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Journal articles on the topic 'Matting'

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1

Kingston, Thomas, Nicholas B. Tiller, Elle Partington, et al. "Sports safety matting diminishes cardiopulmonary resuscitation quality and increases rescuer perceived exertion." PLOS ONE 16, no. 7 (2021): e0254800. http://dx.doi.org/10.1371/journal.pone.0254800.

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Objectives Compliant surfaces beneath a casualty diminish the quality of cardiopulmonary resuscitation (CPR) in clinical environments. To examine this issue in a sporting environment, we assessed chest compression quality and rescuer exertion upon compliant sports safety matting. Methods Twenty-seven advanced life support providers volunteered (13 male/14 female; mass = 79.0 ± 12.5 kg; stature = 1.77 ± 0.09 m). Participants performed 5 × 2 min, randomized bouts of continuous chest compressions on a mannequin, upon five surfaces: solid floor; low-compliance matting; low-compliance matting with
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Liu, Bo, Haipeng Jing, Guangzhi Qu, and Hans W. Guesgen. "Cascaded Segmented Matting Network for Human Matting." IEEE Access 9 (2021): 157182–91. http://dx.doi.org/10.1109/access.2021.3125356.

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Bessmertnyi, V. S., N. M. Zdorenko, D. V. Kochurin, et al. "MODERN TRENDS IN THE DEVELOPMENT OF TECHNOLOGIES FOR MATTING GLASS PRODUCTS." Steklo i Keramika, no. 11 (November 2022): 17–24. http://dx.doi.org/10.14489/glc.2022.11.pp.017-024.

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Modern trends in the development of technologies for matting glass and glass products are considered. An effective technology of glass matting using alternative energy sources, in particular low-temperature plasma, has been developed. It is shown that when matting with iron powders with a dispersion of 160 and 450 microns, a high-quality matte surface of the “frosty” matting type is formed. The microstructure of the matted surface is investigated. Theoretical aspects of glass matting are considered. The technological parameters of matting are determined and the economic efficiency of the devel
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TAN, GUANGHUA, JUN QI, CHUNMING GAO, JIN CHEN, and LIYUAN ZHUO. "SALIENCY-BASED UNSUPERVISED IMAGE MATTING." International Journal of Pattern Recognition and Artificial Intelligence 28, no. 04 (2014): 1454001. http://dx.doi.org/10.1142/s0218001414540019.

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Spectral matting is the state-of-the-art matting method and can well solve the highly under-conditioned matte problem without manual intervention. However, it suffers from huge computation cost and inaccurate alpha matte. This paper presents a modified spectral matting method which combines saliency detection algorithm to get a higher accuracy of alpha matte with less computational cost. First, the saliency detection algorithm is used to detect general locations of foreground objects. For saliency detection method, original two-stage scheme is replaced by feedback scheme to get a more suitable
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Huang, Lingtao, Xipeng Liu, Xuelin Wang, Jiangqi Li, and Benying Tan. "Deep Learning Methods in Image Matting: A Survey." Applied Sciences 13, no. 11 (2023): 6512. http://dx.doi.org/10.3390/app13116512.

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Image matting is a fundamental technique used to extract a fine foreground image from a given image by estimating the opacity values of each pixel. It is one of the key techniques in image processing and has a wide range of applications in practical scenarios, such as in image and video editing. Deep learning has demonstrated outstanding performance in various image processing tasks, making it a popular research topic. In recent years, image matting methods based on deep learning have gained significant attention due to their superior performance. Therefore, this article presents a comprehensi
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Sun, Jian, Jiaya Jia, Chi-Keung Tang, and Heung-Yeung Shum. "Poisson matting." ACM Transactions on Graphics 23, no. 3 (2004): 315–21. http://dx.doi.org/10.1145/1015706.1015721.

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Levin, A., A. Rav Acha, and D. Lischinski. "Spectral Matting." IEEE Transactions on Pattern Analysis and Machine Intelligence 30, no. 10 (2008): 1699–712. http://dx.doi.org/10.1109/tpami.2008.168.

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Chen, Qifeng, Dingzeyu Li, and Chi-Keung Tang. "KNN Matting." IEEE Transactions on Pattern Analysis and Machine Intelligence 35, no. 9 (2013): 2175–88. http://dx.doi.org/10.1109/tpami.2013.18.

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Lepage, Daniel, and Jason Lawrence. "Material matting." ACM Transactions on Graphics 30, no. 6 (2011): 1–10. http://dx.doi.org/10.1145/2070781.2024178.

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Sun, Jian, Yin Li, Sing Bing Kang, and Heung-Yeung Shum. "Flash matting." ACM Transactions on Graphics 25, no. 3 (2006): 772–78. http://dx.doi.org/10.1145/1141911.1141954.

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Gu, Zeqi, Wenqi Xian, Noah Snavely, and Abe Davis. "FactorMatte: Redefining Video Matting for Re-Composition Tasks." ACM Transactions on Graphics 42, no. 4 (2023): 1–14. http://dx.doi.org/10.1145/3592423.

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We propose Factor Matting , an alternative formulation of the video matting problem in terms of counterfactual video synthesis that is better suited for re-composition tasks. The goal of factor matting is to separate the contents of a video into independent components, each representing a counterfactual version of the scene where the contents of other components have been removed. We show that factor matting maps well to a more general Bayesian framing of the matting problem that accounts for complex conditional interactions between layers. Based on this observation, we present a method for so
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Wu, Xian, Xiao-Nan Fang, Tao Chen, and Fang-Lue Zhang. "JMNet: A joint matting network for automatic human matting." Computational Visual Media 6, no. 2 (2020): 215–24. http://dx.doi.org/10.1007/s41095-020-0168-6.

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Mao, Qin, Ting Yan Ren, and Tian Jian Zheng. "The Graph Cut Energy Image Matting Model Based on Dynamic Weight Parameter." Applied Mechanics and Materials 556-562 (May 2014): 5148–52. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.5148.

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The traditional graph cut algorithm for complex image matting accuracy is not high, the weight parameters in the dynamic graph cut energy model is based on image matting. The degree of similarity the algorithm uses Gauss model to calculate the foreground color and background color, in graph cut energy model of dynamic weight parameters are added, by it and then many corrections to the image matting. The experimental results show that the algorithm is easy to operate, that can improve the accuracy of image matting.
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Yu, Haichao, Ning Xu, Zilong Huang, Yuqian Zhou, and Humphrey Shi. "High-Resolution Deep Image Matting." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 4 (2021): 3217–24. http://dx.doi.org/10.1609/aaai.v35i4.16432.

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Image matting is a key technique for image and video editing and composition. Conventionally, deep learning approaches take the whole input image and an associated trimap to infer the alpha matte using convolutional neural networks. Such approaches set state-of-the-arts in image matting; however, they may fail in real-world matting applications due to hardware limitations, since real-world input images for matting are mostly of very high resolution. In this paper, we propose HDMatt, a first deep learning based image matting approach for high-resolution inputs. More concretely, HDMatt runs matt
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Dawson, Cody, Parker Henley, Adam Schroeder, et al. "23 Effects of Rubber Matting on Cattle Locomotion Scores in Slatted Facilities." Journal of Animal Science 99, Supplement_1 (2021): 23. http://dx.doi.org/10.1093/jas/skab054.040.

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Abstract The objective was to determine effects of interlocking rubber floor matting in slatted indoor cattle feeding facilities on cattle locomotion. In experiment 1, Fall-born Angus × Simmental steers (N = 206; BW = 228 ± 34 kg) were blocked by weight and assigned to 32 pens. Pens were randomly assigned to 1 of 4 treatments: new Max Grip Animat matting (MG), new Animat Pebble matting (PEB), old Animat Pebble matting (OLD), and no matting/concrete slating (CONC). Steers were fed a common diet for 209 d with an average stocking density of 3.70 m2 per steer. Locomotion scores were assigned by t
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Dawson, Cody, Parker Henley, Adam Schroeder, et al. "243 Effects of rubber matting on cattle performance and carcass characteristics in slatted facilities." Journal of Animal Science 98, Supplement_3 (2020): 9. http://dx.doi.org/10.1093/jas/skaa054.015.

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Abstract The objective was to determine effects of interlocking rubber floor matting in slatted indoor cattle feeding facilities on cattle performance and carcass characteristics. In experiment 1, Fall-born Angus x Simmental steers (N = 206; BW = 228 ± 34 kg) were blocked by weight and assigned to 32 pens. Pens were randomly assigned to 1 of 4 treatments: new Max Grip Animat matting (MG), new Animat Pebble matting (PEB), old Animat Pebble matting (OLD), and no matting/concrete slating (CONC). Steers were fed a common diet for 209 d with an average stocking density of 3.70 m2 per steer. Final B
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Chen, Aoran, Hai Huang, Yueyan Zhu, and Junsheng Xue. "Real-Time Multi-Person Video Synthesis with Controllable Prior-Guided Matting." Sensors 24, no. 9 (2024): 2795. http://dx.doi.org/10.3390/s24092795.

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In order to enhance the matting performance in multi-person dynamic scenarios, we introduce a robust, real-time, high-resolution, and controllable human video matting method that achieves state of the art on all metrics. Unlike most existing methods that perform video matting frame by frame as independent images, we design a unified architecture using a controllable generation model to solve the problem of the lack of overall semantic information in multi-person video. Our method, called ControlMatting, uses an independent recurrent architecture to exploit temporal information in videos and ac
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18

Singh, Sweta, and Anand Singh Jalal. "Digital Image Matting." International Journal of Computer Vision and Image Processing 3, no. 4 (2013): 16–36. http://dx.doi.org/10.4018/ijcvip.2013100102.

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Digital image matting is the process of softly fetching foreground objects from an image. It has become a widely used application for editing the images and to give special effect in the film production industry. Reducing the cost in film making, giving special effect in movies and editing the images are the main motivations for matting. This paper provides a concise review of various approaches for solving matting problem. These approaches can be broadly categorized into two categories: Trimap-based and Scribble-based matting approaches. This paper also provides strengths and weaknesses of va
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19

McGuire, Morgan, Wojciech Matusik, Hanspeter Pfister, John F. Hughes, and Frédo Durand. "Defocus video matting." ACM Transactions on Graphics 24, no. 3 (2005): 567–76. http://dx.doi.org/10.1145/1073204.1073231.

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Wu, Tai-Pang, Chi-Keung Tang, Michael S. Brown, and Heung-Yeung Shum. "Natural shadow matting." ACM Transactions on Graphics 26, no. 2 (2007): 8. http://dx.doi.org/10.1145/1243980.1243982.

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21

Duan, Qi, Jianfei Cai, and Jianmin Zheng. "Compressive environment matting." Visual Computer 31, no. 12 (2014): 1587–600. http://dx.doi.org/10.1007/s00371-014-1035-1.

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Guan, Yu, Wei Chen, Xiao Liang, Zi'ang Ding, and Qunsheng Peng. "Matting and Compositing." Computer Graphics Forum 25, no. 3 (2006): 567–76. http://dx.doi.org/10.1111/j.1467-8659.2006.00976.x.

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23

Li, Rui, Dan Zhang, Sheng-Ling Geng, and Ming-Quan Zhou. "Matting Algorithm with Improved Portrait Details for Images with Complex Backgrounds." Applied Sciences 14, no. 5 (2024): 1942. http://dx.doi.org/10.3390/app14051942.

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With the continuous development of virtual reality, digital image applications, the required complex scene video proliferates. For this reason, portrait matting has become a popular topic. In this paper, a new matting algorithm with improved portrait details for images with complex backgrounds (MORLIPO) is proposed. This work combines the background restoration module (BRM) and the fine-grained matting module (FGMatting) to achieve high-detail matting for images with complex backgrounds. We recover the background by inputting a single image or video, which serves as a priori and aids in genera
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24

Hu, Wu-Chih, Jia-Jie Jhu, and Cheng-Pin Lin. "Unsupervised and reliable image matting based on modified spectral matting." Journal of Visual Communication and Image Representation 23, no. 4 (2012): 665–76. http://dx.doi.org/10.1016/j.jvcir.2012.03.003.

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Liao, Hong Jian, Xiao Li Long, and Li Ping Wang. "Research on Construction of Kinect-Based Virtual Situation Laboratory." Applied Mechanics and Materials 532 (February 2014): 259–63. http://dx.doi.org/10.4028/www.scientific.net/amm.532.259.

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In order to solve the problems of expensive and non-universal dedicated virtual situational teaching laboratory equipments, this paper proposed to apply Kinect to establish low-cost and strongly-immersive virtual situational teaching system. Figure image matting is a key issue of Kinect-based virtual situational teaching system. So a fast and real-time matting algorithm is hereby put forward with use of Kinect depth map. It adopt improved region growth algorithm to obtain trimap, coupled with the use of a set of shared sample points with low computational complexity. Through weighted filtering
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Xie, Honggang, Kaiyuan Hou, Di Jiang, and Wanjie Ma. "Bust Portraits Matting Based on Improved U-Net." Electronics 12, no. 6 (2023): 1378. http://dx.doi.org/10.3390/electronics12061378.

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Extracting complete portrait foregrounds from natural images is widely used in image editing and high-definition map generation. When making high-definition maps, it is often necessary to matte passers-by to guarantee their privacy. Current matting methods that do not require additional trimap inputs often suffer from inaccurate global predictions or blurred local details. Portrait matting, as a soft segmentation method, allows the creation of excess areas during segmentation, which inevitably leads to noise in the resulting alpha image as well as excess foreground information, so it is not ne
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Huang, Mengcheng, Fang Liu, and Enhua Wu. "A GPU-based matting Laplacian solver for high resolution image matting." Visual Computer 26, no. 6-8 (2010): 943–50. http://dx.doi.org/10.1007/s00371-010-0435-0.

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Joshi, Neel, Wojciech Matusik, Shai Avidan, Hanspeter Pfister, and William Freeman. "Exploring Defocus Matting: Nonparametric Acceleration, Super-Resolution, and Off-Center Matting." IEEE Computer Graphics and Applications 27, no. 2 (2007): 43–52. http://dx.doi.org/10.1109/mcg.2007.32.

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Li, Yaoyi, and Hongtao Lu. "Natural Image Matting via Guided Contextual Attention." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (2020): 11450–57. http://dx.doi.org/10.1609/aaai.v34i07.6809.

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Over the last few years, deep learning based approaches have achieved outstanding improvements in natural image matting. Many of these methods can generate visually plausible alpha estimations, but typically yield blurry structures or textures in the semitransparent area. This is due to the local ambiguity of transparent objects. One possible solution is to leverage the far-surrounding information to estimate the local opacity. Traditional affinity-based methods often suffer from the high computational complexity, which are not suitable for high resolution alpha estimation. Inspired by affinit
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Lupyak, D. D., and R. N. Kvyetnyy. "Ways to increase the efficiency of modern methods of image matting." Optoelectronic Information-Power Technologies 41, no. 1 (2021): 33–38. http://dx.doi.org/10.31649/1681-7893-2021-41-1-33-38.

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The analytical review of modern methods of image matting is carried out in the work. The key ideas of existing methods are identified, and their accuracy is compared. Problems and tasks for further research of image matting methods are identified.
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Ke, Zhanghan, Jiayu Sun, Kaican Li, Qiong Yan, and Rynson W. H. Lau. "MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 1 (2022): 1140–47. http://dx.doi.org/10.1609/aaai.v36i1.19999.

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Existing portrait matting methods either require auxiliary inputs that are costly to obtain or involve multiple stages that are computationally expensive, making them less suitable for real-time applications. In this work, we present a light-weight matting objective decomposition network (MODNet) for portrait matting in real-time with a single input image. The key idea behind our efficient design is by optimizing a series of sub-objectives simultaneously via explicit constraints. In addition, MODNet includes two novel techniques for improving model efficiency and robustness. First, an Efficien
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Li, Hanxi, Wenyu Zhu, Haiqiang Jin, and Yong Ma. "Automatic, Illumination-Invariant and Real-Time Green-Screen Keying Using Deeply Guided Linear Models." Symmetry 13, no. 8 (2021): 1454. http://dx.doi.org/10.3390/sym13081454.

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The conventional green screen keying method requires users’ interaction to guide the whole process and usually assumes a well-controlled illumination environment. In the era of “we-media”, millions of short videos are shared online every day, and most of them are produced by amateurs in relatively poor conditions. As a result, a fully automatic, real-time, and illumination-robust keying method would be very helpful and commercially promising in this era. In this paper, we propose a linear model guided by deep learning prediction to solve this problem. The simple, yet effective algorithm inheri
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Xie, Honglei, Hai Fang, Wei Cai, Li Wan, Ruili Huo, and David Hui. "Development of an innovative composite sandwich matting with GFRP facesheets and wood core." REVIEWS ON ADVANCED MATERIALS SCIENCE 60, no. 1 (2021): 80–91. http://dx.doi.org/10.1515/rams-2021-0016.

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Abstract This paper presents the concept, design, fabrication, application and experimental validation of a new type of composite sandwich matting. The composite sandwich matting comprises a paulownia woods as core material and glass fiber reinforced plastic (GFRP) as face-skins and lattice-webs. The matting was fabricated by vacuum infusion moulding process (VIMP). The mechanical properties of the component materials were studied. Four-point bending tests were also performed to investigate the flexural properties of the paulownia wood core sandwich panels. The experimental results showed that
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Chen, Zhenpeng, Yuanjie Zheng, Xiaojie Li, et al. "Interactive Trimap Generation for Digital Matting Based on Single-Sample Learning." Electronics 9, no. 4 (2020): 659. http://dx.doi.org/10.3390/electronics9040659.

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Image matting refers to the task of estimating the foreground of images, which is an important problem in image processing. Recently, trimap generation has attracted considerable attention because designing a trimap for every image is labor-intensive. In this paper, a two-step algorithm is proposed to generate trimaps. To use the proposed algorithm, users must only provide some clicks (foreground clicks and background clicks), which are employed as the input to generate a binary mask. One-shot learning technique achieves remarkable progress on semantic segmentation, we extend this technique to
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Khader, Anza, ManikothPayyanadan Binitha, and Sharanya Padma. "Matting of body hair." Indian Journal of Dermatology, Venereology, and Leprology 83, no. 4 (2017): 462. http://dx.doi.org/10.4103/0378-6323.204201.

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YANG, Wei, Tao GAN, and Gang LAN. "Texture clustering matting algorithm." Journal of Computer Applications 33, no. 11 (2013): 3213–16. http://dx.doi.org/10.3724/sp.j.1087.2013.03213.

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Xiahou, Jian Bing, Xiao Wei Liu, Qian Qian Wei, and Xiao Na Deng. "Survey on Matting Algorithm." Advanced Materials Research 926-930 (May 2014): 3270–75. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3270.

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Keyer technology is the mainstream of computer graphics technology, this article first made a simple statement of the keyer technical background and application , then divided matting technology into two categories: hard keyer and soft keyer and some of their commonly used algorithms, at the same time this article pointed out the technical problem of the existing keyer technology and some improvement methods, finally combining with the commonly used several methods, had a video as experiments and showed the results.
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Siragusa, M., G. Fabrizi, S. Calvieri, and C. Schepis. "Matting of Scalp Hair." Dermatology 192, no. 4 (1996): 347–49. http://dx.doi.org/10.1159/000246409.

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Meyer, J., and M. Scholz. "Matting of Silicone Sealants." International Polymer Science and Technology 31, no. 1 (2004): 1–6. http://dx.doi.org/10.1177/0307174x0403100101.

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Zhang, Zhan, Yuehai Wang, and Jianyi Yang. "Deep quantised portrait matting." IET Computer Vision 14, no. 6 (2020): 339–49. http://dx.doi.org/10.1049/iet-cvi.2019.0779.

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Thappa, Devinder Mohan, Kaliaperumal Karthikeyan, and Balasubramanian Jeevankumar. "Matting of Scalp Hair." Journal of Dermatology 29, no. 12 (2002): 818–19. http://dx.doi.org/10.1111/j.1346-8138.2002.tb00231.x.

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Hu, Wu-Chih, and Jung-Fu Hsu. "Automatic spectral video matting." Pattern Recognition 46, no. 4 (2013): 1183–94. http://dx.doi.org/10.1016/j.patcog.2012.10.012.

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Lopez, Ana Belén, Silfredo Javier Bohórquez, Marcel Meeuwisse, Dirk Mestach, José C. de la Cal, and José M. Asua. "Self-matting waterborne fluoropolymers." Progress in Organic Coatings 116 (March 2018): 57–69. http://dx.doi.org/10.1016/j.porgcoat.2017.12.003.

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Chuang, Yung-Yu, Dan B. Goldman, Brian Curless, David H. Salesin, and Richard Szeliski. "Shadow matting and compositing." ACM Transactions on Graphics 22, no. 3 (2003): 494–500. http://dx.doi.org/10.1145/882262.882298.

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Chen, Guanying, Kai Han, and Kwan-Yee K. Wong. "Learning Transparent Object Matting." International Journal of Computer Vision 127, no. 10 (2019): 1527–44. http://dx.doi.org/10.1007/s11263-019-01202-3.

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Li, Xuelong, Kang Liu, Yongsheng Dong, and Dacheng Tao. "Patch Alignment Manifold Matting." IEEE Transactions on Neural Networks and Learning Systems 29, no. 7 (2018): 3214–26. http://dx.doi.org/10.1109/tnnls.2017.2727140.

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Xudong Kang, Shutao Li, and Jon Atli Benediktsson. "Pansharpening With Matting Model." IEEE Transactions on Geoscience and Remote Sensing 52, no. 8 (2014): 5088–99. http://dx.doi.org/10.1109/tgrs.2013.2286827.

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Lee, Sun-Young, Jong-Chul Yoon, and In-Kwon Lee. "Temporally coherent video matting." Graphical Models 72, no. 3 (2010): 25–33. http://dx.doi.org/10.1016/j.gmod.2010.03.001.

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Xiahou, Jian Bing, Xiao Na Deng, Qian Qian Wei, and Xiao Wei Liu. "Real-Time Video Matting Algorithm Based on Chroma Key." Advanced Materials Research 926-930 (May 2014): 3161–64. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3161.

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Image matting is a technology to extract interested prospects or subtract the background from videos or images. It is more and more widely used in television and movie production, virtual studio, network education, video monitoring and many other fields. Mainly aims at the pure-colored background of virtual studio, this paper proposed a real-time video matting algorithm based on chroma key. The algorithm used morphology operations to process the edge of matting images effectively, practiced in situational teaching system. It satisfies the real-time requirement on the premise of quality assuran
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YANG, YUXIANG, and ZENGFU WANG. "AN APPLICATION OF MATTING LAPLACIAN MATRIX TO RANGE IMAGE SUPER-RESOLUTION." International Journal of Information Acquisition 08, no. 04 (2011): 273–80. http://dx.doi.org/10.1142/s0219878911002513.

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This paper describes a successful application of Matting Laplacian Matrix to the problem of generating high-resolution range images. The Matting Laplacian Matrix in this paper exploits the fact that discontinuities in range and coloring tend to co-align, which enables us to generate high-resolution range image by integrating regular camera image into the range data. Using one registered and potentially high-resolution camera image as reference, we iteratively refine the input low-resolution range image, in terms of both spatial resolution and depth precision. We show that by using such a Matti
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