abilities in preschool and early school years. Brain and development, 22(6):362–367, 2000. [13] M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman. The pascal visual object classes (voc) challenge. International journal of computer vision, 88(2):303–338, 2010. [14] W. T. Freeman, J. B. Tenenbaum, and E. C. Pasztor. Learning style translation for the lines of a drawing. ACM Transactions on Graphics (TOG), 22(1):33–46, 2003. [15] L. A. Gatys, A. S. Ecker, and M. Bethge. Image style transfer using convolutional neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 2414–2423, 2016. [16] R. Gopalan, P. Turaga, and R. Chellappa. Articulation-invariant representation of non-planar shapes. Computer Vision–ECCV 2010, pages 286–299, 2010. [17] P. M. Hall, J. P. Collomosse, Y.-Z. Song, P. Shen, and C. Li. Rtcams: A new perspective on nonphotorealistic rendering from photographs. IEEE Transactions on Visualization and Computer Graphics, 13(5), 2007. [18] A. Hertzmann. Painterly rendering with curved brush strokes of multiple sizes. In Proceedings of the 25th annual conference on Computer graphics and interactive techniques, pages 453–460. ACM, 1998. [19] A. Hertzmann, N. Oliver, B. Curless, and S. M. Seitz. Curve analogies. In Rendering Techniques, pages 233–246, 2002. [20] P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros. Image-to-image translation with conditional adversarial networks. arXiv preprint arXiv:1611.07004, 2016. [21] E. Kalogerakis, D. Nowrouzezahrai, S. Breslav, and A. Hertzmann. Learning hatching for pen-and-ink illustration of surfaces. ACM Transactions on Graphics (TOG), 31(1):1, 2012. [22] R. Kennedy, J. Gallier, and J. Shi. Contour cut: Identifying salient contours in images by solving a hermitian eigenvalue problem. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pages 2065–2072. IEEE, 2011. [23] C. Lange-Küttner. Size and contour as crucial parameters in children drawing images. Children’s understanding and production of pictures, drawings, and art: Theoretical and empirical approaches, pages 89–106, 2008. [24] L. J. Latecki and R. Lakämper. Convexity rule for shape decomposition based on discrete contour evolution. Computer Vision and Image Understanding, 73(3):441–454, 1999. [25] H. Lee, S. Seo, S. Ryoo, and K. Yoon. Directional texture transfer. In Proceedings of the 8th International Symposium on Non-Photorealistic Animation and Rendering, pages 43–48. ACM, 2010. [26] Y. Li, Y.-Z. Song, T. M. Hospedales, and S. Gong. Free-hand sketch synthesis with deformable stroke models. International Journal of Computer Vision, pages 1–22, 2016. [27] H. Ling and D. W. Jacobs. Shape classification using the inner-distance. IEEE transactions on pattern analysis and machine intelligence, 29(2), 2007. [28] J. Lu, F. Yu, A. Finkelstein, and S. DiVerdi. Helpinghand: example-based stroke stylization. ACM Transactions on Graphics (TOG), 31(4):46, 2012. [29] D. Mould. A stained glass image filter. In Proceedings of the 14th Eurographics workshop on Rendering, pages 20–25. Eurographics Association, 2003. [30] A. Myronenko and X. Song. Point set registration: Coherent point drift. IEEE transactions on pattern analysis and machine intelligence, 32(12):2262–2275, 2010. [31] P. O’Donovan and D. Mould. Felt-based rendering. In Proceedings of the 4th international symposium on Non-photorealistic animation and rendering, pages 55–62. ACM, 2006. [32] Y. Qi, J. Guo, Y.-Z. Song, T. Xiang, H. Zhang, and Z.-H. Tan. Im2sketch: Sketch generation by unconflicted perceptual grouping. Neurocomputing, 165:338–349,2015. [33] A. Richards. The history of developmental stages of child art: 1857-1921. Drawing, psychology of children's art, pages 1974–1975, 1974. [34] S. Roncato, G. Sartori, J. Masterson, and R. Rumiati. Constructional apraxia: An information processing analysis. Cognitive Neuropsychology, 4(2):113–129, 1987. [35] Z. Sadeghi. Children's line drawings and object representation strategies: Categorization of children's mental representation strategies according to the existing theories for object recognition by studying line drawings. International Journal of Signal Processing, Image Processing and Pattern Recognition, 8(12):39–48, 2015. [36] P. Sangkloy, N. Burnell, C. Ham, and J. Hays. The sketchy database: learning to retrieve badly drawn bunnies. ACM Transactions on Graphics (TOG), 35(4):119, 2016. [37] M. Singh, G. D. Seyranian, and D. D. Hoffman. Parsing silhouettes: The short-cut rule. Attention, Perception, & Psychophysics, 61(4):636–660, 1999. [38] T. Szirányi and Z. Tóth. Optimization of paintbrush rendering of images by dynamic mcmc methods. In International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, pages 201–215. Springer, 2001. [39] X. Wang and X. Tang. Face photo-sketch synthesis and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(11):1955–1967, 2009. [40] J. Willats. Getting the drawing to look right as well as to be right: The interaction between production and perception as a mechanism of development. Advances inPsychology, 19:111–125, 1984. [41] M. Zhao and S.-C. Zhu. Portrait painting using active templates. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Non-Photorealistic Animation and Rendering, pages 117–124. ACM, 2011. [42] J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros. Unpaired image-to-image translation using cycle-consistent adversarial networks. arXiv preprint arXiv:1703.10593, 2017. [43] Q. Zhu, G. Song, and J. Shi. Untangling cycles for contour grouping. In Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on, pages 1–8. IEEE, 2007. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/20604 | - |
dc.description.abstract | 兒童的繪畫具有獨特的魅力與童趣,他們扭曲的筆觸和對世界簡化的描述是成年人難以模仿的。本論文提出了將照片轉化成兒童圖畫的方法,藉由重組現有兒童圖畫中的筆畫來重現出兒童圖畫的風格,並可由數個參數控制合成圖畫來模仿不同程度繪畫能力的表現。首先我們取出現有兒童圖畫中的筆畫並建立數個不同年齡層的筆畫資料庫,接著我們對輸入照片中的圖塊做一系列的分割與組合,得到數個線段並取出資料庫中相似的筆畫以重組出一張合成圖畫。藉由直接使用現存兒童圖畫中的筆觸,我們可以不用針對輸入照片來蒐集特定的兒童圖畫,並且對輸入照片的種類也沒有特別的限制。最後,我們進行了一個使用者研究來評量我們的方法。 | zh_TW |
dc.description.abstract | Drawings of children have unique charm due to the naive and untutored style. For easily producing the kid-style art, we proposed KidPen, a method transforming photos into kid-style sketches recomposing strokes in existed drawings of children and are manipulated by several parameters that control the drawing skills of children. We first extracted strokes from existed drawings of children and constructed
several stroke libraries. Then, a set of target segments of the input photo is generated by decomposing and combining the initial segmentation of the input photo. Finally, the segments are matched to similar strokes in the stroke library to compose the synthesized sketch. By directly using the strokes in existed drawings, KidPen works without pre-collecting children’s sketches of particular objects and are not restricted to the input of particular categories. A perceptual study is conducted and showed that our method could produce plausible kid-style sketches. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T02:55:01Z (GMT). No. of bitstreams: 1 ntu-106-R04944014-1.pdf: 13412230 bytes, checksum: 44905ad9f5fccb6345a696262be4eb7e (MD5) Previous issue date: 2017 | en |
dc.description.tableofcontents | 摘要ii
Abstract iii 1 Introduction 1 2 Related Works 3 2.1 Artistic Stylization 3 2.2 Kid-style Drawing Synthesis 5 2.3 Sketches Synthesis From Photos 6 2.4 Development in Children’s Art 7 3 Method 9 3.1 Overview 9 3.2 Stroke Library Construction and Analysis 12 3.2.1 Database 13 3.2.2 Stroke Extraction 13 3.2.3 Contour Decomposition 14 3.2.4 Stroke Libraries Construction 16 3.2.5 Library statistics 16 3.3 Sketch Synthesis 17 3.3.1 Segments Generation 17 3.3.2 Segmentation Selection 21 3.3.3 Stroke Matching 22 3.3.4 Stroke Placing and Connection 23 3.3.5 Stroke Texturing 25 4 Experiments 26 4.1 Demonstration 26 4.2 Perceptual Study 30 5 Discussion 34 5.1 Limitation and Failure Cases 34 5.2 Performance 36 6 Conclusion 37 6.1 Conclusion 37 6.2 Future Works 37 Bibliography 38 | |
dc.language.iso | en | |
dc.title | 基於筆畫重組之兒童風格圖畫生成 | zh_TW |
dc.title | KidPen: Automatic Kid-Style Sketches Synthesis from
Photos Based on Stroke Recomposing | en |
dc.type | Thesis | |
dc.date.schoolyear | 105-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 李明穗(Ming-Sui Lee),葉正聖(Jen-Sheng, Yeh) | |
dc.subject.keyword | 圖畫生成,非真實感繪製,兒童風格, | zh_TW |
dc.subject.keyword | Sketch Synthesis,Non-photorealistic Rendering,Kid-Style, | en |
dc.relation.page | 42 | |
dc.identifier.doi | 10.6342/NTU201701415 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2017-08-07 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
顯示於系所單位: | 資訊網路與多媒體研究所 |
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ntu-106-1.pdf 目前未授權公開取用 | 13.1 MB | Adobe PDF |
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