View source for स्वचालित छवि एनोटेशन

[[File:DenseCap (Johnson et al., 2016) (cropped).png|thumb|upright=1.35|DenseCap डेंस कैप्शनिंग सॉफ़्टवेयर का आउटपुट, हाथी पर सवार एक आदमी की तस्वीर का विश्लेषण करता है]]'''स्वचालित छवि एनोटेशन''' (जिसे '''स्वचालित छवि टैगिंग''' या '''भाषाई अनुक्रमण''' के रूप में भी जाना जाता है) वह प्रक्रिया है जिसके द्वारा एक कंप्यूटर प्रणाली स्वचालित रूप से एक [[डिजिटल छवि]] को [[ चित्र परिचय |कैप्शनिंग]] या कीवर्ड के रूप में [[ मेटा डेटा |मेटा डेटा]] प्रदान करता है। [[कंप्यूटर दृष्टि|कंप्यूटर विज़न]] विधियों के इस एप्लीकेशन का उपयोग किसी [[डेटाबेस]] से महत्त्व की छवियों को व्यवस्थित करने और उनका पता लगाने के लिए [[छवि पुनर्प्राप्ति]] प्रणालियों में किया जाता है।

इस पद्धति को एक प्रकार के बहु-वर्ग [[छवि पहचान]] वर्गीकरण के रूप में माना जा सकता है जिसमें शब्दावली आकार जितनी बड़ी संख्या में कक्षाएं होती हैं। सामान्यतः, निकाले गए [[फ़ीचर वेक्टर]] और प्रशिक्षण एनोटेशन शब्दों के रूप में [[छवि विश्लेषण]] का उपयोग [[ यंत्र अधिगम |मशीन लर्निंग]] विधियों द्वारा नई छवियों पर एनोटेशन को स्वचालित रूप से प्रायुक्त करने का प्रयास करने के लिए किया जाता है। पहले विधियों ने [[फ़ीचर (कंप्यूटर विज़न)]] और प्रशिक्षण एनोटेशन के मध्य सहसंबंधों को सीखा, फिर मशीनी अनुवाद का उपयोग करके विधियों का विकास किया गया जिससे पाठ्य शब्दावली को 'विज़ुअल शब्दावली', या क्लस्टर क्षेत्रों के साथ अनुवाद करने की प्रयास की जा सके जिन्हें ब्लॉब्स के रूप में जाना जाता है। इन प्रयासों के बाद के कार्यों में वर्गीकरण पद्धति, प्रासंगिकता मॉडल इत्यादि सम्मिलित हैं।

स्वचालित छवि एनोटेशन विरुद्ध [[सामग्री-आधारित छवि पुनर्प्राप्ति]] (सीबीआईआर) के लाभ यह हैं कि उपयोगकर्ता द्वारा क्वेरीज़ को अधिक स्वाभाविक रूप से निर्दिष्ट किया जा सकता है।<ref>{{cite web |url=http://i.yz.yamagata-u.ac.jp/paper/inoue04irix.pdf |title=संग्रहीत प्रति|website=i.yz.yamagata-u.ac.jp |access-date=13 January 2022 |archive-url=https://web.archive.org/web/20140808134447/http://i.yz.yamagata-u.ac.jp/paper/inoue04irix.pdf |archive-date=8 August 2014 |url-status=dead}}</ref> सामान्यतः (वर्तमान में) सीबीआईआर को उपयोगकर्ताओं को रंग और [[बनावट (दृश्य कला)]] जैसी छवि अवधारणाओं के आधार पर खोज करने या उदाहरण क्वेरी खोजने की आवश्यकता होती है। उदाहरण छवियों में कुछ छवि विशेषताएं उस अवधारणा को ओवरराइड कर सकती हैं जिस पर उपयोगकर्ता वास्तव में ध्यान केंद्रित कर रहा है। छवि पुनर्प्राप्ति के पारंपरिक विधियाँ, जैसे कि लाइब्रेरी द्वारा उपयोग किए जाने वाले, मैन्युअल रूप से एनोटेटेड छवियों पर निर्भर हैं, जो अस्तित्व में बड़े और निरंतर बढ़ते छवि डेटाबेस को देखते हुए महंगा और समय लेने वाला है।

==यह भी देखें==
*सामग्री-आधारित छवि पुनर्प्राप्ति
*[[छवि खोज से वस्तु वर्गीकरण]]
*[[वस्तु का पता लगाना]]
*[[वस्तु पहचान की रूपरेखा]]

==संदर्भ==
{{Reflist}}
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*{{cite conference|author=Nicolas Hervé |author2=Nozha Boujemaa |url=http://www-rocq.inria.fr/~nherve/nherve_civr2007.pdf |title=Image annotation : which approach for realistic databases ? |book-title=ACM International Conference on Image and Video Retrieval |year=2007 |url-status=dead |archive-url=https://web.archive.org/web/20110520140240/http://www-rocq.inria.fr/~nherve/nherve_civr2007.pdf |archive-date=2011-05-20 }}
*{{cite conference|author=M Inoue |url=http://i.yz.yamagata-u.ac.jp/paper/inoue04irix.pdf |title=On the need for annotation-based image retrieval |book-title=Workshop on Information Retrieval in Context |year=2004 |pages=44–46 |url-status=dead |archive-url=https://web.archive.org/web/20140808134447/http://i.yz.yamagata-u.ac.jp/paper/inoue04irix.pdf |archive-date=2014-08-08 }}


==अग्रिम पठन==
* Word co-occurrence model
:{{cite conference |author1=Y Mori |author2=H Takahashi |author3=R Oka  |name-list-style=amp | title=Image-to-word transformation based on dividing and vector quantizing images with words. | book-title=Proceedings of the International Workshop on Multimedia Intelligent Storage and Retrieval Management | year=1999 |citeseerx=10.1.1.31.1704 }}
* Annotation as machine translation
:{{cite conference|author1=P Duygulu |author2=K Barnard |author3=N de Fretias |author4=D Forsyth |name-list-style=amp |url=http://vision.cs.arizona.edu/kobus/research/publications/ECCV-02-1/ |title=Object recognition as machine translation: Learning a lexicon for a fixed image vocabulary |book-title=Proceedings of the European Conference on Computer Vision |year=2002 |pages=97–112 |url-status=dead |archive-url=https://web.archive.org/web/20050305174408/http://vision.cs.arizona.edu/kobus/research/publications/ECCV-02-1/ |archive-date=2005-03-05 }}
* Statistical models
:{{cite conference |author1=J Li  |author2=J Z Wang  |name-list-style=amp | url=http://www-db.stanford.edu/~wangz/project/imsearch/ALIP/ACMMM06/ | title=Real-time Computerized Annotation of Pictures | book-title=Proc. ACM Multimedia | year=2006 | pages=911–920}}
:{{cite conference |author1=J Z Wang  |author2=J Li  |name-list-style=amp | url=http://www-db.stanford.edu/~wangz/project/imsearch/ALIP/ACM02/ | title=Learning-Based Linguistic Indexing of Pictures with 2-D MHMMs | book-title=Proc. ACM Multimedia | year=2002 | pages=436–445}}
* Automatic linguistic indexing of pictures
:{{cite conference |author1=J Li  |author2=J Z Wang  |name-list-style=amp | url=http://infolab.stanford.edu/~wangz/project/imsearch/ALIP/PAMI08/ | title=Real-time Computerized Annotation of Pictures | book-title=IEEE Transactions on Pattern Analysis and Machine Intelligence | year=2008 }}
:{{cite conference |author1=J Li  |author2=J Z Wang  |name-list-style=amp | url=http://www-db.stanford.edu/~wangz/project/imsearch/ALIP/PAMI03/ | title=Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach | book-title=IEEE Transactions on Pattern Analysis and Machine Intelligence | year=2003 | pages=1075–1088}}

* Hierarchical Aspect Cluster Model
:{{cite conference|author1=K Barnard |author2=D A Forsyth |url=http://kobus.ca/research/publications/ICCV-01/ |title=Learning the Semantics of Words and Pictures |book-title=Proceedings of International Conference on Computer Vision |year=2001 |pages=408–415 |url-status=dead |archive-url=https://web.archive.org/web/20070928161148/http://kobus.ca/research/publications/ICCV-01/ |archive-date=2007-09-28 }}
* Latent Dirichlet Allocation model
:{{cite conference|author1=D Blei |author2=A Ng |author3=M Jordan |name-list-style=amp |url=http://www.ics.uci.edu/~liang/seminars/win05/papers/blei03-latent-dirichlet.pdf |title=Latent Dirichlet allocation |book-title=Journal of Machine Learning Research |year=2003 |pages=3:993–1022 |url-status=dead |archive-url=http://web.archive.bibalex.org/web/20050521213733/http://www.ics.uci.edu/~liang/seminars/win05/papers/blei03-latent-dirichlet.pdf |archive-date=2005-05-21 }}
* [[supervised learning|Supervised]] [[multiclass labeling]]
:{{cite conference |author1=G Carneiro |author2=A B Chan |author3=P Moreno |author4=N Vasconcelos  |name-list-style=amp | url=http://www.svcl.ucsd.edu/publications/journal/2007/pami/pami07-semantics.pdf | title=Supervised Learning of Semantic Classes for Image Annotation and Retrieval| book-title=IEEE Transactions on Pattern Analysis and Machine Intelligence | year=2006 | pages=394–410}}
* Texture similarity
:{{cite conference |author1=R W Picard  |author2=T P Minka  |name-list-style=amp | url=http://citeseer.ist.psu.edu/picard95vision.html | title=Vision Texture for Annotation | book-title=Multimedia Systems | year=1995 }}
* Support Vector Machines
:{{cite journal |author1=C Cusano |author2=G Ciocca |author3=R Scettini  |editor-first1=Simone |editor-first2=Raimondo |editor-last1=Santini |editor-last2=Schettini |name-list-style=amp | title=Image Annotation Using SVM |journal=Internet Imaging V |volume=5304 <!-- | book-title=Proceedings of Internet Imaging IV --> | year=2004 | pages=330–338|bibcode=2003SPIE.5304..330C |doi=10.1117/12.526746 |s2cid=16246057 }}
* Ensemble of Decision Trees and Random Subwindows
:{{cite conference |author1=R Maree |author2=P Geurts |author3=J Piater |author4=L Wehenkel  |name-list-style=amp |
url=http://www.montefiore.ulg.ac.be/~maree/#publications | title=Random Subwindows for Robust Image Classification |
book-title=Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition | year=2005 | pages=1:34–30}}
* Maximum Entropy
:{{cite conference |author1=J Jeon |author2=R Manmatha | url=http://ciir.cs.umass.edu/pubfiles/mm-355.pdf | title=Using Maximum Entropy for Automatic Image Annotation | book-title=Int'l Conf on Image and Video Retrieval (CIVR 2004)| year=2004 | pages=24–32}}
* Relevance models
:{{cite conference |author1=J Jeon |author2=V Lavrenko |author3=R Manmatha  |name-list-style=amp | url=http://ciir.cs.umass.edu/pubfiles/mm-41.pdf | title=Automatic image annotation and retrieval using cross-media relevance models | book-title=Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval | year=2003 | pages=119–126}}
* Relevance models using continuous probability density functions
:{{cite conference |author1=V Lavrenko |author2=R Manmatha |author3=J Jeon  |name-list-style=amp | url=http://ciir.cs.umass.edu/pubfiles/mm-46.pdf | title=A model for learning the semantics of pictures | book-title=Proceedings of the 16th Conference on Advances in Neural Information Processing Systems NIPS | year=2003 }}
* Coherent Language Model
:{{cite conference |author1=R Jin |author2=J Y Chai |author3=L Si | url=http://www.cse.msu.edu/~rongjin/publications/acmmm04.jin.pdf | title=Effective Automatic Image Annotation via A Coherent Language Model and Active Learning | book-title=Proceedings of MM'04 | year=2004 }}
* Inference networks
:{{cite conference |author1=D Metzler  |author2=R Manmatha  |name-list-style=amp | url=http://ciir.cs.umass.edu/pubfiles/mm-346.pdf | title=An inference network approach to image retrieval | book-title=Proceedings of the International Conference on Image and Video Retrieval | year=2004 | pages=42–50}}
* Multiple Bernoulli distribution
:{{cite conference |author1=S Feng |author2=R Manmatha |author3=V Lavrenko  |name-list-style=amp | url=http://ciir.cs.umass.edu/pubfiles/mm-333.pdf | title=Multiple Bernoulli relevance models for image and video annotation | book-title=IEEE Conference on Computer Vision and Pattern Recognition | year=2004 | pages=1002–1009}}
* Multiple design alternatives
:{{cite conference|author1=J Y Pan |author2=H-J Yang |author3=P Duygulu |author4=C Faloutsos |url=http://www.informedia.cs.cmu.edu/documents/ICME04AutoICap.pdf |title=Automatic Image Captioning |book-title=Proceedings of the 2004 IEEE International Conference on Multimedia and Expo (ICME'04) |year=2004 |url-status=dead |archive-url=https://web.archive.org/web/20041209191242/http://www.informedia.cs.cmu.edu/documents/ICME04AutoICap.pdf |archive-date=2004-12-09 }}
* Image captioning
:{{cite conference|author1=Quan Hoang Lam |author2=Quang Duy Le |author3=Kiet Van Nguyen |author4=Ngan Luu-Thuy Nguyen |url=https://link.springer.com/chapter/10.1007/978-3-030-63007-2_57 |title=UIT-ViIC: A Dataset for the First Evaluation on Vietnamese Image Captioning |book-title=Proceedings of the 2020 International Conference on Computational Collective Intelligence (ICCCI 2020) |year=2020 |doi=10.1007/978-3-030-63007-2_57 |arxiv=2002.00175 }}
* Natural scene annotation
:{{cite conference |author1=J Fan |author2=Y Gao |author3=H Luo |author4=G Xu | url=http://portal.acm.org/ft_gateway.cfm?id=1009055&type=pdf&coll=GUIDE&dl=GUIDE&CFID=1581830&CFTOKEN=99651762 | title=Automatic Image Annotation by Using Concept-Sensitive Salient Objects for Image Content Representation | book-title=Proceedings of the 27th annual international conference on Research and development in information retrieval | year=2004 | pages=361–368}}
* Relevant low-level global filters
:{{cite conference |author1=A Oliva  |author2=A Torralba  |name-list-style=amp | url=http://cvcl.mit.edu/Papers/IJCV01-Oliva-Torralba.pdf | title=Modeling the shape of the scene: a holistic representation of the spatial envelope | book-title=International Journal of Computer Vision | year=2001 | pages=42:145–175}}
* Global image features and nonparametric density estimation
:{{cite conference|author1=A Yavlinsky, E Schofield |author2=S Rüger |name-list-style=amp |url=http://km.doc.ic.ac.uk/www-pub/civr05-annotation.pdf |title=Automated Image Annotation Using Global Features and Robust Nonparametric Density Estimation |book-title=Int'l Conf on Image and Video Retrieval (CIVR, Singapore, Jul 2005) |year=2005 |url-status=dead |archive-url=https://web.archive.org/web/20051220164354/http://km.doc.ic.ac.uk/www-pub/civr05-annotation.pdf |archive-date=2005-12-20 }}
* Video semantics
:{{cite conference |author1=N Vasconcelos  |author2=A Lippman  |name-list-style=amp | url=http://www.svcl.ucsd.edu/publications/journal/2000/ip/ip00.pdf | title=Statistical Models of Video Structure for Content Analysis and Characterization | book-title=IEEE Transactions on Image Processing | year=2001 | pages=1–17}}
:{{cite conference |author1=Ilaria Bartolini |author2=Marco Patella |author3=Corrado Romani  |name-list-style=amp | 
url=http://dl.acm.org/citation.cfm?doid=1862344.1862364 | title=Shiatsu: Semantic-based Hierarchical Automatic Tagging of Videos by Segmentation Using Cuts | book-title=3rd ACM International Multimedia Workshop on Automated Information Extraction in Media Production (AIEMPro10) | year=2010}}
* Image Annotation Refinement
:{{cite conference |author1=Yohan Jin |author2-link=Latifur Khan |author2=Latifur Khan |author3=Lei Wang |author4=Mamoun Awad  |name-list-style=amp | url=http://portal.acm.org/citation.cfm?id=1101305&dl=GUIDE, | title=Image annotations by combining multiple evidence & wordNet | book-title=13th Annual ACM International Conference on Multimedia (MM 05) |year=2005 | pages=706–715}}
:{{cite conference |author1=Changhu Wang |author2=Feng Jing |author3=Lei Zhang |author4=Hong-Jiang Zhang  |name-list-style=amp |
url=http://portal.acm.org/citation.cfm?id=1180639.1180774#, | title=Image annotation refinement using random walk with restarts | book-title =14th Annual ACM International Conference on Multimedia (MM 06) |year=2006}}
:{{cite conference |author1=Changhu Wang |author2=Feng Jing |author3=Lei Zhang |author4=Hong-Jiang Zhang  |name-list-style=amp | title=content-based image annotation refinement | book-title=IEEE Conference on Computer Vision and Pattern Recognition (CVPR 07)| year=2007|doi=10.1109/CVPR.2007.383221 }}
:{{cite conference |author1=Ilaria Bartolini  |author2=Paolo Ciaccia |name-list-style=amp | title=Imagination: Exploiting Link Analysis for Accurate Image Annotation | book-title=Springer Adaptive Multimedia Retrieval | year=2007|doi=10.1007/978-3-540-79860-6_3 }}
:{{cite conference |author1=Ilaria Bartolini  |author2=Paolo Ciaccia |name-list-style=amp |
url=http://dl.acm.org/citation.cfm?doid=1868366.1868371 | title=Multi-dimensional Keyword-based Image Annotation and Search | book-title=2nd ACM International Workshop on Keyword Search on Structured Data (KEYS 2010)| year=2010}}
* Automatic Image Annotation by Ensemble of Visual Descriptors
:{{cite conference |author1=Emre Akbas  |author2=Fatos Y. Vural  |name-list-style=amp | title=Automatic Image Annotation by Ensemble of Visual Descriptors | book-title=Intl. Conf. on Computer Vision (CVPR) 2007, Workshop on Semantic Learning Applications in Multimedia | year=2007|doi=10.1109/CVPR.2007.383484 }}
* A New Baseline for Image Annotation
:{{cite conference | author=Ameesh Makadia and Vladimir Pavlovic and Sanjiv Kumar | url=http://www.cs.rutgers.edu/~vladimir/pub/makadia08eccv.pdf | title=A New Baseline for Image Annotation | book-title= European Conference on Computer Vision (ECCV) | year=2008}}

Simultaneous Image Classification and Annotation

:{{cite conference | author=Chong Wang and David Blei and Li Fei-Fei | url=http://cs.stanford.edu/groups/vision/documents/WangBleiFei-Fei_CVPR2009.pdf | title=Simultaneous Image Classification and Annotation | book-title=Conf. on Computer Vision and Pattern Recognition (CVPR) | year=2009}}
* TagProp: Discriminative Metric Learning in Nearest Neighbor Models for Image Auto-Annotation
:{{cite conference | author=Matthieu Guillaumin and Thomas Mensink and Jakob Verbeek and Cordelia Schmid | url=https://lear.inrialpes.fr/pubs/2009/GMVS09/GMVS09.pdf | title=TagProp: Discriminative Metric Learning in Nearest Neighbor Models for Image Auto-Annotation | book-title=Intl. Conf. on Computer Vision (ICCV) | year=2009}}
* Image Annotation Using Metric Learning in Semantic Neighbourhoods
:{{cite conference  |author1=Yashaswi Verma  |author2=C. V. Jawahar  |name-list-style=amp  |url=http://researchweb.iiit.ac.in/~yashaswi.verma/eccv12/vj_eccv12.pdf  |title=Image Annotation Using Metric Learning in Semantic Neighbourhoods  |book-title=European Conference on Computer Vision (ECCV)  |year=2012  |access-date=2014-02-26  |archive-url=https://web.archive.org/web/20130514202446/http://researchweb.iiit.ac.in/%7Eyashaswi.verma/eccv12/vj_eccv12.pdf  |archive-date=2013-05-14  |url-status=dead  }}
* Automatic Image Annotation Using Deep Learning Representations
:{{cite conference |author1=Venkatesh N. Murthy  |author2=Subhransu Maji and R. Manmatha |name-list-style=amp | url=https://people.cs.umass.edu/~smaji/papers/embeddings-icmr15s.pdf | title=Automatic Image Annotation Using Deep Learning Representations | book-title= International Conference on Multimedia (ICMR) | year=2015}}
*Holistic Image Annotation using Salient Regions and Background Image Information
:{{cite conference |last1 = Sarin|last2= Fahrmair|name-list-style=amp|
url=https://www.jstage.jst.go.jp/article/ipsjjip/20/1/20_1_250/_pdf/-char/en| title = Leveraging Features from Background and Salient Regions for Automatic Image Annotation| book-title= 
| year = 2012|first1=Supheakmungkol|volume=20|pages=250–266|conference=Journal of Information Processing|first2=Michael|last3=Wagner|first3=Matthias|last4=Kameyama|first4=Wataru}}
* Medical Image Annotation using bayesian networks and active learning
:{{cite conference |author1 = N. B. Marvasti|author2= E. Yörük and B. Acar|name-list-style=amp|
url=https://www.researchgate.net/publication/320935564| title = Computer-Aided Medical Image Annotation: Preliminary Results With Liver Lesions in CT| book-title= IEEE Journal of Biomedical and Health Informatics
| year = 2018}}
{{Computer vision}}

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