{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T12:40:07Z","timestamp":1751719207659,"version":"3.41.0"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319942100"},{"type":"electronic","value":"9783319942117"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-94211-7_25","type":"book-chapter","created":{"date-parts":[[2018,6,29]],"date-time":"2018-06-29T07:29:59Z","timestamp":1530257399000},"page":"225-232","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Visual Scene Reconstruction Using a Bayesian Learning Framework"],"prefix":"10.1007","author":[{"given":"Sami","family":"Bourouis","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nizar","family":"Bouguila","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yexing","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad","family":"Azam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,6,30]]},"reference":[{"key":"25_CR1","doi-asserted-by":"crossref","unstructured":"Allili, M.S., Bouguila, N., Ziou, D.: Finite generalized gaussian mixture modeling and applications to image and video foreground segmentation. In: Proc. of the Fourth Canadian Conference on Computer and Robot Vision (CRV). pp. 183\u2013190 (2007)","DOI":"10.1109\/CRV.2007.33"},{"issue":"4","key":"25_CR2","doi-asserted-by":"crossref","first-page":"1386","DOI":"10.1016\/j.engappai.2012.10.009","volume":"26","author":"O Amayri","year":"2013","unstructured":"Amayri, O., Bouguila, N.: On online high-dimensional spherical data clustering and feature selection. Eng. Appl. of AI 26(4), 1386\u20131398 (2013)","journal-title":"Eng. Appl. of AI"},{"issue":"12","key":"25_CR3","doi-asserted-by":"publisher","first-page":"1649","DOI":"10.1109\/TKDE.2009.42","volume":"21","author":"N Bouguila","year":"2009","unstructured":"Bouguila, N.: A model-based approach for discrete data clustering and feature weighting using MAP and stochastic complexity. IEEE Trans. Knowl. Data Eng. 21(12), 1649\u20131664 (2009)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"6","key":"25_CR4","doi-asserted-by":"publisher","first-page":"1183","DOI":"10.1016\/j.patcog.2010.12.010","volume":"44","author":"N Bouguila","year":"2011","unstructured":"Bouguila, N.: Bayesian hybrid generative discriminative learning based on finite liouville mixture models. Pattern Recognition 44(6), 1183\u20131200 (2011)","journal-title":"Pattern Recognition"},{"key":"25_CR5","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1007\/11510888_5","volume-title":"Machine Learning and Data Mining in Pattern Recognition","author":"Nizar Bouguila","year":"2005","unstructured":"Bouguila, N., Ziou, D.: Mml-based approach for finite dirichlet mixture estimation and selection. In: International Workshop on Machine Learning and Data Mining in Pattern Recognition. pp. 42\u201351. Springer (2005)"},{"issue":"2","key":"25_CR6","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1007\/s10115-011-0467-4","volume":"33","author":"N Bouguila","year":"2012","unstructured":"Bouguila, N., Ziou, D.: A countably infinite mixture model for clustering and feature selection. Knowl. Inf. Syst. 33(2), 351\u2013370 (2012)","journal-title":"Knowl. Inf. Syst."},{"issue":"5","key":"25_CR7","doi-asserted-by":"publisher","first-page":"2329","DOI":"10.1016\/j.eswa.2013.09.030","volume":"41","author":"S Bourouis","year":"2014","unstructured":"Bourouis, S., Mashrgy, M.A., Bouguila, N.: Bayesian learning of finite generalized inverted dirichlet mixtures: Application to object classification and forgery detection. Expert Systems with Applications 41(5), 2329\u20132336 (2014)","journal-title":"Expert Systems with Applications"},{"key":"25_CR8","doi-asserted-by":"crossref","unstructured":"Channoufi, I., Bourouis, S., Bouguila, N., Hamrouni, K.: Color image segmentation with bounded generalized gaussian mixture model and feature selection. 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP\u20192018) (2018)","DOI":"10.1109\/ATSIP.2018.8364459"},{"key":"25_CR9","doi-asserted-by":"publisher","unstructured":"Channoufi, I., Bourouis, S., Bouguila, N., Hamrouni, K.: Image and video denoising by combining unsupervised bounded generalized gaussian mixture modeling and spatial information. Multimedia Tools and Applications (Feb 2018).https:\/\/doi.org\/10.1007\/s11042-018-5808-9","DOI":"10.1007\/s11042-018-5808-9"},{"key":"25_CR10","doi-asserted-by":"crossref","unstructured":"Congdon, P.: Applied Bayesian Modelling. John Wiley and Sons (2003)","DOI":"10.1002\/0470867159"},{"key":"25_CR11","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1007\/978-3-642-12159-3_19","volume-title":"Artificial Neural Networks in Pattern Recognition","author":"Tarek Elguebaly","year":"2010","unstructured":"Elguebaly, Tarek, Bouguila, Nizar: Bayesian Learning of Generalized Gaussian Mixture Models on Biomedical Images. In: Schwenker, Friedhelm, El Gayar, Neamat (eds.) ANNPR 2010. LNCS (LNAI), vol. 5998, pp. 207\u2013218. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-12159-3_19"},{"issue":"1","key":"25_CR12","doi-asserted-by":"publisher","first-page":"828","DOI":"10.1016\/j.eswa.2011.07.081","volume":"39","author":"W Fan","year":"2012","unstructured":"Fan, W., Bouguila, N.: Novel approaches for synthesizing video textures. Expert Systems with Applications 39(1), 828\u2013839 (2012)","journal-title":"Expert Systems with Applications"},{"issue":"10","key":"25_CR13","doi-asserted-by":"publisher","first-page":"2754","DOI":"10.1016\/j.patcog.2013.03.026","volume":"46","author":"W Fan","year":"2013","unstructured":"Fan, W., Bouguila, N.: Variational learning of a dirichlet process of generalized dirichlet distributions for simultaneous clustering and feature selection. Pattern Recognition 46(10), 2754\u20132769 (2013)","journal-title":"Pattern Recognition"},{"key":"25_CR14","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.compeleceng.2015.03.018","volume":"43","author":"W Fan","year":"2015","unstructured":"Fan, W., Sallay, H., Bouguila, N., Bourouis, S.: A hierarchical dirichlet process mixture of generalized dirichlet distributions for feature selection. Computers & Electrical Engineering 43, 48\u201365 (2015)","journal-title":"Computers & Electrical Engineering"},{"issue":"2","key":"25_CR15","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/s11263-005-6643-9","volume":"63","author":"A Fitzgibbon","year":"2005","unstructured":"Fitzgibbon, A., Wexler, Y., Zisserman, A.: Image-based rendering using image-based priors. International Journal of Computer Vision 63(2), 141\u2013151 (2005)","journal-title":"International Journal of Computer Vision"},{"key":"25_CR16","doi-asserted-by":"crossref","unstructured":"Li, W., Li, B.: Probabilistic image-based rendering with gaussian mixture model. In: 18th International Conference on Pattern Recognition (ICPR\u201906). vol. 1, pp. 179\u2013182 (2006)","DOI":"10.1109\/ICPR.2006.945"},{"key":"25_CR17","doi-asserted-by":"crossref","unstructured":"Marin, J., Mengersen, K., Robert, C.: Bayesian modeling and inference on mixtures of distributions. In: Dey, D., Rao, C. (eds.) Handbook of Statistics 25. Elsevier-Sciences (2004)","DOI":"10.1016\/S0169-7161(05)25016-2"},{"key":"25_CR18","unstructured":"McLachlan, G., Peel, D.: Finite mixture models. John Wiley & Sons (2004)"},{"key":"25_CR19","doi-asserted-by":"crossref","unstructured":"Mustafa, A., Kim, H., Guillemaut, J.Y., Hilton, A.: General dynamic scene reconstruction from multiple view video. In: 2015 IEEE International Conference on Computer Vision (ICCV). pp. 900\u2013908 (Dec 2015)","DOI":"10.1109\/ICCV.2015.109"},{"key":"25_CR20","doi-asserted-by":"crossref","unstructured":"Najar, F., Bourouis, S., Bouguila, N., Belguith, S.: A comparison between different gaussian-based mixture models. In: 14th IEEE International Conference on. Computer Systems and Applications, Tunisia. IEEE (2017)","DOI":"10.1109\/AICCSA.2017.108"},{"key":"25_CR21","doi-asserted-by":"crossref","unstructured":"Oboh, B.S., Bouguila, N.: Unsupervised learning of finite mixtures using scaled dirichlet distribution and its application to software modules categorization. In: 2017 IEEE International Conference on Industrial Technology (ICIT). pp. 1085\u20131090 (March 2017)","DOI":"10.1109\/ICIT.2017.7915513"},{"key":"25_CR22","unstructured":"Sch\u00f6dl, A., Essa, I.A.: Machine learning for video-based rendering. In: Advances in neural information processing systems. pp. 1002\u20131008 (2001)"},{"issue":"8","key":"25_CR23","doi-asserted-by":"publisher","first-page":"1370","DOI":"10.1109\/JPROC.2010.2049330","volume":"98","author":"N Snavely","year":"2010","unstructured":"Snavely, N., Simon, I., Goesele, M., Szeliski, R., Seitz, S.M.: Scene reconstruction and visualization from community photo collections. Proceedings of the IEEE 98(8), 1370\u20131390 (2010)","journal-title":"Proceedings of the IEEE"}],"container-title":["Lecture Notes in Computer Science","Image and Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-94211-7_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T12:19:35Z","timestamp":1751717975000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-94211-7_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319942100","9783319942117"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-94211-7_25","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"30 June 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICISP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image and Signal Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cherbourg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 July 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 July 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icisp2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.icisp-conf.org\/index.php.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"122","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"58","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"48% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1.88","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}