{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T06:01:34Z","timestamp":1743055294381,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030134686"},{"type":"electronic","value":"9783030134693"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-13469-3_54","type":"book-chapter","created":{"date-parts":[[2019,3,2]],"date-time":"2019-03-02T13:03:53Z","timestamp":1551531833000},"page":"462-469","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["FqSD: Full-Quaternion Saliency Detection in Images"],"prefix":"10.1007","author":[{"given":"Reynolds Le\u00f3n","family":"Guerra","sequence":"first","affiliation":[]},{"given":"Edel B.","family":"Garc\u00eda Reyes","sequence":"additional","affiliation":[]},{"given":"Annette M.","family":"Gonz\u00e1lez\u00a0Quevedo","sequence":"additional","affiliation":[]},{"given":"Heydi M\u00e9ndez","family":"V\u00e1zquez","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,3,3]]},"reference":[{"issue":"1","key":"54_CR1","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1109\/TIP.2017.2756825","volume":"27","author":"X Wang","year":"2018","unstructured":"Wang, X., et al.: Edge preserving and multi-scale contextual neural network for salient object detection. IEEE Trans. Image Process. 27(1), 121\u2013134 (2018)","journal-title":"IEEE Trans. Image Process."},{"key":"54_CR2","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1016\/j.patcog.2017.09.023","volume":"74","author":"C Aytekin","year":"2018","unstructured":"Aytekin, C., Iosifidis, A., Gabbouj, M.: Probabilistic saliency estimation. Pattern Recognit. 74, 359\u2013372 (2018)","journal-title":"Pattern Recognit."},{"key":"54_CR3","doi-asserted-by":"crossref","unstructured":"Murabito, F., et al.: Top-down saliency detection driven by visual classification. arXiv preprint arXiv:1709.05307 (2017)","DOI":"10.1016\/j.cviu.2018.03.005"},{"key":"54_CR4","unstructured":"Li, S., Mathews, P.: Can image retrieval help visual saliency detection? arXiv preprint arXiv:1709.08172 (2017)"},{"key":"54_CR5","unstructured":"Zhu, F., et al.: A novel two-stream saliency image fusion CNN architecture for person re-identification. Multimed. Syst., 1\u201314 (2017)"},{"issue":"4","key":"54_CR6","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1167\/13.4.11","volume":"13","author":"E Erdem","year":"2013","unstructured":"Erdem, E., Erdem, A.: Visual saliency estimation by nonlinearly integrating features using region covariances. J. Vis. 13(4), 11\u201311 (2013)","journal-title":"J. Vis."},{"key":"54_CR7","doi-asserted-by":"crossref","unstructured":"Hu, D., et al.: Saliency region detection via local and global (2015)","DOI":"10.2991\/csic-15.2015.27"},{"issue":"23","key":"54_CR8","doi-asserted-by":"publisher","first-page":"16699","DOI":"10.1007\/s11042-016-3903-3","volume":"75","author":"S Liu","year":"2016","unstructured":"Liu, S., Hu, J.: Visual saliency based on frequency domain analysis and spatial information. Multimed. Tools Appl. 75(23), 16699\u201316711 (2016)","journal-title":"Multimed. Tools Appl."},{"issue":"7","key":"54_CR9","first-page":"111","volume":"8","author":"C Yu","year":"2015","unstructured":"Yu, C., Zhang, W., Wang, C.: A saliency detection method based on global contrast. Int. J. Signal Process. Image Process. Pattern Recognit. 8(7), 111\u2013122 (2015)","journal-title":"Int. J. Signal Process. Image Process. Pattern Recognit."},{"key":"54_CR10","doi-asserted-by":"crossref","unstructured":"Wang, L., et al.: Deep networks for saliency detection via local estimation and global search. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3183\u20133192. IEEE (2015)","DOI":"10.1109\/CVPR.2015.7298938"},{"issue":"8","key":"54_CR11","doi-asserted-by":"publisher","first-page":"58","DOI":"10.5815\/ijigsp.2015.08.07","volume":"7","author":"OS Rajankar","year":"2015","unstructured":"Rajankar, O.S., Kolekar, U.D.: Scale space reduction with interpolation to speed up visual saliency detection. Int. J. Image Graph. Signal Process. 7(8), 58 (2015)","journal-title":"Int. J. Image Graph. Signal Process."},{"key":"54_CR12","doi-asserted-by":"crossref","unstructured":"Burt, P.J., Adelson, E.H.: The Laplacian pyramid as a compact image code. In: Readings in Computer Vision, pp. 671\u2013679 (1987)","DOI":"10.1016\/B978-0-08-051581-6.50065-9"},{"key":"54_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1007\/978-3-319-75193-1_41","volume-title":"Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications","author":"RL Guerra","year":"2018","unstructured":"Guerra, R.L., Garc\u00eda Reyes, E.B., Mata, F.J.S.: Full-quaternion color correction in images for person re-identification. In: Mendoza, M., Velast\u00edn, S. (eds.) CIARP 2017. LNCS, vol. 10657, pp. 339\u2013346. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-75193-1_41"},{"key":"54_CR14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-0348-0622-0","volume-title":"Real Quaternionic Calculus Handbook","author":"JP Morais","year":"2014","unstructured":"Morais, J.P., Georgiev, S., Spr\u00f6\u00dfig, W.: Real Quaternionic Calculus Handbook. Springer, Basel (2014). https:\/\/doi.org\/10.1007\/978-3-0348-0622-0"},{"issue":"22","key":"54_CR15","doi-asserted-by":"publisher","first-page":"10077","DOI":"10.1007\/s11042-015-2803-2","volume":"74","author":"V Buso","year":"2015","unstructured":"Buso, V., Benois-Pineau, J., Domenger, J.-P.: Geometrical cues in visual saliency models for active object recognition in egocentric videos. Multimed. Tools Appl. 74(22), 10077\u201310095 (2015)","journal-title":"Multimed. Tools Appl."},{"key":"54_CR16","doi-asserted-by":"crossref","unstructured":"Yan, Q., et al.: Hierarchical saliency detection. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1155\u20131162. IEEE (2013)","DOI":"10.1109\/CVPR.2013.153"},{"key":"54_CR17","doi-asserted-by":"crossref","unstructured":"Yang, C., et al.: Saliency detection via graph-based manifold ranking. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3166\u20133173. IEEE (2013)","DOI":"10.1109\/CVPR.2013.407"},{"issue":"11","key":"54_CR18","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1109\/34.730558","volume":"20","author":"L Itti","year":"1998","unstructured":"Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20(11), 1254\u20131259 (1998)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"54_CR19","doi-asserted-by":"crossref","unstructured":"Zhu, W., et al.: Saliency optimization from robust background detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2814\u20132821 (2014)","DOI":"10.1109\/CVPR.2014.360"},{"key":"54_CR20","doi-asserted-by":"publisher","first-page":"3176","DOI":"10.1109\/TIP.2015.2440174","volume":"24","author":"H Li","year":"2015","unstructured":"Li, H., et al.: Inner and inter label propagation: salient object detection in the wild. IEEE Trans. Image Process. 24, 3176\u20133186 (2015)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"54_CR21","doi-asserted-by":"publisher","first-page":"00027","DOI":"10.15406\/iratj.2017.02.00027","volume":"2","author":"L Jiang","year":"2017","unstructured":"Jiang, L., Zhong, H., Lin, X.: Saliency detection via boundary prior and center prior. Int. Robot. Autom. J. 2(4), 00027 (2017). https:\/\/doi.org\/10.15406\/iratj.2017.02.00027","journal-title":"Int. Robot. Autom. J."},{"key":"54_CR22","doi-asserted-by":"crossref","unstructured":"Tong, N., et al.: Salient object detection via bootstrap learning. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1884\u20131892. IEEE (2015)","DOI":"10.1109\/CVPR.2015.7298798"},{"key":"54_CR23","doi-asserted-by":"crossref","unstructured":"Li, Y., et al.: The secrets of salient object segmentation. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 280\u2013287. IEEE (2014)","DOI":"10.1109\/CVPR.2014.43"},{"key":"54_CR24","doi-asserted-by":"crossref","unstructured":"Kim, J., et al.: Salient region detection via high-dimensional color transform. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 883\u2013890 (2014)","DOI":"10.1109\/CVPR.2014.118"},{"key":"54_CR25","unstructured":"Qin, Y., et al.: Saliency detection via cellular automata. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 110\u2013119. IEEE (2015)"},{"key":"54_CR26","doi-asserted-by":"crossref","unstructured":"Xia, C., Zhang, H., Gao, X.: Saliency detection by aggregating complementary background template with optimization framework. arXiv preprint arXiv:1706.04285 (2017)","DOI":"10.1145\/3205326.3205353"},{"issue":"07","key":"54_CR27","doi-asserted-by":"publisher","first-page":"1850024","DOI":"10.1142\/S0218001418500246","volume":"32","author":"H Wang","year":"2018","unstructured":"Wang, H., et al.: Saliency region detection method based on background and spatial position. Int. J. Pattern Recognit. Artif. Intell. 32(07), 1850024 (2018)","journal-title":"Int. J. Pattern Recognit. Artif. Intell."}],"container-title":["Lecture Notes in Computer Science","Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-13469-3_54","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,2]],"date-time":"2023-03-02T01:10:43Z","timestamp":1677719443000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-13469-3_54"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030134686","9783030134693"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-13469-3_54","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"3 March 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CIARP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Iberoamerican Congress on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Madrid","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","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":"19 November 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 November 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ciarp2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/atvs.ii.uam.es\/ciarp2018\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-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":"187","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":"112","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":"60% - 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":"2,94","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":"5","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":"Yes","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"}]}}