{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T16:28:05Z","timestamp":1747153685383,"version":"3.40.5"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T00:00:00Z","timestamp":1698364800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T00:00:00Z","timestamp":1698364800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Alma Mater Studiorum - Universit\u00e0 di Bologna"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2024,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>An invisible layer of knowledge is progressively growing with the emergence of situated visualizations and reality-based information retrieval systems. In essence, digital content will overlap with real-world entities, eventually providing insights into the surrounding environment and useful information for the user. The implementation of such a vision may appear close, but many subtle details separate us from its fulfillment. This kind of implementation, as the overlap between rendered virtual annotations and the camera\u2019s real-world view, requires different computer vision paradigms for object recognition and tracking which often require high computing power and large-scale datasets of images. Nevertheless, these resources are not always available, and in some specific domains, the lack of an appropriate reference dataset could be disruptive for a considered task. In this particular scenario, we here consider the problem of wine recognition to support an augmented reading of their labels. In fact, images of wine bottle labels may not be available as wineries periodically change their designs, product information regulations may vary, and specific bottles may be rare, making the label recognition process hard or even impossible. In this work, we present augmented wine recognition, an augmented reality system that exploits optical character recognition paradigms to interpret and exploit the text within a wine label, without requiring any reference image. Our experiments show that such a framework can overcome the limitations posed by image retrieval-based systems while exhibiting a comparable performance.\n<\/jats:p>","DOI":"10.1007\/s00371-023-03119-y","type":"journal-article","created":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T17:01:33Z","timestamp":1698426093000},"page":"5519-5531","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Making paper labels smart for augmented wine recognition"],"prefix":"10.1007","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3572-2076","authenticated-orcid":false,"given":"Alessia","family":"Angeli","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9341-7651","authenticated-orcid":false,"given":"Lorenzo","family":"Stacchio","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6144-5060","authenticated-orcid":false,"given":"Lorenzo","family":"Donatiello","sequence":"additional","affiliation":[]},{"given":"Alessandro","family":"Giacch\u00e8","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3058-8004","authenticated-orcid":false,"given":"Gustavo","family":"Marfia","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"3119_CR1","doi-asserted-by":"publisher","first-page":"396","DOI":"10.1016\/j.protcy.2013.12.208","volume":"11","author":"MZ Bayu","year":"2013","unstructured":"Bayu, M.Z., Arshad, H., Ali, N.M.: Nutritional information visualization using mobile augmented reality technology. Proc. Technol. 11, 396\u2013402 (2013)","journal-title":"Proc. Technol."},{"doi-asserted-by":"crossref","unstructured":"Haugstvedt, A.-C., Krogstie, J.: Mobile augmented reality for cultural heritage: a technology acceptance study. In: 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), pp. 247\u2013255 (2012). IEEE","key":"3119_CR2","DOI":"10.1109\/ISMAR.2012.6402563"},{"key":"3119_CR3","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1007\/978-3-319-28231-2_44","volume-title":"Information and Communication Technologies in Tourism 2016","author":"F Tscheu","year":"2016","unstructured":"Tscheu, F., Buhalis, D.: Augmented reality at cultural heritage sites. In: Inversini, A., Schegg, R. (eds.) Information and Communication Technologies in Tourism 2016, pp. 607\u2013619. Springer, Cham (2016)"},{"doi-asserted-by":"crossref","unstructured":"Stacchio, L., Hajahmadi, S., Marfia, G.: Preserving family album photos with the hololens 2. In: 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), pp. 643\u2013644 (2021). IEEE","key":"3119_CR4","DOI":"10.1109\/VRW52623.2021.00204"},{"doi-asserted-by":"crossref","unstructured":"B\u00fcschel, W., Mitschick, A., Dachselt, R.: Here and now: reality-based information retrieval: perspective paper. In: Proceedings of the 2018 Conference on Human Information Interaction & Retrieval, pp. 171\u2013180 (2018)","key":"3119_CR5","DOI":"10.1145\/3170427.3186493"},{"issue":"1","key":"3119_CR6","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1109\/TVCG.2021.3114835","volume":"28","author":"N Bressa","year":"2021","unstructured":"Bressa, N., Korsgaard, H., Tabard, A., Houben, S., Vermeulen, J.: What\u2019s the situation with situated visualization? A survey and perspectives on situatedness. IEEE Trans. Vis. Comput. Gr. 28(1), 107\u2013117 (2021)","journal-title":"IEEE Trans. Vis. Comput. Gr."},{"issue":"11","key":"3119_CR7","doi-asserted-by":"publisher","first-page":"14749","DOI":"10.1007\/s11042-021-10971-4","volume":"81","author":"NC Martins","year":"2022","unstructured":"Martins, N.C., Marques, B., Alves, J., Ara\u00fajo, T., Dias, P., Santos, B.S.: Augmented reality situated visualization in decision-making. Multimed. Tools Appl. 81(11), 14749\u201314772 (2022)","journal-title":"Multimed. Tools Appl."},{"issue":"7","key":"3119_CR8","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1145\/159544.159566","volume":"36","author":"GW Fitzmaurice","year":"1993","unstructured":"Fitzmaurice, G.W.: Situated information spaces and spatially aware palmtop computers. Commun. ACM 36(7), 39\u201349 (1993)","journal-title":"Commun. ACM"},{"key":"3119_CR9","volume-title":"Augmented Reality Enhanced Cooking with Microsoft Hololens","author":"A Orsini","year":"2017","unstructured":"Orsini, A., Venkatesan, G., Huang, G., Shah, G., Shah, N.: Augmented Reality Enhanced Cooking with Microsoft Hololens. State University of New Jersey, Rutgers (2017)"},{"issue":"4","key":"3119_CR10","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1080\/15378020.2020.1859973","volume":"24","author":"A Rejeb","year":"2021","unstructured":"Rejeb, A., Rejeb, K., Keogh, J.G.: Enablers of augmented reality in the food supply chain: a systematic literature review. J. Foodserv. Bus. Res. 24(4), 415\u2013444 (2021)","journal-title":"J. Foodserv. Bus. Res."},{"issue":"4","key":"3119_CR11","doi-asserted-by":"publisher","first-page":"216","DOI":"10.3390\/digital1040016","volume":"1","author":"GD Styliaras","year":"2021","unstructured":"Styliaras, G.D.: Augmented reality in food promotion and analysis: review and potentials. Digital 1(4), 216\u2013240 (2021)","journal-title":"Digital"},{"unstructured":"Yuka: Yuka. https:\/\/yuka.io\/it\/ (2021)","key":"3119_CR12"},{"unstructured":"Vivino: Vivino. https:\/\/www.vivino.com\/ (2021)","key":"3119_CR13"},{"doi-asserted-by":"crossref","unstructured":"Vrigkas, M., Lappas, G., Kleftodimos, A., Triantafillidou, A.: Augmented reality for wine industry: past, present, and future. In: SHS Web of Conferences, vol. 102, p. 04006 (2021). EDP Sciences","key":"3119_CR14","DOI":"10.1051\/shsconf\/202110204006"},{"doi-asserted-by":"crossref","unstructured":"Sonderegger, A., Ribes, D., Henchoz, N., Groves, E.: Food talks: visual and interaction principles for representing environmental and nutritional food information in augmented reality. In: 2019 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), pp. 98\u2013103 (2019). IEEE","key":"3119_CR15","DOI":"10.1109\/ISMAR-Adjunct.2019.00040"},{"issue":"4","key":"3119_CR16","doi-asserted-by":"publisher","first-page":"43","DOI":"10.2753\/MIS0742-1222270402","volume":"27","author":"O Hinz","year":"2011","unstructured":"Hinz, O., Eckert, J., Skiera, B.: Drivers of the long tail phenomenon: an empirical analysis. J. Manag. Inf. Syst. 27(4), 43\u201370 (2011)","journal-title":"J. Manag. Inf. Syst."},{"key":"3119_CR17","first-page":"31","volume":"22","author":"S Stricker","year":"2007","unstructured":"Stricker, S., Mueller, R.A., Sumner, D.A.: Marketing wine on the web. Choices 22, 31\u201334 (2007)","journal-title":"Choices"},{"issue":"2","key":"3119_CR18","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1007\/s40797-021-00145-4","volume":"7","author":"JM Alston","year":"2021","unstructured":"Alston, J.M., Gaeta, D.: Reflections on the political economy of European wine appellations. Ital. Econ. J. 7(2), 219\u2013258 (2021)","journal-title":"Ital. Econ. J."},{"doi-asserted-by":"publisher","unstructured":"Breuel, T.M.: High performance text recognition using a hybrid convolutional-lstm implementation. In: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), vol. 01, pp. 11\u201316 (2017). https:\/\/doi.org\/10.1109\/ICDAR.2017.12","key":"3119_CR19","DOI":"10.1109\/ICDAR.2017.12"},{"unstructured":"Wick, C., Reul, C., Puppe, F.: Calamari-a high-performance tensorflow-based deep learning package for optical character recognition. arXiv preprint arXiv:1807.02004 (2018)","key":"3119_CR20"},{"issue":"3","key":"3119_CR21","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1080\/09571269908718177","volume":"10","author":"S Charters","year":"1999","unstructured":"Charters, S., Lockshin, L., Unwin, T.: Consumer responses to wine bottle back labels. J. Wine Res. 10(3), 183\u2013195 (1999)","journal-title":"J. Wine Res."},{"doi-asserted-by":"crossref","unstructured":"Stacchio, L., Angeli, A., Donatiello, L., Giacch\u00e8, A., Marfia, G.: Rethinking augmented wine recognition. In: 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), pp. 1\u20136 (2022). IEEE, to appear","key":"3119_CR22","DOI":"10.1109\/ISMAR-Adjunct57072.2022.00117"},{"issue":"4","key":"3119_CR23","doi-asserted-by":"publisher","first-page":"1179","DOI":"10.1007\/s10997-020-09526-w","volume":"25","author":"L Penco","year":"2021","unstructured":"Penco, L., Serravalle, F., Profumo, G., Viassone, M.: Mobile augmented reality as an internationalization tool in the \u201cmade in Italy\u2019\u2019 food and beverage industry. J. Manage. Governance 25(4), 1179\u20131209 (2021)","journal-title":"J. Manage. Governance"},{"key":"3119_CR24","first-page":"012014","volume":"1963","author":"NO Salim","year":"2021","unstructured":"Salim, N.O., Zeebaree, S.R., Sadeeq, M.A., Radie, A., Shukur, H.M., Rashid, Z.N.: Study for food recognition system using deep learning. J. Phys: Conf. Ser. 1963, 012014 (2021)","journal-title":"J. Phys: Conf. Ser."},{"doi-asserted-by":"crossref","unstructured":"Gundimeda, V., Murali, R.S., Joseph, R., Babu, N.N.: An automated computer vision system for extraction of retail food product metadata. In: First International Conference on Artificial Intelligence and Cognitive Computing, pp. 199\u2013216 (2019). Springer","key":"3119_CR25","DOI":"10.1007\/978-981-13-1580-0_20"},{"key":"3119_CR26","doi-asserted-by":"publisher","first-page":"19336","DOI":"10.1109\/ACCESS.2020.2967090","volume":"8","author":"B Hu","year":"2020","unstructured":"Hu, B., Zhou, N., Zhou, Q., Wang, X., Liu, W.: Diffnet: a learning to compare deep network for product recognition. IEEE Access 8, 19336\u201319344 (2020)","journal-title":"IEEE Access"},{"doi-asserted-by":"crossref","unstructured":"Lin, M., Ma, L., Yu, B.: An efficient and light-weight detector for wine bottle defects. In: 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV), pp. 957\u2013962 (2020). IEEE","key":"3119_CR27","DOI":"10.1109\/ICARCV50220.2020.9305489"},{"key":"3119_CR28","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1016\/j.crfs.2021.03.009","volume":"4","author":"L Zhu","year":"2021","unstructured":"Zhu, L., Spachos, P., Pensini, E., Plataniotis, K.N.: Deep learning and machine vision for food processing: a survey. Curr. Res. Food Sci. 4, 233\u2013249 (2021)","journal-title":"Curr. Res. Food Sci."},{"unstructured":"TinEye: WineEngine is image recognition for the beverage industry. https:\/\/services.tineye.com\/WineEngine (2021)","key":"3119_CR29"},{"unstructured":"livingwinelabels: livingwinelabels. https:\/\/www.livingwinelabels.com\/ (2021)","key":"3119_CR30"},{"unstructured":"PTC: Vivino and Vuforia\u2019s Image Recognition Solution Make a Great Pairing. https:\/\/www.ptc.com\/en\/case-studies\/vivino (2022)","key":"3119_CR31"},{"unstructured":"Gebru, T., Hazi, O., Yeh, V.: Mobile wine label recognition (2022)","key":"3119_CR32"},{"issue":"4","key":"3119_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5392\/IJoC.2014.10.4.001","volume":"10","author":"IS Na","year":"2014","unstructured":"Na, I.S., Chen, Y.J., Kim, S.H.: Automatic segmentation of product bottle label based on grabcut algorithm. Int. J. Contents 10(4), 1\u201310 (2014)","journal-title":"Int. J. Contents"},{"doi-asserted-by":"crossref","unstructured":"Wu, M.-Y., Lee, J.-H., Kuo, S.-W.: A hierarchical feature search method for wine label image recognition. In: 2015 38th International Conference on Telecommunications and Signal Processing (TSP), pp. 568\u2013572 (2015). IEEE","key":"3119_CR34","DOI":"10.1109\/TSP.2015.7296327"},{"doi-asserted-by":"crossref","unstructured":"\u010caki\u0107, S., Popovi\u0107, T., \u0160andi, S., Kr\u010do, S., Gazivoda, A.: The use of tesseract ocr number recognition for food tracking and tracing. In: 2020 24th International Conference on Information Technology (IT), pp. 1\u20134 (2020). IEEE","key":"3119_CR35","DOI":"10.1109\/IT48810.2020.9070558"},{"issue":"5","key":"3119_CR36","doi-asserted-by":"publisher","first-page":"125","DOI":"10.5392\/JKCA.2011.11.5.125","volume":"11","author":"J-M Jung","year":"2011","unstructured":"Jung, J.-M., Yang, H.-J., Kim, S.-H., Lee, G.-S., Kim, S.-H.: Wine label recognition system using image similarity. J. Korea Contents Assoc. 11(5), 125\u2013137 (2011)","journal-title":"J. Korea Contents Assoc."},{"unstructured":"\u00c1lvarez\u00a0M\u00e1rquez, J.O., Ziegler, J.: Improving the shopping experience with an augmented reality-enhanced shelf. Mensch und Computer 2017-Workshopband (2017)","key":"3119_CR37"},{"doi-asserted-by":"crossref","unstructured":"Li, X., Yang, J., Ma, J.: Cnn-sift consecutive searching and matching for wine label retrieval. In: International Conference on Intelligent Computing, pp. 250\u2013261 (2019). Springer","key":"3119_CR38","DOI":"10.1007\/978-3-030-26763-6_24"},{"unstructured":"Vuforia: Vuforia SDK. https:\/\/developer.vuforia.com\/downloads\/SDK (2022)","key":"3119_CR39"},{"unstructured":"Camera di Commercio Molise: Guida etichettature vino. https:\/\/www.molise.camcom.gov.it\/sites\/default\/files\/guida_etichettatura_vino.pdf (2016)","key":"3119_CR40"},{"unstructured":"Michele A. Fino: Questione di Etichetta. https:\/\/www.spazioprever.it\/salabar\/vino\/pdf\/Questione_di_etichetta.pdf (2013)","key":"3119_CR41"},{"unstructured":"Vittorio Portinari: Elementi di Legislazione Vitivinicola: le norme per l\u2019etichettatura e la tracciabilit\u00e0 dei vini. http:\/\/www.sardegnaagricoltura.it\/documenti\/14_43_20160531144229.pdf (2016)","key":"3119_CR42"},{"unstructured":"FEDERDOC: I VINI ITALIANI A DENOMINAZIONE D\u2019ORIGINE 2020. https:\/\/www.federdoc.com\/new\/wp-content\/uploads\/2020\/06\/vini_italiani_denominazione_origine_2020.pdf (2021)","key":"3119_CR43"},{"doi-asserted-by":"publisher","unstructured":"Bansal, R., Raj, G., Choudhury, T.: Blur image detection using laplacian operator and open-cv. In: 2016 International Conference System Modeling Advancement in Research Trends (SMART), pp. 63\u201367 (2016). https:\/\/doi.org\/10.1109\/SYSMART.2016.7894491","key":"3119_CR44","DOI":"10.1109\/SYSMART.2016.7894491"},{"issue":"3","key":"3119_CR45","doi-asserted-by":"publisher","first-page":"314","DOI":"10.7763\/IJMLC.2012.V2.137","volume":"2","author":"A Singh","year":"2012","unstructured":"Singh, A., Bacchuwar, K., Bhasin, A.: A survey of OCR applications. Int. J. Mach. Learn. Comput. 2(3), 314 (2012)","journal-title":"Int. J. Mach. Learn. Comput."},{"unstructured":"Easy Ocr: JadedAI. https:\/\/github.com\/JaidedAI\/EasyOCR (2021)","key":"3119_CR46"},{"doi-asserted-by":"crossref","unstructured":"Baek, Y., Lee, B., Han, D., Yun, S., Lee, H.: Character region awareness for text detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9365\u20139374 (2019)","key":"3119_CR47","DOI":"10.1109\/CVPR.2019.00959"},{"issue":"11","key":"3119_CR48","doi-asserted-by":"publisher","first-page":"2298","DOI":"10.1109\/TPAMI.2016.2646371","volume":"39","author":"B Shi","year":"2016","unstructured":"Shi, B., Bai, X., Yao, C.: An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition. IEEE Trans. Pattern Anal. Mach. Intell. 39(11), 2298\u20132304 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"doi-asserted-by":"crossref","unstructured":"Baek, J., Kim, G., Lee, J., Park, S., Han, D., Yun, S., Oh, S.J., Lee, H.: What is wrong with scene text recognition model comparisons? Dataset and model analysis. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4715\u20134723 (2019)","key":"3119_CR49","DOI":"10.1109\/ICCV.2019.00481"},{"doi-asserted-by":"crossref","unstructured":"Graves, A., Fern\u00e1ndez, S., Gomez, F., Schmidhuber, J.: Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks. In: Proceedings of the 23rd International Conference on Machine Learning, pp. 369\u2013376 (2006)","key":"3119_CR50","DOI":"10.1145\/1143844.1143891"},{"unstructured":"Smelyakov, K., Chupryna, A., Darahan, D., Midina, S.: Effectiveness of modern text recognition solutions and tools for common data sources. In: CEUR Workshop Proceedings, pp. 154\u2013165 (2021)","key":"3119_CR51"},{"unstructured":"Levenshtein, V.I., : Binary codes capable of correcting deletions, insertions, and reversals. In: Soviet Physics Doklady, vol. 10, pp. 707\u2013710 (1966). Soviet Union","key":"3119_CR52"},{"key":"3119_CR53","doi-asserted-by":"publisher","first-page":"113609","DOI":"10.1016\/j.cma.2020.113609","volume":"376","author":"L Abualigah","year":"2021","unstructured":"Abualigah, L., Diabat, A., Mirjalili, S., Abd Elaziz, M., Gandomi, A.H.: The arithmetic optimization algorithm. Comput. Methods Appl. Mech. Eng. 376, 113609 (2021)","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"3119_CR54","doi-asserted-by":"publisher","first-page":"107250","DOI":"10.1016\/j.cie.2021.107250","volume":"157","author":"L Abualigah","year":"2021","unstructured":"Abualigah, L., Yousri, D., Abd Elaziz, M., Ewees, A.A., Al-Qaness, M.A., Gandomi, A.H.: Aquila optimizer: a novel meta-heuristic optimization algorithm. Comput. Ind. Eng. 157, 107250 (2021)","journal-title":"Comput. Ind. Eng."},{"doi-asserted-by":"crossref","unstructured":"Abualigah, L., Abd Elaziz, M., Sumari, P., Geem, Z.W., Gandomi, A.H.: Reptile search algorithm (RSA): s nature-inspired meta-heuristic optimizer. Expert Syst. Appl. 191, 116158 (2022)","key":"3119_CR55","DOI":"10.1016\/j.eswa.2021.116158"},{"doi-asserted-by":"crossref","unstructured":"Oyelade, O.N., Ezugwu, A.E.-S., Mohamed, T.I., Abualigah, L.: Ebola optimization search algorithm: a new nature-inspired metaheuristic optimization algorithm. IEEE Access 10, 16150\u201316177 (2022)","key":"3119_CR56","DOI":"10.1109\/ACCESS.2022.3147821"},{"key":"3119_CR57","doi-asserted-by":"publisher","first-page":"114570","DOI":"10.1016\/j.cma.2022.114570","volume":"391","author":"JO Agushaka","year":"2022","unstructured":"Agushaka, J.O., Ezugwu, A.E., Abualigah, L.: Dwarf mongoose optimization algorithm. Comput. Methods Appl. Mech. Eng. 391, 114570 (2022)","journal-title":"Comput. Methods Appl. Mech. Eng."},{"issue":"22","key":"3119_CR58","doi-asserted-by":"publisher","first-page":"20017","DOI":"10.1007\/s00521-022-07530-9","volume":"34","author":"AE Ezugwu","year":"2022","unstructured":"Ezugwu, A.E., Agushaka, J.O., Abualigah, L., Mirjalili, S., Gandomi, A.H.: Prairie dog optimization algorithm. Neural Comput. Appl. 34(22), 20017\u201320065 (2022)","journal-title":"Neural Comput. Appl."},{"issue":"2","key":"3119_CR59","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1080\/02664769823151","volume":"25","author":"CA Glasbey","year":"1998","unstructured":"Glasbey, C.A., Mardia, K.V.: A review of image-warping methods. J. Appl. Stat. 25(2), 155\u2013171 (1998)","journal-title":"J. Appl. Stat."},{"doi-asserted-by":"crossref","unstructured":"Zhan, F., Lu, S.: Esir: End-to-end scene text recognition via iterative image rectification. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2059\u20132068 (2019)","key":"3119_CR60","DOI":"10.1109\/CVPR.2019.00216"},{"key":"3119_CR61","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1007\/978-3-030-12939-2_25","volume-title":"Pattern Recognition","author":"P Follmann","year":"2019","unstructured":"Follmann, P., Drost, B., B\u00f6ttger, T.: Acquire, augment, segment and enjoy: weakly supervised instance segmentation of supermarket products. In: Brox, T., Bruhn, A., Fritz, M. (eds.) Pattern Recognition, pp. 363\u2013376. Springer, Cham (2019)"},{"doi-asserted-by":"crossref","unstructured":"Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A.C., Lo, W.-Y., et al.: Segment anything. arXiv preprint arXiv:2304.02643 (2023)","key":"3119_CR62","DOI":"10.1109\/ICCV51070.2023.00371"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-023-03119-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-023-03119-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-023-03119-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T13:33:30Z","timestamp":1721828010000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-023-03119-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,27]]},"references-count":62,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["3119"],"URL":"https:\/\/doi.org\/10.1007\/s00371-023-03119-y","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"type":"print","value":"0178-2789"},{"type":"electronic","value":"1432-2315"}],"subject":[],"published":{"date-parts":[[2023,10,27]]},"assertion":[{"value":"9 September 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 October 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declaration"}},{"value":"We hereby declare that we have no conflicts of interest that could be perceived as influencing the integrity or objectivity of our research work.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}