{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T09:32:31Z","timestamp":1790847151858,"version":"4.1.0"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031550140","type":"print"},{"value":"9783031550157","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-55015-7_22","type":"book-chapter","created":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T20:57:33Z","timestamp":1710363453000},"page":"262-274","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Anthropomorphic Human-Robot Interaction Framework: Attention Based Approach"],"prefix":"10.1007","author":[{"given":"Natnael","family":"Wondimu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ma\u00eblic","family":"Neau","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antoine","family":"Dizet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ubbo","family":"Visser","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C\u00e9dric","family":"Buche","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,3,14]]},"reference":[{"key":"22_CR1","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1007\/s12369-017-0446-3","volume":"10","author":"R Andreasson","year":"2018","unstructured":"Andreasson, R., Alenljung, B., Billing, E., Lowe, R.: Affective touch in human-robot interaction: conveying emotion to the nao robot. Int. J. Soc. Robot. 10, 473\u2013491 (2018)","journal-title":"Int. J. Soc. Robot."},{"issue":"2","key":"22_CR2","doi-asserted-by":"publisher","first-page":"74","DOI":"10.5898\/JHRI.3.2.Beer","volume":"3","author":"JM Beer","year":"2014","unstructured":"Beer, J.M., Fisk, A.D., Rogers, W.A.: Toward a framework for levels of robot autonomy in human-robot interaction. J. Hum.-Robot Interact. 3(2), 74 (2014)","journal-title":"J. Hum.-Robot Interact."},{"key":"22_CR3","doi-asserted-by":"crossref","unstructured":"Duchaine, V., Gosselin, C.: Safe, stable and intuitive control for physical human-robot interaction. In: 2009 IEEE International Conference on Robotics and Automation, pp. 3383\u20133388. IEEE (2009)","DOI":"10.1109\/ROBOT.2009.5152664"},{"key":"22_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.rcim.2021.102304","volume":"75","author":"J Fan","year":"2022","unstructured":"Fan, J., Zheng, P., Li, S.: Vision-based holistic scene understanding towards proactive human-robot collaboration. Robot. Comput.-Integr. Manuf. 75, 102304 (2022)","journal-title":"Robot. Comput.-Integr. Manuf."},{"issue":"3\u20134","key":"22_CR5","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1016\/S0921-8890(02)00372-X","volume":"42","author":"T Fong","year":"2003","unstructured":"Fong, T., Nourbakhsh, I., Dautenhahn, K.: A survey of socially interactive robots. Robot. Auton. Syst. 42(3\u20134), 143\u2013166 (2003)","journal-title":"Robot. Auton. Syst."},{"issue":"5","key":"22_CR6","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1017\/S0140525X01000103","volume":"24","author":"B Hommel","year":"2001","unstructured":"Hommel, B., M\u00fcsseler, J., Aschersleben, G., Prinz, W.: The theory of event coding (TEC): a framework for perception and action planning. Behav. Brain Sci. 24(5), 849\u2013878 (2001)","journal-title":"Behav. Brain Sci."},{"key":"22_CR7","doi-asserted-by":"publisher","first-page":"1049","DOI":"10.3389\/fpsyg.2015.01049","volume":"6","author":"CM Huang","year":"2015","unstructured":"Huang, C.M., Andrist, S., Saupp\u00e9, A., Mutlu, B.: Using gaze patterns to predict task intent in collaboration. Front. Psychol. 6, 1049 (2015)","journal-title":"Front. Psychol."},{"key":"22_CR8","doi-asserted-by":"crossref","unstructured":"Jiang, L., Xu, M., Liu, T., Qiao, M., Wang, Z.: Deepvs: a deep learning based video saliency prediction approach. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 602\u2013617 (2018)","DOI":"10.1007\/978-3-030-01264-9_37"},{"issue":"1\u20132","key":"22_CR9","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.cviu.2004.10.009","volume":"100","author":"T Jost","year":"2005","unstructured":"Jost, T., Ouerhani, N., Von Wartburg, R., M\u00fcri, R., H\u00fcgli, H.: Assessing the contribution of color in visual attention. Comput. Vis. Image Underst. 100(1\u20132), 107\u2013123 (2005)","journal-title":"Comput. Vis. Image Underst."},{"issue":"3","key":"22_CR10","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1075\/is.8.3.04kah","volume":"8","author":"PH Kahn Jr","year":"2007","unstructured":"Kahn, P.H., Jr., et al.: What is a human?: toward psychological benchmarks in the field of human-robot interaction. Interact. Stud. 8(3), 363\u2013390 (2007)","journal-title":"Interact. Stud."},{"issue":"2","key":"22_CR11","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1521\/soco.2008.26.2.169","volume":"26","author":"S Kiesler","year":"2008","unstructured":"Kiesler, S., Powers, A., Fussell, S.R., Torrey, C.: Anthropomorphic interactions with a robot and robot-like agent. Soc. Cogn. 26(2), 169\u2013181 (2008)","journal-title":"Soc. Cogn."},{"key":"22_CR12","doi-asserted-by":"crossref","unstructured":"Li, H., Chen, G., Li, G., Yu, Y.: Motion guided attention for video salient object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 7274\u20137283 (2019)","DOI":"10.1109\/ICCV.2019.00737"},{"key":"22_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2019.115686","volume":"81","author":"X Li","year":"2020","unstructured":"Li, X.: Human-robot interaction based on gesture and movement recognition. Signal Process. Image Commun. 81, 115686 (2020)","journal-title":"Signal Process. Image Commun."},{"issue":"18","key":"22_CR14","doi-asserted-by":"publisher","first-page":"2397","DOI":"10.1016\/j.visres.2005.03.019","volume":"45","author":"RJ Peters","year":"2005","unstructured":"Peters, R.J., Iyer, A., Itti, L., Koch, C.: Components of bottom-up gaze allocation in natural images. Vision. Res. 45(18), 2397\u20132416 (2005)","journal-title":"Vision. Res."},{"key":"22_CR15","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1146\/annurev-neuro-062111-150525","volume":"35","author":"SE Petersen","year":"2012","unstructured":"Petersen, S.E., Posner, M.I.: The attention system of the human brain: 20 years after. Annu. Rev. Neurosci. 35, 73\u201389 (2012)","journal-title":"Annu. Rev. Neurosci."},{"key":"22_CR16","unstructured":"Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Pearson Education Limited, London (2016)"},{"key":"22_CR17","doi-asserted-by":"crossref","unstructured":"Saran, A., Majumdar, S., Short, E.S., Thomaz, A., Niekum, S.: Human gaze following for human-robot interaction. In: 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 8615\u20138621. IEEE (2018)","DOI":"10.1109\/IROS.2018.8593580"},{"key":"22_CR18","doi-asserted-by":"crossref","unstructured":"Schauerte, B., Fink, G.A.: Focusing computational visual attention in multi-modal human-robot interaction. In: International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction, pp. 1\u20138 (2010)","DOI":"10.1145\/1891903.1891912"},{"issue":"4","key":"22_CR19","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1177\/0018720816644364","volume":"58","author":"TB Sheridan","year":"2016","unstructured":"Sheridan, T.B.: Human-robot interaction: status and challenges. Hum. Factors 58(4), 525\u2013532 (2016)","journal-title":"Hum. Factors"},{"key":"22_CR20","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"issue":"5","key":"22_CR21","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1016\/j.visres.2004.09.017","volume":"45","author":"BW Tatler","year":"2005","unstructured":"Tatler, B.W., Baddeley, R.J., Gilchrist, I.D.: Visual correlates of fixation selection: effects of scale and time. Vision. Res. 45(5), 643\u2013659 (2005)","journal-title":"Vision. Res."},{"key":"22_CR22","doi-asserted-by":"crossref","unstructured":"Wang, W., Shen, J., Guo, F., Cheng, M.M., Borji, A.: Revisiting video saliency: a large-scale benchmark and a new model. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4894\u20134903 (2018)","DOI":"10.1109\/CVPR.2018.00514"},{"key":"22_CR23","doi-asserted-by":"crossref","unstructured":"Wang, Y., Jodoin, P.M., Porikli, F., Konrad, J., Benezeth, Y., Ishwar, P.: CDnet 2014: an expanded change detection benchmark dataset. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 387\u2013394 (2014)","DOI":"10.1109\/CVPRW.2014.126"},{"key":"22_CR24","doi-asserted-by":"crossref","unstructured":"Wondimu, N., Visser, U., Buche, C.: Interactive video saliency prediction: the stacked-ConvLSTM approach. In: 15th International Conference on Agents and Artificial Intelligence, pp. 157\u2013168. SCITEPRESS-Science and Technology Publications (2023)","DOI":"10.5220\/0011664600003393"},{"key":"22_CR25","doi-asserted-by":"crossref","unstructured":"Wondimu, N., Visser, U., Buche, C.: A new approach to moving object detection and segmentation: the XY-shift frame differencing. In: 15th International Conference on Agents and Artificial Intelligence, pp. 309\u2013318. SCITEPRESS-Science and Technology Publications; SCITEPRESS-Science and $$\\ldots $$ (2023)","DOI":"10.5220\/0011664500003393"},{"key":"22_CR26","unstructured":"Wondimu, N.A., Buche, C., Visser, U.: Interactive machine learning: a state of the art review. arXiv preprint arXiv:2207.06196 (2022)"}],"container-title":["Lecture Notes in Computer Science","RoboCup 2023: Robot World Cup XXVI"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-55015-7_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T20:59:39Z","timestamp":1710363579000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-55015-7_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031550140","9783031550157"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-55015-7_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"14 March 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"RoboCup","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Robot World Cup","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bordeaux","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"robocup2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2023.robocup.org\/en\/home\/","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":"59","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":"36","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":"61% - 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":"3","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":"3","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)"}}]}}