{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T23:57:47Z","timestamp":1726185467824},"publisher-location":"Cham","reference-count":31,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031222153"},{"type":"electronic","value":"9783031222160"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-22216-0_28","type":"book-chapter","created":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T04:39:26Z","timestamp":1673930366000},"page":"407-424","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["People Tracking in Panoramic Video for Guiding Robots"],"prefix":"10.1007","author":[{"given":"Alberto","family":"Bacchin","sequence":"first","affiliation":[]},{"given":"Filippo","family":"Berno","sequence":"additional","affiliation":[]},{"given":"Emanuele","family":"Menegatti","sequence":"additional","affiliation":[]},{"given":"Alberto","family":"Pretto","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,18]]},"reference":[{"issue":"1","key":"28_CR1","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/S0004-3702(99)00070-3","volume":"114","author":"W Burgard","year":"1999","unstructured":"Burgard, W., Cremers, A.B., Fox, D., H\u00e4hnel, D., Lakemeyer, G., Schulz, D., Steiner, W., Thrun, S.: Experiences with an interactive museum tour-guide robot. Art. Intell. 114(1), 3\u201355 (1999)","journal-title":"Art. Intell."},{"key":"28_CR2","doi-asserted-by":"crossref","unstructured":"Koide, K., Miura, J., Menegatti, E.: Monocular person tracking and identification with on-line deep feature selection for person following robots. Rob. Auton. Syst. 124 (2020)","DOI":"10.1016\/j.robot.2019.103348"},{"issue":"01","key":"28_CR3","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1109\/TPAMI.2019.2929257","volume":"43","author":"Z Cao","year":"2021","unstructured":"Cao, Z., Hidalgo, G., Simon, T., Wei, S., Sheikh, Y.: Openpose: realtime multi-person 2d pose estimation using part affinity fields. IEEE Trans. Pattern Anal. Mach. Intell. 43(01), 172\u2013186 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"28_CR4","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1007\/978-3-319-60928-7_42","volume-title":"Augmented Reality, Virtual Reality, and Computer Graphics","author":"WG Aguilar","year":"2017","unstructured":"Aguilar, W.G., Luna, M.A., Moya, J.F., Abad, V., Ruiz, H., Parra, H., Lopez, W.: Cascade classifiers and saliency maps based people detection. In: De Paolis, L.T., Bourdot, P., Mongelli, A. (eds.) Augmented Reality, Virtual Reality, and Computer Graphics, pp. 501\u2013510. Springer International Publishing, Cham (2017)"},{"key":"28_CR5","unstructured":"Geronimo, D., Sappa, A., L\u00f3pez, A., Ponsa, D.: Pedestrian detection using adaboost learning of features and vehicle pitch estimation. In Proceedings of the IASTED Int. Conf. on Visualization, Imaging and Image Processing, pp. 400\u20134005 (2006)"},{"issue":"6","key":"28_CR6","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1016\/j.vrih.2020.04.005","volume":"2","author":"X Ji","year":"2020","unstructured":"Ji, X., Fang, Q., Dong, J., Shuai, Q., Jiang, W., Zhou, X.: A survey on monocular 3d human pose estimation. Virtual Reality Intell. Hardware 2(6), 471\u2013500 (2020)","journal-title":"Virtual Reality Intell. Hardware"},{"key":"28_CR7","doi-asserted-by":"crossref","unstructured":"Zhao, X., Li, W., Zhang, Y., Gulliver, T.A., Chang, S., Feng, Z.: A faster RCNN-based pedestrian detection system. In: 2016 IEEE 84th Vehicular Technology Conference (VTC-Fall), pp. 1\u20135 (2016)","DOI":"10.1109\/VTCFall.2016.7880852"},{"key":"28_CR8","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster r-cnn: Towards real-time object detection with region proposal networks. In: Cortes, C., Lawrence, N., Lee, D., Sugiyama, M., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol. 28 (2015)"},{"key":"28_CR9","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: unified, real-time object detection. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 779\u2013788 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"28_CR10","doi-asserted-by":"crossref","unstructured":"Ahmad, M., Ahmed, I., Adnan, A.: Overhead view person detection using yolo. In: IEEE 10th Annual Ubiquitous Computing. Electronics Mobile Communication Conference (UEMCON), vol. 2019, pp. 0627\u20130633 (2019)","DOI":"10.1109\/UEMCON47517.2019.8992980"},{"key":"28_CR11","doi-asserted-by":"crossref","unstructured":"Sharma, S., Ansari, J.A., Krishna\u00a0Murthy, J., Madhava\u00a0Krishna, K.: Beyond pixels: Leveraging geometry and shape cues for online multi-object tracking. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 3508\u20133515 (2018)","DOI":"10.1109\/ICRA.2018.8461018"},{"key":"28_CR12","doi-asserted-by":"crossref","unstructured":"Niu, Y., Xu, Z., Xu, E., Li, G., Huo, Y., Sun, W.: Monocular pedestrian 3d localization for social distance monitoring. Sensors 21 (2021)","DOI":"10.3390\/s21175908"},{"key":"28_CR13","unstructured":"Kreiss, S., Bertoni, L., Alahi, A.: OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association. IEEE Trans. Intell. Transp. Syst. 1\u201314 (2021, March)"},{"key":"28_CR14","doi-asserted-by":"crossref","unstructured":"Bertoni, L., Kreiss, S., Alahi, A.: Monoloco: Monocular 3d pedestrian localization and uncertainty estimation. In: 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 6860\u20136870 (2019)","DOI":"10.1109\/ICCV.2019.00696"},{"key":"28_CR15","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.robot.2019.01.011","volume":"114","author":"M Kollmitz","year":"2019","unstructured":"Kollmitz, M., Eitel, A., Vasquez, A., Burgard, W.: Deep 3d perception of people and their mobility aids. Rob. Auton. Syst. 114, 29\u201340 (2019)","journal-title":"Rob. Auton. Syst."},{"key":"28_CR16","doi-asserted-by":"crossref","unstructured":"Munaro, M., Menegatti, E.: Fast RGB-D people tracking for service robots. Auton. Robots 37 (2014)","DOI":"10.1007\/s10514-014-9385-0"},{"key":"28_CR17","doi-asserted-by":"crossref","unstructured":"Zheng, K., Wu, F., Chen, X.: Laser-based people detection and obstacle avoidance for a hospital transport robot. Sensors 21(3) (2021)","DOI":"10.3390\/s21030961"},{"key":"28_CR18","doi-asserted-by":"crossref","unstructured":"Choi, W., Savarese, S.: Multiple target tracking in world coordinate with single, minimally calibrated camera. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) Computer Vision\u2014ECCV 2010, pp. 553\u2013567. Heidelberg, Springer, Berlin Heidelberg, Berlin (2010)","DOI":"10.1007\/978-3-642-15561-1_40"},{"issue":"11","key":"28_CR19","doi-asserted-by":"publisher","first-page":"904","DOI":"10.1016\/j.imavis.2014.08.002","volume":"32","author":"I Ardiyanto","year":"2014","unstructured":"Ardiyanto, I., Miura, J.: Partial least squares-based human upper body orientation estimation with combined detection and tracking. Image Vis. Comput. 32(11), 904\u2013915 (2014)","journal-title":"Image Vis. Comput."},{"key":"28_CR20","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.neucom.2019.12.037","volume":"386","author":"Y Liu","year":"2020","unstructured":"Liu, Y., Yin, J., Yu, D., Zhao, S., Shen, J.: Multiple people tracking with articulation detection and stitching strategy. Neurocomputing 386, 18\u201329 (2020)","journal-title":"Neurocomputing"},{"key":"28_CR21","doi-asserted-by":"crossref","unstructured":"Ondr\u00fa\u0161ka, P., Posner, I.: Deep tracking: seeing beyond seeing using recurrent neural networks. In: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence. AAAI\u201916, AAAI Press, pp. 3361\u20133367 (2016)","DOI":"10.1609\/aaai.v30i1.10413"},{"key":"28_CR22","doi-asserted-by":"crossref","unstructured":"Thaler, M., Bailer, W.: Real-time person detection and tracking in panoramic video. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 1027\u20131032 (2013)","DOI":"10.1109\/CVPRW.2013.149"},{"key":"28_CR23","doi-asserted-by":"crossref","unstructured":"Tai, K.C., Tang, C.W.: Siamese networks based people tracking for 360-degree videos with equi-angular cubemap format. In: 2020 IEEE International Conference on Consumer Electronics\u2014Taiwan (ICCE-Taiwan), pp. 1\u20132 (2020)","DOI":"10.1109\/ICCE-Taiwan49838.2020.9258313"},{"key":"28_CR24","doi-asserted-by":"crossref","unstructured":"Li, J., Zang, Z., Xie, H., Wang, G.: Implementation of person tracking system in panorama based on personalized distribution. In: 2020 39th Chinese Control Conference (CCC), pp. 7123\u20137128 (2020)","DOI":"10.23919\/CCC50068.2020.9188474"},{"key":"28_CR25","doi-asserted-by":"crossref","unstructured":"Shere, M., Kim, H., Hilton, A.: 3d multi person tracking with dual $$360^{\\circ }$$ cameras. In: 2020 IEEE International Conference on Image Processing (ICIP), pp. 2765\u20132769 (2020)","DOI":"10.1109\/ICIP40778.2020.9191269"},{"key":"28_CR26","doi-asserted-by":"crossref","unstructured":"Yang, F., Li, F., Wu, Y., Sakti, S., Nakamura, S.: Using panoramic videos for multi-person localization and tracking in a 3d panoramic coordinate. In: ICASSP 2020\u20142020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1863\u20131867 (2020)","DOI":"10.1109\/ICASSP40776.2020.9053497"},{"key":"28_CR27","unstructured":"Wan, E., Van Der\u00a0Merwe, R.: The unscented kalman filter for nonlinear estimation. In: Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373), pp. 153\u2013158 (2000)"},{"key":"28_CR28","doi-asserted-by":"crossref","unstructured":"Nghiem, A.T., Bremond, F., Thonnat, M., Valentin, V.: Etiseo, performance evaluation for video surveillance systems. In: 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, pp. 476\u2013481 (2007)","DOI":"10.1109\/AVSS.2007.4425357"},{"key":"28_CR29","unstructured":"Vandyke, M., Schwartz, J., Hall, C.: Unscented kalman filtering for spacecraft attitude state and parameter estimation. Adv. Astronaut. Sci. 119 (2004)"},{"key":"28_CR30","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016","DOI":"10.1109\/CVPR.2016.90"},{"key":"28_CR31","doi-asserted-by":"crossref","unstructured":"Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., Chen, L.C.: Mobilenetv2: Inverted residuals and linear bottlenecks. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4510\u20134520 (2018)","DOI":"10.1109\/CVPR.2018.00474"}],"container-title":["Lecture Notes in Networks and Systems","Intelligent Autonomous Systems 17"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-22216-0_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T04:46:13Z","timestamp":1673930773000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-22216-0_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031222153","9783031222160"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-22216-0_28","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"18 January 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IAS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Autonomous Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zagreb","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Croatia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 June 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 June 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ias2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.ias-17.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}