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Journal articles on the topic 'Cartons Computer-aided design'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Shan, Shuang, Yiting Ma, Chengcheng Tang, and Xuejin Chen. "Folding cartons: Interactive manipulation of cartons from 2D layouts." Computer Aided Geometric Design 62 (May 2018): 228–38. http://dx.doi.org/10.1016/j.cagd.2018.03.018.

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2

Zhu, Lifeng, Benyi Xie, Yongjie Jessica Zhang, and Lap-Fai Yu. "Cartonist: Automatic Synthesis and Interactive Exploration of Nonstandard Carton Design." Computer-Aided Design 114 (September 2019): 215–23. http://dx.doi.org/10.1016/j.cad.2019.04.007.

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3

Zhang, Lvmin, Tien-Tsin Wong, and Yuxin Liu. "Sprite-from-Sprite." ACM Transactions on Graphics 41, no. 6 (November 30, 2022): 1–12. http://dx.doi.org/10.1145/3550454.3555439.

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We present an approach to decompose cartoon animation videos into a set of "sprites" --- the basic units of digital cartoons that depict the contents and transforms of each animated object. The sprites in real-world cartoons are unique: artists may draw arbitrary sprite animations for expressiveness, where the animated content is often complicated, irregular, and challenging; alternatively, artists may also reduce their workload by tweening and adjusting sprites, or even reuse static sprites, in which case the transformations are relatively regular and simple. Based on these observations, we propose a sprite decomposition framework using Pixel Multilayer Perceptrons (Pixel MLPs) where the estimation of each sprite is conditioned on and guided by all other sprites. In this way, once those relatively regular and simple sprites are resolved, the decomposition of the remaining "challenging" sprites can simplified and eased with the guidance of other sprites. We call this method "sprite-from-sprite" cartoon decomposition. We study ablative architectures of our framework, and the user study demonstrates that our results are the most preferred ones in 19/20 cases.

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4

Liu, Feng. "Research on the Application of Cellular Algorithm in 3D Modeling of Cartoon Characters." Applied Mechanics and Materials 513-517 (February 2014): 1744–47. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1744.

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The traditional design method of 3D animation modelings, by which can obtain attractive and precise 3D animation modelings, is to use three-dimensional modeling software such as Maya or 3D Max to draw directly. However, this method is faced with many problems, for instance, the lack of creativity, long design circle, high production costs, etc. For the problem of the lack of creativity, the reason is that animation designers are often subject to the limitation of the existing modelings and design concepts in the design process, therefore, they can not design creative modelings which are attractive and unforgettable enough. [For the problem of long design circle and high production costs, the reason is that although the 3D animation software are powerful, to skillfully master them not only requires users to have knowledge of computer technology and aesthetics at the same time, but also need a long learning process of modeling. Moreover, it takes the designers a lot of time and energy to design, draw and complete each modeling, and this will undoubtedly extend the design circle and increase the costs to some extent. Therefore, how to quickly and automatically generate creative 3D animation modelings has become a research focus of the present computer-aided creative design.

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5

Fox, Barrett. "Funnelvision web cartoon." ACM SIGGRAPH Computer Graphics 34, no. 2 (May 2000): 60–61. http://dx.doi.org/10.1145/351440.351587.

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6

Yu, Jinhui, Xinan Jiang, Haiying Chen, and Cheng Yao. "Real-time cartoon water animation." Computer Animation and Virtual Worlds 18, no. 4-5 (2007): 405–14. http://dx.doi.org/10.1002/cav.207.

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7

Zhuang, Yueting, Jun Yu, Jun Xiao, and Cheng Chen. "Perspective-aware cartoon clips synthesis." Computer Animation and Virtual Worlds 19, no. 3-4 (2008): 355–64. http://dx.doi.org/10.1002/cav.258.

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8

Todo, Hideki, Ken Anjyo, and Takeo Igarashi. "Stylized lighting for cartoon shader." Computer Animation and Virtual Worlds 20, no. 2-3 (June 2009): 143–52. http://dx.doi.org/10.1002/cav.301.

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9

Yu, Jun, Yueting Zhuang, Jun Xiao, and Cheng Chen. "Adaptive control in cartoon data reusing." Computer Animation and Virtual Worlds 18, no. 4-5 (2007): 571–82. http://dx.doi.org/10.1002/cav.189.

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10

He, Haitao, and Duanqing Xu. "Real-time cartoon animation of smoke." Computer Animation and Virtual Worlds 16, no. 3-4 (2005): 441–49. http://dx.doi.org/10.1002/cav.103.

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11

Larnder, Chris Isaac. "Augmented perception via cartoon rendering." ACM SIGGRAPH Computer Graphics 40, no. 3 (November 2006): 8. http://dx.doi.org/10.1145/1186743.1186754.

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12

Sugisaki, Eiji, Yosuke Kazama, Shigeo Morishima, Natsuko Tanaka, and Akiko Sato. "Hair motion cloning from cartoon animation sequences." Computer Animation and Virtual Worlds 17, no. 3-4 (2006): 491–99. http://dx.doi.org/10.1002/cav.151.

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13

Yu, Jinhui, Jing Liao, and John Patterson. "Modeling the interaction between objects and cartoon water." Computer Animation and Virtual Worlds 19, no. 3-4 (2008): 375–85. http://dx.doi.org/10.1002/cav.239.

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14

Kawamoto, Shin-ichi, Tatsuo Yotsukura, Ken Anjyo, and Satoshi Nakamura. "Efficient lip-synch tool for 3D cartoon animation." Computer Animation and Virtual Worlds 19, no. 3-4 (2008): 247–57. http://dx.doi.org/10.1002/cav.250.

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15

Xu, Jun, Xiang Li, Yangchun Ren, and Weidong Geng. "Performance-driven animation of hand-drawn cartoon faces." Computer Animation and Virtual Worlds 22, no. 5 (March 14, 2011): 471–83. http://dx.doi.org/10.1002/cav.372.

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16

Zhang, Richard. "Computer Graphics and VR/AR: From Clouds, to Cartoons, to a 3-D Virtual Museum." IEEE Computer Graphics and Applications 42, no. 5 (September 1, 2022): 7. http://dx.doi.org/10.1109/mcg.2022.3201455.

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17

Jiao, Shaohui, Xin Chen, Gang Yang, and Enhua Wu. "Cartoon Fur Texture Synthesis and Replacement in Images and Videos." Journal of Computer-Aided Design & Computer Graphics 22, no. 7 (August 6, 2010): 1166–73. http://dx.doi.org/10.3724/sp.j.1089.2010.10912.

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18

Ono, Shunsuke, Takamichi Miyata, and Isao Yamada. "Cartoon-Texture Image Decomposition Using Blockwise Low-Rank Texture Characterization." IEEE Transactions on Image Processing 23, no. 3 (March 2014): 1128–42. http://dx.doi.org/10.1109/tip.2014.2299067.

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19

Mullineux, G., and J. Matthews. "Constraint-based simulation of carton folding operations." Computer-Aided Design 42, no. 3 (March 2010): 257–65. http://dx.doi.org/10.1016/j.cad.2009.12.003.

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20

Sur, Frederic. "A Non-Local Dual-Domain Approach to Cartoon and Texture Decomposition." IEEE Transactions on Image Processing 28, no. 4 (April 2019): 1882–94. http://dx.doi.org/10.1109/tip.2018.2881906.

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21

CHANG, CHUEH-WEI, and SUH-YIN LEE. "Automatic Cel Painting in Computer-assisted Cartoon Production using Similarity Recognition." Journal of Visualization and Computer Animation 8, no. 3 (July 1997): 165–85. http://dx.doi.org/10.1002/(sici)1099-1778(199707)8:3<165::aid-vis157>3.0.co;2-2.

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22

Shen, Yang, Lizhuang Ma, and Hai Liu. "An MLS-based cartoon deformation." Visual Computer 26, no. 9 (December 17, 2009): 1229–39. http://dx.doi.org/10.1007/s00371-009-0404-7.

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23

Dai, Jian S., and Ferdinando Cannella. "Stiffness Characteristics of Carton Folds for Packaging." Journal of Mechanical Design 130, no. 2 (2008): 022305. http://dx.doi.org/10.1115/1.2813785.

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24

Liu, Xueting, Wenliang Wu, Chengze Li, Yifan Li, and Huisi Wu. "Reference-guided structure-aware deep sketch colorization for cartoons." Computational Visual Media 8, no. 1 (October 27, 2021): 135–48. http://dx.doi.org/10.1007/s41095-021-0228-6.

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AbstractDigital cartoon production requires extensive manual labor to colorize sketches with visually pleasant color composition and color shading. During colorization, the artist usually takes an existing cartoon image as color guidance, particularly when colorizing related characters or an animation sequence. Reference-guided colorization is more intuitive than colorization with other hints, such as color points or scribbles, or text-based hints. Unfortunately, reference-guided colorization is challenging since the style of the colorized image should match the style of the reference image in terms of both global color composition and local color shading. In this paper, we propose a novel learning-based framework which colorizes a sketch based on a color style feature extracted from a reference color image. Our framework contains a color style extractor to extract the color feature from a color image, a colorization network to generate multi-scale output images by combining a sketch and a color feature, and a multi-scale discriminator to improve the reality of the output image. Extensive qualitative and quantitative evaluations show that our method outperforms existing methods, providing both superior visual quality and style reference consistency in the task of reference-based colorization.

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25

Liao, Jing, Jinhui Yu, and John Patterson. "Modeling ocean waves and interaction between objects and ocean water for cartoon animation." Computer Animation and Virtual Worlds 22, no. 2-3 (April 2011): 81–89. http://dx.doi.org/10.1002/cav.400.

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26

Gao, Yiming, and Xiaoping Yang. "A Cartoon-Texture Approach for JPEG/JPEG 2000 Decompression Based on TGV and Shearlet Transform." IEEE Transactions on Image Processing 28, no. 3 (March 2019): 1356–65. http://dx.doi.org/10.1109/tip.2018.2877485.

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27

Livny, Yotam, Michael Press, and Jihad El-Sana. "Interactive GPU-based adaptive cartoon-style rendering." Visual Computer 24, no. 4 (December 25, 2007): 239–47. http://dx.doi.org/10.1007/s00371-007-0201-0.

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28

Ng, M. K., Xiaoming Yuan, and Wenxing Zhang. "Coupled Variational Image Decomposition and Restoration Model for Blurred Cartoon-Plus-Texture Images With Missing Pixels." IEEE Transactions on Image Processing 22, no. 6 (June 2013): 2233–46. http://dx.doi.org/10.1109/tip.2013.2246520.

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29

Wan, Jerome, Guillaume Mougeot, and Xubo Yang. "Dense feature pyramid network for cartoon dog parsing." Visual Computer 36, no. 10-12 (July 9, 2020): 2471–83. http://dx.doi.org/10.1007/s00371-020-01887-5.

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30

Chih-Kuo Yeh, Pradeep Kumar Jayaraman, Xiaopei Liu, Chi-Wing Fu, and Tong-Yee Lee. "2.5D Cartoon Hair Modeling and Manipulation." IEEE Transactions on Visualization and Computer Graphics 21, no. 3 (March 1, 2015): 304–14. http://dx.doi.org/10.1109/tvcg.2014.2360406.

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31

Collomosse, J. P., D. Rowntree, and P. M. Hall. "Rendering cartoon-style motion cues in post-production video." Graphical Models 67, no. 6 (November 2005): 549–64. http://dx.doi.org/10.1016/j.gmod.2004.12.002.

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32

Dai, Jian S., and John Rees Jones. "Matrix Representation of Topological Changes in Metamorphic Mechanisms." Journal of Mechanical Design 127, no. 4 (July 24, 2004): 837–40. http://dx.doi.org/10.1115/1.1866159.

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Metamorphic mechanisms form a class of mechanisms that has the facilities to change configuration from one kind to another with a resultant change in the number of effective links and mobility of movement. This paper develops formal matrix operations to describe the distinct topology of configurations found in a metamorphic mechanism and to complete transformation between them. A new way is hence introduced for modeling topological changes of metamorphic mechanisms in general. It introduces a new elimination E-elementary matrix together with a U-elementary matrix to form an EU-elementary matrix operation to produce the configuration transformation. The use of these matrix operations is demonstrated in both spherical and spatial metamorphic mechanisms, the mechanistic models taken from the industrial packaging operations of carton folding manipulation that stimulated this study.

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33

Zhang, Lei, Hua Huang, and Hongbo Fu. "EXCOL: An EXtract-and-COmplete Layering Approach to Cartoon Animation Reusing." IEEE Transactions on Visualization and Computer Graphics 18, no. 7 (July 2012): 1156–69. http://dx.doi.org/10.1109/tvcg.2011.111.

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34

SI, Jingjing, Jing XIANG, Yinbo CHENG, and Kai LIU. "Compressive Phase Retrieval Realized by Combining Generalized Approximate Message Passing with Cartoon-Texture Model." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E101.A, no. 9 (September 1, 2018): 1608–15. http://dx.doi.org/10.1587/transfun.e101.a.1608.

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35

MacCallum-Stewart, Esther. "‘The street smarts of a cartoon princess’. New roles for women in games." Digital Creativity 20, no. 4 (December 2009): 225–37. http://dx.doi.org/10.1080/14626260903290299.

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36

Allen, Barry A., and Cyrus Levinthal. "CARTOS II semi-automated nerve tracing: Three-dimensional reconstruction from serial section micrographs." Computerized Medical Imaging and Graphics 14, no. 5 (September 1990): 319–29. http://dx.doi.org/10.1016/0895-6111(90)90106-l.

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37

Qiu, C., Vahid Aminzadeh, and Jian S. Dai. "Kinematic Analysis and Stiffness Validation of Origami Cartons." Journal of Mechanical Design 135, no. 11 (September 27, 2013). http://dx.doi.org/10.1115/1.4025381.

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Origami-type cartons have been widely used in packaging industry because of their versatility, but there is a lack of systematic approach to study their folding behavior, which is a key issue in designing packaging machines in packaging industry. This paper addresses the fundamental issue by taking the geometric design and material property into consideration, and develops mathematical models to predict the folding characteristics of origami cartons. Three representative types of cartons, including tray cartons, gable cartons, and crash-lock cartons were selected, and the static equilibrium of folding process was developed based on their kinematic models in the frame work of screw theory. Subsequently, folding experiments of both single crease and origami carton samples were conducted. Mathematical models of carton folding were obtained by aggregating single crease's folding characteristics into the static equilibrium, and they showed good agreements with experiment results. Furthermore, the mathematical models were validated with folding experiments of one complete food packaging carton, which shows the overall approach has potential value in predicting carton's folding behavior with different material properties and geometric designs.

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38

Yao, Wei, and Jian S. Dai. "Dexterous Manipulation of Origami Cartons With Robotic Fingers Based on the Interactive Configuration Space." Journal of Mechanical Design 130, no. 2 (December 27, 2007). http://dx.doi.org/10.1115/1.2813783.

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This paper investigates the equivalent mechanism structure of origami cartons and for the first time proposes a quantitative model of cartons and the interactive configuration space for folding origami cartons. With an analysis of the equivalent mechanism, gusset vertexes of cartons are investigated based on their equivalent spherical linkages and identified as guiding linkages that determine folding. Having established a kinematics model, a configuration control vector is characterized to control carton manipulation. The information of this configuration control vector is passed to the tip of a robotic finger, and the finger configuration space is hence identified. The paper further introduces configuration transformation and creates a carton interactive configuration space, leading to generating trajectories of all four configuration control vectors and, subsequently, to finger operation trajectories. This results in making use of four robotic fingers for folding origami cartons. The interactive technique is further used for final tucking carton flaps. A novel rig with robotic fingers is then presented to demonstrate the principle and concept.

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39

Mullineux, Glen. "On the Torque Characteristic of a Crash-Lock Carton Base." Journal of Mechanical Design 131, no. 8 (July 9, 2009). http://dx.doi.org/10.1115/1.3151800.

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An important part of some packaging cartons is the crash-lock base. A recent investigation of the torque required for its erection has made some linearizing assumptions. It is here shown that these can be avoided as the relations connecting the angles between panels can be found. This also indicates that the final increase in the required torque is due to geometric effects rather than frictional ones.

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40

Wei, Guowu, and Jian S. Dai. "Origami-Inspired Integrated Planar-Spherical Overconstrained Mechanisms." Journal of Mechanical Design 136, no. 5 (March 19, 2014). http://dx.doi.org/10.1115/1.4025821.

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This paper presents two integrated planar-spherical overconstrained mechanisms that are inspired and evolved from origami cartons with a crash-lock base. Investigating the crash-lock base of the origami cartons, the first overconstrained mechanism is evolved by integrating a planar four-bar linkage with two spherical linkages in the diagonal corners. The mechanism has mobility one and the overconstraint was exerted by the two spherical linkages. This mechanism is then evolved into another integrated planar-spherical overconstrained mechanism with two double-spherical linkages at the diagonal corners. The evolved mechanism has mobility one. It is interesting to find that the double-spherical linkage at the corner of this new mechanism is an overconstrained 6R linkage. The geometry evolution is presented and the constraint matrices of the mechanisms are formulated using screw-loop equations verifying mobility of the mechanisms. The paper further reveals the assembly conditions and geometric constraint of the two overconstrained mechanisms. Further, with mechanism decomposition, geometry and kinematics of the mechanisms are investigated with closed-form equations, leading to comparison of these two mechanisms with numerical simulation. The paper further proposes that the evolved overconstrained mechanism can in reverse lead to new origami folds and crease patterns. The paper hence not only lays the groundwork for kinematic investigation of origami-inspired mechanisms but also sheds light on the investigation of integrated overconstrained mechanisms.

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41

Yu, Jun, Dongquan Liu, and Hock Soon Seah. "Transductive graph based cartoon synthesis." Computer Animation and Virtual Worlds, 2010, n/a. http://dx.doi.org/10.1002/cav.355.

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42

Li, Yong, Lingjie Lao, Zhen Cui, Shiguang Shan, and Jian Yang. "Graph Jigsaw Learning for Cartoon Face Recognition." IEEE Transactions on Image Processing, 2022, 1. http://dx.doi.org/10.1109/tip.2022.3177952.

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43

Fukusato, Tsukasa, and Akinobu Maejima. "View-Dependent Deformation for 2.5D Cartoon Models." IEEE Computer Graphics and Applications, 2022, 1. http://dx.doi.org/10.1109/mcg.2022.3174202.

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44

Li, Xiang, Jun Xu, Yangchun Ren, and Weidong Geng. "Animating cartoon faces by multi-view drawings." Computer Animation and Virtual Worlds, 2010, n/a. http://dx.doi.org/10.1002/cav.344.

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45

Lei, Peng, Shuchang Xu, and Sanyuan Zhang. "An art-oriented pixelation method for cartoon images." Visual Computer, January 7, 2023. http://dx.doi.org/10.1007/s00371-022-02763-0.

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46

Chen, Shu-Yu, Jia-Qi Zhang, Lin Gao, Yue He, Shihong Xia, Min Shi, and Fang-Luee Zhang. "Active Colorization for Cartoon Line Drawings." IEEE Transactions on Visualization and Computer Graphics, 2020, 1. http://dx.doi.org/10.1109/tvcg.2020.3009949.

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47

Li, Xiaoyu, Bo Zhang, Jing Liao, and Pedro Sander. "Deep Sketch-guided Cartoon Video Inbetweening." IEEE Transactions on Visualization and Computer Graphics, 2021, 1. http://dx.doi.org/10.1109/tvcg.2021.3049419.

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48

Ma, Ziheng, Chengze Li, Xueting Liu, Huisi Wu, and Zhenkun Wen. "Separating Shading and Reflectance from Cartoon Illustrations." IEEE Transactions on Visualization and Computer Graphics, 2023, 1–17. http://dx.doi.org/10.1109/tvcg.2023.3239364.

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49

Xu, Cheng, Wei Qu, Xuemiao Xu, and Xueting Liu. "Multi-scale Flow-based Occluding Effect and Content Separation for Cartoon Animations." IEEE Transactions on Visualization and Computer Graphics, 2022, 1. http://dx.doi.org/10.1109/tvcg.2022.3174656.

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50

Rasmussen, Mikkel Bayard, Kelvin Østergaard Pagels, and Devarajan Ramanujan. "Supporting Household Waste Sorting Practices by Addressing Information Gaps." Journal of Computing and Information Science in Engineering 20, no. 4 (April 3, 2020). http://dx.doi.org/10.1115/1.4046734.

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Abstract The Danish government has outlined a target of recycling 50% of total household waste by the year 2022 and transitioning to a circular economy in the future. Improving household waste sorting is an important consideration toward achieving this goal. This paper focuses on understanding existing waste sorting practices among Danish residents. We conducted a preliminary survey (N = 180) that assessed preference for sorting strategies and the types of waste sorted. Following this, a more detailed survey was conducted (N = 357) that assessed residents’ motivation to sort household waste, knowledge of local sorting requirements, information gaps that prevent effective sorting, and need for specific features in a mobile application. Results show that over one-third of respondents felt they needed additional waste sorting information. Respondents had fewer inaccuracies disposing items within a single waste stream (e.g., electronics waste) compared to items with mixed waste streams (e.g., milk carton with a plastic cap). Based on these findings, we propose the design of a mobile application that can potentially support household waste sorting in Denmark.

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