The application of image analysis technology in the extraction of human body feature parameters
With the improvement of living standards, personalized clothing customization has become a trend of people’s apparel demand. The key factor in personalized clothing customization is a three-dimensional human modeling. With the development of image analysis technology, it is possible to use image ana...
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| Published in: | EURASIP journal on image and video processing Vol. 2018; no. 1; pp. 1 - 10 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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Springer International Publishing
30.10.2018
Springer Nature B.V SpringerOpen |
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| ISSN: | 1687-5281, 1687-5176, 1687-5281 |
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| Abstract | With the improvement of living standards, personalized clothing customization has become a trend of people’s apparel demand. The key factor in personalized clothing customization is a three-dimensional human modeling. With the development of image analysis technology, it is possible to use image analysis technology to extract human characteristics. In this paper, two-dimensional human feature regions and characteristic parameter extraction methods of images are used. The backpropagation neural network (BP neural network) is used to curve the three-dimensional human characteristics, and the neck, chest, waist, and buttocks of 22 subjects are verified. The results show that the use of this method can well achieve the extraction of human characteristic parameters. |
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| AbstractList | Abstract With the improvement of living standards, personalized clothing customization has become a trend of people’s apparel demand. The key factor in personalized clothing customization is a three-dimensional human modeling. With the development of image analysis technology, it is possible to use image analysis technology to extract human characteristics. In this paper, two-dimensional human feature regions and characteristic parameter extraction methods of images are used. The backpropagation neural network (BP neural network) is used to curve the three-dimensional human characteristics, and the neck, chest, waist, and buttocks of 22 subjects are verified. The results show that the use of this method can well achieve the extraction of human characteristic parameters. With the improvement of living standards, personalized clothing customization has become a trend of people’s apparel demand. The key factor in personalized clothing customization is a three-dimensional human modeling. With the development of image analysis technology, it is possible to use image analysis technology to extract human characteristics. In this paper, two-dimensional human feature regions and characteristic parameter extraction methods of images are used. The backpropagation neural network (BP neural network) is used to curve the three-dimensional human characteristics, and the neck, chest, waist, and buttocks of 22 subjects are verified. The results show that the use of this method can well achieve the extraction of human characteristic parameters. |
| ArticleNumber | 116 |
| Author | Wei, Pengcheng Li, Li Jiang, Jiao |
| Author_xml | – sequence: 1 givenname: Pengcheng surname: Wei fullname: Wei, Pengcheng email: m13942692615@163.com organization: School of Mathematics and Information Engineering, Chongqing University of Education – sequence: 2 givenname: Jiao surname: Jiang fullname: Jiang, Jiao organization: School of Automation, Chongqing University of Posts and Telecommunications – sequence: 3 givenname: Li surname: Li fullname: Li, Li organization: School of Mathematics and Information Engineering, Chongqing University of Education |
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| Copyright | The Author(s). 2018 EURASIP Journal on Image and Video Processing is a copyright of Springer, (2018). All Rights Reserved. © 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| Keywords | Feature extraction Image analysis BP neural network Human characteristics Computer-aided design (CAD) |
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| References_xml | – reference: HuangCLuximonAYeungKFunctional 3D human model design: a pilot study based on surface anthropometry and infrared thermography[J]Computer-Aided Design and Applications201512447548410.1080/16864360.2014.997644 – reference: X.J. Zhu, X.Y. Xiong, Human body shapes modeling and feature points location based on ASM for virtual fitting[C]//Sixth International Conference on Information Science and Technology. IEEE, 476–481 (2016) – reference: Yan-NiMAGengGHZhouMQLocalization and extraction for feature points of human faces[J]Computer Engineering & Applications20094518167170 – reference: L.I. Ru-Ping, L. Zhu, W.U. Fang-Shen, et al., BP neural network algorithm improvement and application research[J]. Journal of Heze University (2016) – reference: MihalikJKasarMShaping of Geometry of 3D Human Head Model[C]//Radioelektronika, 2007. International Conference. IEEE200714 – reference: T. Kim, K.H. Jo, S.E. Kim, et al., Recognition of free gymnastics using human body feature points from silhouette and skin region[C]//The, Russian-Korean International Symposium on Science and Technology, 2002. Korus-2002. Proceedings. IEEE, 150–154 (2002) – reference: TangJLiuXChengHGender recognition with limited feature points from 3-D human body shapes[J]201224812484 – reference: S. Sakamoto, Extracting feature points on human eye photographs[J]. Proc Miru 76, 461-464 (1993) – reference: ParkerDTaylorCAWangKImaged based 3D solid model construction of human arteries for blood flow simulations[C]//Engineering in Medicine and Biology Society, 1998. Proceedings of the International Conference of the IEEEIEEE199829981001 – reference: SakamotoSMiyaoYTajimaJExtracting Feature Points on Human Eye Photographs.[C]//Iapr Workshop on Machine Vision Applications, Mva 1992, December December 7–9, 19921993Tokyo, JapanDBLP461464 – reference: JinPBianYUDaWMulti-scale symmetry transform with application to location of feature points on human face image[J]Acta Electron. Sin.2002303363366 – reference: WangBGuXMaLTemperature error correction based on BP neural network in meteorological wireless sensor network[J]International Journal of Sensor Networks201623426510.1504/IJSNET.2017.083532 – reference: HuaGUGuang-DaSUChengDUAutomatic localization of the vital feature points on human faces[J]Journal of Optoelectronics Laser2004158975979 – reference: JiangLiminZhangJingjunXuanPingZouQuanBP Neural Network Could Help Improve Pre-miRNA Identification in Various SpeciesBioMed Research International20162016111 – reference: S.U. Xin, H. Pei, W.U. 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| Snippet | With the improvement of living standards, personalized clothing customization has become a trend of people’s apparel demand. The key factor in personalized... Abstract With the improvement of living standards, personalized clothing customization has become a trend of people’s apparel demand. The key factor in... |
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| SubjectTerms | Back propagation Biometrics BP neural network Computer-aided design (CAD) Engineering Feature extraction Human characteristics Image analysis Image Processing and Computer Vision Neural networks Parameters Pattern Recognition Signal,Image and Speech Processing Technology assessment Three dimensional models Visual Information Learning and Analytics on Cross-Media Big Data |
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| Title | The application of image analysis technology in the extraction of human body feature parameters |
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