{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:45:19Z","timestamp":1742913919531,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031167874"},{"type":"electronic","value":"9783031167881"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-16788-1_19","type":"book-chapter","created":{"date-parts":[[2022,9,22]],"date-time":"2022-09-22T20:35:56Z","timestamp":1663878956000},"page":"300-316","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Online Marker-Free Extrinsic Camera Calibration Using Person Keypoint Detections"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6395-5854","authenticated-orcid":false,"given":"Bastian","family":"P\u00e4tzold","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9509-2080","authenticated-orcid":false,"given":"Simon","family":"Bultmann","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5040-7525","authenticated-orcid":false,"given":"Sven","family":"Behnke","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,9,20]]},"reference":[{"issue":"3\u20134","key":"19_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3199667","volume":"14","author":"R Bhardwaj","year":"2018","unstructured":"Bhardwaj, R., Tummala, G.K., Ramalingam, G., Ramjee, R., Sinha, P.: AutoCalib: automatic traffic camera calibration at scale. ACM Trans. Sensor Networks (TOSN) 14(3\u20134), 1\u201327 (2018). https:\/\/doi.org\/10.1145\/3199667","journal-title":"ACM Trans. Sensor Networks (TOSN)"},{"unstructured":"Bradski, G.: The OpenCV Library. Dr. Dobb\u2019s Journal of Software Tools (2000)","key":"19_CR2"},{"doi-asserted-by":"publisher","unstructured":"Bultmann, S., Behnke, S.: Real-time multi-view 3D human pose estimation using semantic feedback to smart edge sensors. In: Robotics: Science and Systems XVII (RSS) (2021). https:\/\/doi.org\/10.15607\/rss.2021.xvii.040","key":"19_CR3","DOI":"10.15607\/rss.2021.xvii.040"},{"doi-asserted-by":"publisher","unstructured":"Bultmann, S., Behnke, S.: 3D semantic scene perception using distributed smart edge sensors. In: IEEE International Conference on Intelligent Autonomous Systems (IAS) (2022). https:\/\/doi.org\/10.48550\/ARXIV.2205.01460","key":"19_CR4","DOI":"10.48550\/ARXIV.2205.01460"},{"issue":"1","key":"19_CR5","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.E., Sheikh, Y.: OpenPose: realtime multi-person 2D pose estimation using part affinity fields. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 43(1), 172\u2013186 (2021). https:\/\/doi.org\/10.1109\/TPAMI.2019.2929257","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (PAMI)"},{"doi-asserted-by":"publisher","unstructured":"Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, p. 886\u2013893 (2005). https:\/\/doi.org\/10.1109\/CVPR.2005.177","key":"19_CR6","DOI":"10.1109\/CVPR.2005.177"},{"unstructured":"Dellaert, F.: Factor graphs and GTSAM: a hands-on introduction. Tech. Rep. GT-RIM-CP &R-2012-002, Georgia Institute of Technology (2012). https:\/\/research.cc.gatech.edu\/borg\/sites\/edu.borg\/files\/downloads\/gtsam.pdf","key":"19_CR7"},{"issue":"1\u20132","key":"19_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/2300000043","volume":"6","author":"F Dellaert","year":"2017","unstructured":"Dellaert, F., Kaess, M.: Factor graphs for robot perception. Found. Trends Robot. (FNT) 6(1\u20132), 1\u2013139 (2017). https:\/\/doi.org\/10.1561\/2300000043","journal-title":"Found. Trends Robot. (FNT)"},{"issue":"1","key":"19_CR9","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1023\/B:VISI.0000042934.15159.49","volume":"61","author":"PF Felzenszwalb","year":"2005","unstructured":"Felzenszwalb, P.F., Huttenlocher, D.P.: Pictorial structures for object recognition. Int. J. Comput. Vis. (IJCV) 61(1), 55\u201379 (2005). https:\/\/doi.org\/10.1023\/B:VISI.0000042934.15159.49","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"doi-asserted-by":"publisher","unstructured":"Fischler, M., Elschlager, R.: The representation and matching of pictorial structures. IEEE Trans. Comput. C-22(1), 67\u201392 (1973). https:\/\/doi.org\/10.1109\/T-C.1973.223602","key":"19_CR10","DOI":"10.1109\/T-C.1973.223602"},{"issue":"6","key":"19_CR11","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381\u2013395 (1981). https:\/\/doi.org\/10.1145\/358669.358692","journal-title":"Commun. ACM"},{"unstructured":"Google: EdgeTPU dev board (2020). https:\/\/coral.ai\/docs\/dev-board\/datasheet. Accessed 25 Mar 2022","key":"19_CR12"},{"doi-asserted-by":"publisher","unstructured":"Guan, J., Deboeverie, F., Slembrouck, M., Van Haerenborgh, D., Van Cauwelaert, D., Veelaert, P., Philips, W.: Extrinsic calibration of camera networks based on pedestrians. Sensors 16(5) (2016). https:\/\/doi.org\/10.3390\/s16050654","key":"19_CR13","DOI":"10.3390\/s16050654"},{"key":"19_CR14","volume-title":"Multiple View Geometry in Computer Vision","author":"R Hartley","year":"2003","unstructured":"Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, USA (2003)","edition":"2"},{"doi-asserted-by":"publisher","unstructured":"Henning, D., Laidlow, T., Leutenegger, S.: BodySLAM: joint camera localisation, mapping, and human motion tracking. In: European Conference on Computer Vision (ECCV) (2022). https:\/\/doi.org\/10.48550\/ARXIV.2205.02301","key":"19_CR15","DOI":"10.48550\/ARXIV.2205.02301"},{"doi-asserted-by":"publisher","unstructured":"H\u00f6dlmoser, M., Kampel, M.: Multiple camera self-calibration and 3D reconstruction using pedestrians. In: International Symposium on Visual Computing (ISVC) (2010). https:\/\/doi.org\/10.1007\/978-3-642-17274-8_1","key":"19_CR16","DOI":"10.1007\/978-3-642-17274-8_1"},{"issue":"2","key":"19_CR17","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s10851-009-0161-2","volume":"35","author":"DQ Huynh","year":"2009","unstructured":"Huynh, D.Q.: Metrics for 3D rotations: comparison and analysis. J. Math. Imaging Vis. 35(2), 155\u2013164 (2009)","journal-title":"J. Math. Imaging Vis."},{"key":"19_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1007\/978-3-642-33564-8_16","volume-title":"Computer Vision and Graphics","author":"J Komorowski","year":"2012","unstructured":"Komorowski, J., Rokita, P.: Extrinsic camera calibration method and its performance evaluation. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds.) ICCVG 2012. LNCS, vol. 7594, pp. 129\u2013138. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33564-8_16"},{"doi-asserted-by":"publisher","unstructured":"Li, J., Wang, C., Zhu, H., Mao, Y., Fang, H.S., Lu, C.: CrowdPose: efficient crowded scenes pose estimation and a new benchmark. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 10855\u201310864 (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.01112","key":"19_CR19","DOI":"10.1109\/CVPR.2019.01112"},{"doi-asserted-by":"publisher","unstructured":"Lin, T.Y., et al.: Microsoft COCO: common objects in context. In: European Conference on Computer Vision (ECCV), pp. 740\u2013755 (2014). https:\/\/doi.org\/10.1007\/978-3-319-10602","key":"19_CR20","DOI":"10.1007\/978-3-319-10602"},{"doi-asserted-by":"publisher","unstructured":"Liu, J., Collins, R.T., Liu, Y.: Surveillance camera autocalibration based on pedestrian height distributions. In: British Machine Vision Conference (BMVC), p. 144 (2011). https:\/\/doi.org\/10.5244\/C.25","key":"19_CR21","DOI":"10.5244\/C.25"},{"doi-asserted-by":"publisher","unstructured":"Liu, J., Collins, R.T., Liu, Y.: Robust autocalibration for a surveillance camera network. In: IEEE Workshop on Applications of Computer Vision (WACV), pp. 433\u2013440 (2013). https:\/\/doi.org\/10.1109\/WACV.2013.6475051","key":"19_CR22","DOI":"10.1109\/WACV.2013.6475051"},{"doi-asserted-by":"publisher","unstructured":"Lowe, D.: Object recognition from local scale-invariant features. In: IEEE International Conference on Computer Vision (ICCV), vol. 2, pp. 1150\u20131157 (1999). https:\/\/doi.org\/10.1109\/ICCV.1999.790410","key":"19_CR23","DOI":"10.1109\/ICCV.1999.790410"},{"issue":"9","key":"19_CR24","doi-asserted-by":"publisher","first-page":"1513","DOI":"10.1109\/TPAMI.2006.178","volume":"28","author":"F Lv","year":"2006","unstructured":"Lv, F., Zhao, T., Nevatia, R.: Camera calibration from video of a walking human. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 28(9), 1513\u20131518 (2006). https:\/\/doi.org\/10.1109\/TPAMI.2006.178","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (PAMI)"},{"doi-asserted-by":"publisher","unstructured":"Maye, J., Furgale, P., Siegwart, R.: Self-supervised calibration for robotic systems. In: IEEE Intelligent Vehicles Symposium (IV), pp. 473\u2013480 (2013). https:\/\/doi.org\/10.1109\/IVS.2013.6629513","key":"19_CR25","DOI":"10.1109\/IVS.2013.6629513"},{"unstructured":"NVIDIA: Nvidia Jetson Xavier NX Developer Kit (2020). https:\/\/developer.nvidia.com\/embedded\/jetson-xavier-nx-devkit. Accessed25 Mar 2022","key":"19_CR26"},{"doi-asserted-by":"publisher","unstructured":"Olson, E.: AprilTag: a robust and flexible visual fiducial system. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 3400\u20133407 (2011). https:\/\/doi.org\/10.1109\/ICRA.2011.5979561","key":"19_CR27","DOI":"10.1109\/ICRA.2011.5979561"},{"doi-asserted-by":"publisher","unstructured":"Rehder, J., Nikolic, J., Schneider, T., Hinzmann, T., Siegwart, R.: Extending kalibr: calibrating the extrinsics of multiple IMUs and of individual axes. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 4304\u20134311 (2016). https:\/\/doi.org\/10.1109\/ICRA.2016.7487628","key":"19_CR28","DOI":"10.1109\/ICRA.2016.7487628"},{"doi-asserted-by":"publisher","unstructured":"Reinke, A., Camurri, M., Semini, C.: A factor graph approach to multi-camera extrinsic calibration on legged robots. In: IEEE International Conference on Robotic Computing (IRC), pp. 391\u2013394 (2019). https:\/\/doi.org\/10.1109\/IRC.2019.00071","key":"19_CR29","DOI":"10.1109\/IRC.2019.00071"},{"doi-asserted-by":"publisher","unstructured":"Tanke, J., Gall, J.: Iterative greedy matching for 3D human pose tracking from multiple views. In: DAGM German Conference on Pattern Recognition (GCPR) (2019). https:\/\/doi.org\/10.1007\/978-3-030-33676-9_38","key":"19_CR30","DOI":"10.1007\/978-3-030-33676-9_38"},{"doi-asserted-by":"publisher","unstructured":"Truong, A.M., Philips, W., Guan, J., Deligiannis, N., Abrahamyan, L.: Automatic extrinsic calibration of camera networks based on pedestrians. In: IEEE International Conference on Distributed Smart Cameras (ICDSC) (2019). https:\/\/doi.org\/10.1145\/3349801.3349802","key":"19_CR31","DOI":"10.1145\/3349801.3349802"},{"issue":"04","key":"19_CR32","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1109\/34.88573","volume":"13","author":"S Umeyama","year":"1991","unstructured":"Umeyama, S.: Least-squares estimation of transformation parameters between two point patterns. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 13(04), 376\u2013380 (1991). https:\/\/doi.org\/10.1109\/34.88573","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (PAMI)"},{"issue":"2","key":"19_CR33","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1134\/S1054661816020267","volume":"26","author":"S Wirtz","year":"2016","unstructured":"Wirtz, S., Paulus, D.: Evaluation of established line segment distance functions. Pattern Recogn. Image Anal. 26(2), 354\u2013359 (2016). https:\/\/doi.org\/10.1134\/S1054661816020267","journal-title":"Pattern Recogn. Image Anal."},{"issue":"11","key":"19_CR34","doi-asserted-by":"publisher","first-page":"1330","DOI":"10.1109\/34.888718","volume":"22","author":"Z Zhang","year":"2000","unstructured":"Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 22(11), 1330\u20131334 (2000). https:\/\/doi.org\/10.1109\/34.888718","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (PAMI)"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-16788-1_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,22]],"date-time":"2022-09-22T20:40:47Z","timestamp":1663879247000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-16788-1_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031167874","9783031167881"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-16788-1_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"20 September 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DAGM GCPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"DAGM German Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Konstanz","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","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":"27 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"44","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dagm2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/gcpr-vmv-2022.uni-konstanz.de\/","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"78","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":"37","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":"47% - 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":"2.6","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)"}}]}}