{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:28:41Z","timestamp":1740122921251,"version":"3.37.3"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2020,10,29]],"date-time":"2020-10-29T00:00:00Z","timestamp":1603929600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,10,29]],"date-time":"2020-10-29T00:00:00Z","timestamp":1603929600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Science Foundation of Hubei","award":["2014CFB764"],"award-info":[{"award-number":["2014CFB764"]}]},{"name":"Department of Education of the Hubei Province of China","award":["Q20131608"],"award-info":[{"award-number":["Q20131608"]}]},{"name":"Engineering Research Center of Hubei Province for Clothing Information. Xiao Qin\u2019s work is supported by the U.S. National Science Foundation","award":["IIS-1618669; OAC-1642133;CCF0845257 (CAREER)"],"award-info":[{"award-number":["IIS-1618669; OAC-1642133;CCF0845257 (CAREER)"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,2]]},"DOI":"10.1007\/s11042-020-10085-3","type":"journal-article","created":{"date-parts":[[2020,10,29]],"date-time":"2020-10-29T17:14:35Z","timestamp":1603991675000},"page":"7567-7580","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A textile fabric classification framework through small motions in videos"],"prefix":"10.1007","volume":"80","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8466-6085","authenticated-orcid":false,"given":"Tao","family":"Peng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianzi","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junping","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinrong","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changnian","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhonghua","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Di","family":"Peng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,29]]},"reference":[{"key":"10085_CR1","unstructured":"Abadi M, Barham P, Chen J, et al. (2016) TensorFlow: A system for large-scale machine learning [J].:1\u201318"},{"key":"10085_CR2","doi-asserted-by":"crossref","unstructured":"Aliaga C, O\u2019Sullivan C, Gutierrez D, Tamstorf R (2015) Sackcloth or silk?: the impact of appearance vs dynamics on the perception of animated cloth. In Proceedings of the ACM SIGGRAPH symposium on applied perception, pages 41\u201346. ACM","DOI":"10.1145\/2804408.2804412"},{"key":"10085_CR3","doi-asserted-by":"crossref","unstructured":"Bouman KL, Xiao B, Battaglia P, and Freeman WT (2013) Estimating the material properties of fabric from video. In Proceedings of the IEEE international conference on computer vision, pages 1984\u20131991.","DOI":"10.1109\/ICCV.2013.455"},{"key":"10085_CR4","unstructured":"Chowdhary CL and Acharjya DP (2015) Segmentation of Mammograms using a Novel Intuitionistic Possibilistic Fuzzy C-Mean Clustering Algorithm, 50th Annual Golden Jubilee Convention of the Computer Society of India (CSI-2015), 2nd-5th December, Springer, AISC Vol. 652, pp. 75\u201382"},{"issue":"2","key":"10085_CR5","doi-asserted-by":"publisher","first-page":"38","DOI":"10.4018\/IJHISI.2016040103","volume":"11","author":"CL Chowdhary","year":"2016","unstructured":"Chowdhary CL, Acharjya DP (2016) A Hybrid Scheme for Breast Cancer Detection using Intuitionistic Fuzzy Rough Set Technique. Int J Healthcare Inform Syst Inform, IGI Global 11(2):38\u201361","journal-title":"Int J Healthcare Inform Syst Inform, IGI Global"},{"key":"10085_CR6","unstructured":"Chowdhary CL and Acharjya DP (2017) Clustering Algorithm in Possibilistic Exponential Fuzzy C-Mean Segmenting Medical Images, Journal of Biomimetics, Biomaterials and Biomedical Engineering, Vol. 30, pp. 12\u201323"},{"key":"10085_CR7","unstructured":"Chowdhary CL, Acharjya DP (2020) Segmentation and Feature Extraction in Medical Imaging: A Systematic Review, International Conference on Computational Intelligence and Data Science (ICCIDS 2019), Procedia Computer Science, Elsevier, Vol. 167, pp. 26\u201336"},{"key":"10085_CR8","unstructured":"Chowdhary CL, Sai GVK, Acharjya DP (2016) Decrease in False Assumption for Detection using Digital Mammography, International Conference on Computational Intelligence in Data Mining (ICCIDM-2015), December 5\u20136, 2015, Bhubaneswar, India, Springer, pp. 325\u2013333"},{"key":"10085_CR9","unstructured":"Chung J, Ahn S, Bengio Y (2016) Hierarchical Multiscale Recurrent Neural Networks[J]"},{"issue":"2","key":"10085_CR10","first-page":"3","volume":"1","author":"J Dai","year":"2017","unstructured":"Dai J, Qi H, Xiong Y, Li Y, Zhang G, Hu H, Wei Y (2017) Deformable convolutional networks. CoRR, abs\/1703.06211 1(2):3","journal-title":"CoRR, abs\/1703.06211"},{"key":"10085_CR11","doi-asserted-by":"crossref","unstructured":"Davis A, Bouman KL, Chen JG, Rubinstein M, Durand F, and Freeman WT (2015) Visual vibrometry: Estimating material properties from small motion in video. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 5335\u20135343","DOI":"10.1109\/CVPR.2015.7299171"},{"key":"10085_CR12","doi-asserted-by":"crossref","unstructured":"Deng J, Dong W, Socher R, Li LJ, Li K,Fei-Fei L (2009) Imagenet:A large-scale hierarchical image database. In Computer Vision and Pattern Recognition, 2009. IEEE conference on, pages 248\u2013255","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"10085_CR13","doi-asserted-by":"crossref","unstructured":"Donahue J, Hendricks LA, Guadarrama S, Rohrbach M, Venugopalan S, Saenko K, Darrell T (2015) Long-term recurrent convolutional networks for visual recognition and description. In Proceedings of the IEEE conference on computer vision and pattern recognition. :2625\u20132634","DOI":"10.1109\/CVPR.2015.7298878"},{"issue":"3","key":"10085_CR14","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1177\/004051759806800305","volume":"68","author":"KC Fan","year":"1998","unstructured":"Fan KC, Wang YK, Chang BL, Wang TP, Jou CH, Kao IF (1998) Fabric classification based on recognition using a neural network and dimensionality reduction[J]. Text Res J 68(3):179\u2013185","journal-title":"Text Res J"},{"issue":"5","key":"10085_CR15","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1167\/3.5.3","volume":"3","author":"RW Fleming","year":"2003","unstructured":"Fleming RW, Dror RO, Adelson EH (2003) Real-world illumination and the perception of surface reflectance properties. J Vision 3(5):3\u20133","journal-title":"J Vision"},{"key":"10085_CR16","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"issue":"5","key":"10085_CR17","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1167\/6.5.8","volume":"6","author":"Y-X Ho","year":"2006","unstructured":"Ho Y-X, Landy MS, Maloney LT (2006) How direction of illumination affects visually perceived surface roughness. J Vision 6(5):8\u20138","journal-title":"J Vision"},{"issue":"1","key":"10085_CR18","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1109\/TPAMI.2012.59","volume":"35","author":"S Ji","year":"2013","unstructured":"Ji S, Xu W, Yang M, Yu K (2013) 3d convolutional neural networks for human action recognition. IEEE Trans Pattern Anal Mach Intell 35(1):221\u2013231","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"5","key":"10085_CR19","doi-asserted-by":"publisher","first-page":"1092","DOI":"10.1007\/s12221-014-1092-0","volume":"15","author":"J Jing","year":"2014","unstructured":"Jing J, Xu M, Li P, Li Q, Liu S (2014) Automatic classification of woven fabric structure based on texture feature and PNN[J]. Fibers Polymers 15(5):1092\u20131098","journal-title":"Fibers Polymers"},{"key":"10085_CR20","unstructured":"Jueliang H (2004) Research on the classification of fabrics based on Bayesian method [J]. Textile J, (01):47\u201348+4."},{"key":"10085_CR21","doi-asserted-by":"crossref","unstructured":"Grigorios Kalliatakis, Georgios Stamatiadis, Shoaib Ehsan, Ales Leonardis, Juergen Gall, Anca Sticlaru, and Klaus D McDonald-Maier (2017) Evaluating deep convolutional neural networks for material classification. arXiv preprint arXiv:1703.04101","DOI":"10.5220\/0006166603460352"},{"key":"10085_CR22","doi-asserted-by":"crossref","unstructured":"Karpathy A, Toderici G, Shetty S, Leung T, Sukthankar R, Fei-Fei L (2014) Large-scale video classification with convolutional neural networks. In Proceedings of the IEEE conference on Computer Vision and Pattern Recognition, pages 1725\u20131732","DOI":"10.1109\/CVPR.2014.223"},{"issue":"20","key":"10085_CR23","doi-asserted-by":"publisher","first-page":"2144","DOI":"10.1177\/0040517510373630","volume":"80","author":"C-FJ Kuo","year":"2010","unstructured":"Kuo C-FJ, Shih C-Y, Ho C-E, Peng K-C (2010) Application of computer vision in the automatic identification and classification of woven fabric weave patterns[J]. Textile Res J 80(20):2144\u20132157","journal-title":"Textile Res J"},{"issue":"11","key":"10085_CR24","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun Y, Bottou L\u2019e, Bengio Y, Haffner P (1998) Gradient-based learning applied to document recognition. Proceedings of the IEEE 86(11):2278\u20132324","journal-title":"Proceedings of the IEEE"},{"key":"10085_CR25","doi-asserted-by":"crossref","unstructured":"Liu C, Sharan L, Adelson EH, Rosenholtz R (2010) Exploring features in a Bayesian framework for material recognition. In Computer Vision and Pattern Recognition (CVPR), 2010 IEEE conference on, pages 239\u2013246","DOI":"10.1109\/CVPR.2010.5540207"},{"key":"10085_CR26","unstructured":"Ng JY-H, Hausknecht M, Vijayanarasimhan S, Vinyals O, Monga R, Toderici G (2015) Beyond short snippets: Deep networks for video classification. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 4694\u20134702"},{"issue":"9","key":"10085_CR27","doi-asserted-by":"publisher","first-page":"1360","DOI":"10.1109\/TIP.2005.852470","volume":"14","author":"F Ning","year":"2005","unstructured":"Ning F, Delhomme D, LeCun Y, Piano F, Bottou L\u2019e, Barbano PE (2005) Toward automatic phenotyping of developing embryos from videos. IEEE Trans Image Process 14(9):1360\u20131371","journal-title":"IEEE Trans Image Process"},{"key":"10085_CR28","unstructured":"Sharma S, Kiros R, Salakhutdinov R (2015) Action recognition using visual attention. arXiv preprint arXiv:1511.04119"},{"key":"10085_CR29","unstructured":"Show A 2015 Tell: Neural image caption generation with visual attention. Kelvin Xu et. al. arXiv Pre-Print. 83:89"},{"key":"10085_CR30","unstructured":"Simonyan K, Zisserman A (2014) Two-stream convolutional networks for action recognition in videos. In: Advances in neural information processing systems, pages 568\u2013576"},{"issue":"9","key":"10085_CR31","doi-asserted-by":"publisher","first-page":"902","DOI":"10.1177\/0040517510391702","volume":"81","author":"J Sun","year":"2011","unstructured":"Sun J, Yao M, Xu B et al (2011) Fabric wrinkle characterization and classification using modified wavelet coefficients and support-vector-machine classifiers[J]. Text Res J 81(9):902\u2013913","journal-title":"Text Res J"},{"key":"10085_CR32","unstructured":"Sutskever I, Martens J, Dahl G, Hinton G (2013) On the importance of initialization and momentum in deep learning. In: International conference on machine learning:1139\u20131147"},{"key":"10085_CR33","doi-asserted-by":"crossref","unstructured":"Szegedy C, Vanhoucke V, Ioffe S, Shlens J, Wojna Z (2016) Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pages 2818\u20132826","DOI":"10.1109\/CVPR.2016.308"},{"key":"10085_CR34","doi-asserted-by":"crossref","unstructured":"Tran D, Bourdev L, Fergus R, Torresani L, and Paluri M (2015) Learning spatiotemporal features with 3d convolutional networks. In: Proceedings of the IEEE international conference on computer vision, pages 4489\u20134497,","DOI":"10.1109\/ICCV.2015.510"},{"key":"10085_CR35","doi-asserted-by":"crossref","unstructured":"Vinit Bodhwani DP Acharjya U (2019) Bodhwani: deep residual networks for plant identification, international conference on pervasive computing advances and applications (PerCAA-2019), Procedia computer science, Elsevier, 152: 86\u2013194","DOI":"10.1016\/j.procs.2019.05.042"},{"key":"10085_CR36","doi-asserted-by":"crossref","unstructured":"Wang L, Xiong Y, Wang Z, Yu Q, Lin D, Tang X, Van Gool L (2016) Temporal segment networks: Towards good practices for deep action recognition. In: European Conference on Computer Vision, pages 20\u201336","DOI":"10.1007\/978-3-319-46484-8_2"},{"key":"10085_CR37","unstructured":"Wu Y, He K (2018) Group Normalization[J]. International Journal of Computer Vision, 2018"},{"key":"10085_CR38","doi-asserted-by":"crossref","unstructured":"Wu Z, Wang X, Jiang Y-G, Ye H, Xue X (2015) Modeling spatial-temporal clues in a hybrid deep learning framework for video classification. In: Proceedings of the 23rd ACM international conference on Multimedia, pages 461\u2013470. ACM","DOI":"10.1145\/2733373.2806222"},{"key":"10085_CR39","unstructured":"Xie J, He T, Zhang Z, Zhang H, Zhang Z, Li M (2018) Bag of tricks for image classification with convolutional neural networks. arXiv preprint arXiv:1812.01187"},{"key":"10085_CR40","unstructured":"Yang M, Ji S, Xu W, Wang J, Lv F, Yu K, Gong Y, Dikmen M, Lin DJ, Huang TS 2009Detecting human actions in surveillance videos. In: TREC video retrieval evaluation workshop"},{"key":"10085_CR41","doi-asserted-by":"crossref","unstructured":"Yang S, Liang J, Lin MC (2017) Learning-based cloth material recovery from video. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 4383\u20134393,","DOI":"10.1109\/ICCV.2017.470"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-10085-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-020-10085-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-10085-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,24]],"date-time":"2021-02-24T23:48:20Z","timestamp":1614210500000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-020-10085-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,29]]},"references-count":41,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["10085"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-10085-3","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2020,10,29]]},"assertion":[{"value":"3 December 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 October 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 October 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 October 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}