{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T20:48:20Z","timestamp":1761598100366,"version":"3.37.3"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T00:00:00Z","timestamp":1565049600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T00:00:00Z","timestamp":1565049600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J CARS"],"published-print":{"date-parts":[[2019,11]]},"DOI":"10.1007\/s11548-019-02044-7","type":"journal-article","created":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T09:04:41Z","timestamp":1565082281000},"page":"1871-1879","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Fusing information from multiple 2D depth cameras for 3D human pose estimation in the operating room"],"prefix":"10.1007","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3963-7052","authenticated-orcid":false,"given":"Lasse","family":"Hansen","sequence":"first","affiliation":[]},{"given":"Marlin","family":"Siebert","sequence":"additional","affiliation":[]},{"given":"Jasper","family":"Diesel","sequence":"additional","affiliation":[]},{"given":"Mattias P.","family":"Heinrich","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,8,6]]},"reference":[{"key":"2044_CR1","doi-asserted-by":"crossref","unstructured":"Achilles F, Ichim AE, Coskun H, Tombari F, Noachtar S, Navab N (2016) Patient mocap: human pose estimation under blanket occlusion for hospital monitoring applications. In: Proceedings of the international conference on medical image computing and computer-assisted intervention (MICCAI). Springer, pp 491\u2013499","DOI":"10.1007\/978-3-319-46720-7_57"},{"key":"2044_CR2","doi-asserted-by":"crossref","unstructured":"Andriluka M, Iqbal U, Insafutdinov E, Pishchulin L, Milan A, Gall J, Schiele B (2018) Posetrack: a benchmark for human pose estimation and tracking. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5167\u20135176","DOI":"10.1109\/CVPR.2018.00542"},{"key":"2044_CR3","doi-asserted-by":"crossref","unstructured":"Andriluka M, Pishchulin L, Gehler P, Schiele B (2014) 2D human pose estimation: new benchmark and state of the art analysis. In: Proceedings of the conference on computer vision and pattern recognition (CVPR), pp 3686\u20133693","DOI":"10.1109\/CVPR.2014.471"},{"key":"2044_CR4","doi-asserted-by":"crossref","unstructured":"Andriluka M, Roth S, Schiele B (2009) Pictorial structures revisited: people detection and articulated pose estimation. In: Proceedings of the conference on computer vision and pattern recognition (CVPR). IEEE, pp 1014\u20131021","DOI":"10.1109\/CVPR.2009.5206754"},{"issue":"7","key":"2044_CR5","doi-asserted-by":"publisher","first-page":"1035","DOI":"10.1007\/s00138-016-0792-4","volume":"27","author":"V Belagiannis","year":"2016","unstructured":"Belagiannis V, Wang X, Shitrit HBB, Hashimoto K, Stauder R, Aoki Y, Kranzfelder M, Schneider A, Fua P, Ilic S, Feussner H, Navab N (2016) Parsing human skeletons in an operating room. Mach Vis Appl (MVA) 27(7):1035\u20131046","journal-title":"Mach Vis Appl (MVA)"},{"key":"2044_CR6","doi-asserted-by":"crossref","unstructured":"Cao Z, Simon T, Wei S.E, Sheikh Y (2017) Realtime multi-person 2d pose estimation using part affinity fields. In: Proceedings of the conference on computer vision and pattern recognition (CVPR), pp 7291\u20137299","DOI":"10.1109\/CVPR.2017.143"},{"key":"2044_CR7","first-page":"1","volume":"6","author":"K Chen","year":"2018","unstructured":"Chen K, Gabriel P, Alasfour A, Gong C, Doyle WK, Devinsky O, Friedman D, Dugan P, Melloni L, Thesen T, Gonda D, Sattar S, Wang S, Gilja V (2018) Patient-specific pose estimation in clinical environments. J Transl Eng Health Med (JTEHM) 6:1\u201311","journal-title":"J Transl Eng Health Med (JTEHM)"},{"key":"2044_CR8","doi-asserted-by":"crossref","unstructured":"Chen Y, Wang Z, Peng Y, Zhang Z, Yu G, Sun J (2018) Cascaded pyramid network for multi-person pose estimation. In: Proceedings of the conference on computer vision and pattern recognition (CVPR), pp 7103\u20137112","DOI":"10.1109\/CVPR.2018.00742"},{"key":"2044_CR9","unstructured":"Dietz A, Schr\u00f6der S, P\u00f6sch A, Frank K, Reithmeier E (2016) Contactless surgery light control based on 3D gesture recognition. In: GCAI, pp 138\u2013146"},{"key":"2044_CR10","doi-asserted-by":"crossref","unstructured":"Felzenszwalb P, McAllester D, Ramanan D (2008) A discriminatively trained, multiscale, deformable part model. In: Proceedings of the conference on computer vision and pattern recognition (CVPR). IEEE, pp 1\u20138","DOI":"10.1109\/CVPR.2008.4587597"},{"key":"2044_CR11","doi-asserted-by":"crossref","unstructured":"Girshick R, Shotton J, Kohli P, Criminisi A, Fitzgibbon A (2011) Efficient regression of general-activity human poses from depth images. In: Proceedings of the international conference on computer vision (ICCV). IEEE, pp 415\u2013422","DOI":"10.1109\/ICCV.2011.6126270"},{"key":"2044_CR12","doi-asserted-by":"crossref","unstructured":"Hansen L, Diesel J, Heinrich MP (2019) Regularized landmark detection with CAEs for human pose estimation in the operating room. In: Bildverarbeitung f\u00fcr die Medizin (BVM). Springer, pp 178\u2013183","DOI":"10.1007\/978-3-658-25326-4_38"},{"key":"2044_CR13","doi-asserted-by":"crossref","unstructured":"Haque A, Peng B, Luo Z, Alahi A, Yeung S, Fei-Fei L (2016) Towards viewpoint invariant 3D human pose estimation. In: Proccedings of the European conference on computer vision (ECCV). Springer, pp 160\u2013177","DOI":"10.1007\/978-3-319-46448-0_10"},{"key":"2044_CR14","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the conference on computer vision and pattern recognition (CVPR), pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"issue":"7","key":"2044_CR15","doi-asserted-by":"publisher","first-page":"1325","DOI":"10.1109\/TPAMI.2013.248","volume":"36","author":"C Ionescu","year":"2014","unstructured":"Ionescu C, Papava D, Olaru V, Sminchisescu C (2014) Human3.6m: large scale datasets and predictive methods for 3D human sensing in natural environments. Trans Pattern Anal Mach Intell (TPAMI) 36(7):1325\u20131339","journal-title":"Trans Pattern Anal Mach Intell (TPAMI)"},{"issue":"5","key":"2044_CR16","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1145\/2447976.2447993","volume":"56","author":"MG Jacob","year":"2013","unstructured":"Jacob MG, Li YT, Akingba GA, Wachs JP (2013) Collaboration with a robotic scrub nurse. Commun ACM 56(5):68\u201375","journal-title":"Commun ACM"},{"key":"2044_CR17","doi-asserted-by":"crossref","unstructured":"Jung HY, Suh Y, Moon G, Lee KM (2016) A sequential approach to 3d human pose estimation: separation of localization and identification of body joints. In: Proceedings of the European conference on computer vision (ECCV). Springer, pp 747\u2013761","DOI":"10.1007\/978-3-319-46454-1_45"},{"key":"2044_CR18","doi-asserted-by":"crossref","unstructured":"Kadkhodamohammadi A, Gangi A, de\u00a0Mathelin M, Padoy N (2017) A multi-view RGB-D approach for human pose estimation in operating rooms. In: Proceedings of the winter conference on applications of computer vision (WACV). IEEE, pp 363\u2013372","DOI":"10.1109\/WACV.2017.47"},{"key":"2044_CR19","unstructured":"Kadkhodamohammadi A, Padoy N (2018) A generalizable approach for multi-view 3D human pose regression. \narXiv:1804.10462"},{"key":"2044_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11263-018-1066-6","volume":"126","author":"I Katircioglu","year":"2018","unstructured":"Katircioglu I, Tekin B, Salzmann M, Lepetit V, Fua P (2018) Learning latent representations of 3D human pose with deep neural networks. Int J Comput Vis (IJCV) 126:1\u201316","journal-title":"Int J Comput Vis (IJCV)"},{"key":"2044_CR21","unstructured":"Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. \narXiv:1412.6980"},{"key":"2044_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/JTEHM.2019.2892970","volume":"7","author":"S Liu","year":"2019","unstructured":"Liu S, Yin Y, Ostadabbas S (2019) In-bed pose estimation: deep learning with shallow dataset. IEEE J Transl Eng Health Med 7:1\u201312. \nhttps:\/\/doi.org\/10.1109\/JTEHM.2019.2892970","journal-title":"IEEE J Transl Eng Health Med"},{"key":"2044_CR23","doi-asserted-by":"crossref","unstructured":"Liu W, Anguelov D, Erhan D, Szegedy C, Reed S, Fu CY, Berg AC (2016) Ssd: single shot multibox detector. In: Proceedings of the European conference on computer vision (ECCV). Springer, pp 21\u201337","DOI":"10.1007\/978-3-319-46448-0_2"},{"issue":"12","key":"2044_CR24","doi-asserted-by":"publisher","first-page":"1282","DOI":"10.1001\/jama.2018.9222","volume":"320","author":"TH McCoy","year":"2018","unstructured":"McCoy TH, Perlis RH (2018) Temporal trends and characteristics of reportable health data breaches, 2010\u20132017. JAMA 320(12):1282\u20131284","journal-title":"JAMA"},{"key":"2044_CR25","unstructured":"Moon G, Yong\u00a0Chang J, Mu\u00a0Lee K (2018) V2v-posenet: voxel-to-voxel prediction network for accurate 3D hand and human pose estimation from a single depth map. In: Proceedings of the conference on computer vision and pattern recognition (CVPR), pp 5079\u20135088"},{"key":"2044_CR26","unstructured":"Mori G, Ren X, Efros AA, Malik J (2018) Recovering human body configurations: combining segmentation and recognition. In: Proceedings of the conference on computer vision and pattern recognition (CVPR), vol.\u00a02. IEEE (2004)"},{"key":"2044_CR27","unstructured":"Newell A, Huang Z, Deng J (2017) Associative embedding: end-to-end learning for joint detection and grouping. In: Guyon I, Luxburg UV, Bengio S, Wallach H, Fergus R, Vishwanathan S, Garnett R (eds) Advances in neural information processing systems 30, Curran Associates, Inc., pp 2277\u20132287. \nhttp:\/\/papers.nips.cc\/paper\/6822-associative-embedding-end-to-end-learning-for-joint-detection-and-grouping.pdf"},{"key":"2044_CR28","doi-asserted-by":"crossref","unstructured":"Newell A, Yang K, Deng J (2016) Stacked hourglass networks for human pose estimation. In: Proceedings of the European conference on computer vision (ECCV). Springer, pp 483\u2013499","DOI":"10.1007\/978-3-319-46484-8_29"},{"issue":"3","key":"2044_CR29","doi-asserted-by":"publisher","first-page":"632","DOI":"10.1016\/j.media.2010.10.001","volume":"16","author":"N Padoy","year":"2012","unstructured":"Padoy N, Blum T, Ahmadi SA, Feussner H, Berger MO, Navab N (2012) Statistical modeling and recognition of surgical workflow. Med Image Anal 16(3):632\u2013641","journal-title":"Med Image Anal"},{"key":"2044_CR30","unstructured":"Paszke A, Gross S, Chintala S, Chanan G, Yang E, DeVito Z, Lin Z, Desmaison A, Antiga L, Lerer A (2017) Automatic differentiation in pytorch. In: Advances in neural information processing systems workshop (NIPS-W)"},{"key":"2044_CR31","doi-asserted-by":"crossref","unstructured":"Pavlakos G, Zhou X, Derpanis KG, Daniilidis K (2017) Coarse-to-fine volumetric prediction for single-image 3D human pose. In: Proceedings of the conference on computer vision and pattern recognition (CVPR). IEEE, pp 1263\u20131272","DOI":"10.1109\/CVPR.2017.139"},{"key":"2044_CR32","unstructured":"Ren S, He K, Girshick R, Sun J (2015) Faster R-CNN: towards real-time object detection with region proposal networks. In: Advances in neural information processing systems (NIPS), pp 91\u201399"},{"key":"2044_CR33","doi-asserted-by":"crossref","unstructured":"Shotton J, Fitzgibbon A, Cook M, Sharp T, Finocchio M, Moore R, Kipman A, Blake A (2011) Real-time human pose recognition in parts from single depth images. In: Proceedings of the conference on computer vision and pattern recognition (CVPR). IEEE, pp 1297\u20131304","DOI":"10.1109\/CVPR.2011.5995316"},{"issue":"2","key":"2044_CR34","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1016\/j.jss.2015.03.097","volume":"197","author":"MR Silas","year":"2015","unstructured":"Silas MR, Grassia P, Langerman A (2015) Video recording of the operating room-is anonymity possible? J Surg Res 197(2):272\u2013276","journal-title":"J Surg Res"},{"key":"2044_CR35","unstructured":"Srivastav V, Issenhuth T, Kadkhodamohammadi A, de\u00a0Mathelin M, Gangi A, Padoy N (2018) MVOR: a multi-view RGB-D operating room dataset for 2D and 3D human pose estimation. \narXiv:1808.08180"},{"key":"2044_CR36","doi-asserted-by":"crossref","unstructured":"Toshev A, Szegedy C (2014) Deeppose: human pose estimation via deep neural networks. In: Proceedings of the conference on computer vision and pattern recognition (CVPR), pp 1653\u20131660","DOI":"10.1109\/CVPR.2014.214"},{"issue":"Dec","key":"2044_CR37","first-page":"3371","volume":"11","author":"P Vincent","year":"2010","unstructured":"Vincent P, Larochelle H, Lajoie I, Bengio Y, Manzagol PA (2010) Stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion. J Mach Learn Res (JMLR) 11(Dec):3371\u20133408","journal-title":"J Mach Learn Res (JMLR)"},{"key":"2044_CR38","doi-asserted-by":"crossref","unstructured":"Xiao B, Wu H, Wei, Y (2018) Simple baselines for human pose estimation and tracking. In: Proceedings of the European conference on computer vision (ECCV)","DOI":"10.1007\/978-3-030-01231-1_29"},{"issue":"1","key":"2044_CR39","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1007\/s11263-012-0532-9","volume":"100","author":"A Yao","year":"2012","unstructured":"Yao A, Gall J, Van Gool L (2012) Coupled action recognition and pose estimation from multiple views. Int J Comput Vis 100(1):16\u201337","journal-title":"Int J Comput Vis"},{"key":"2044_CR40","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1016\/j.sbspro.2013.10.293","volume":"97","author":"YA Yusoff","year":"2013","unstructured":"Yusoff YA, Basori AH, Mohamed F (2013) Interactive hand and arm gesture control for 2D medical image and 3D volumetric medical visualization. Proc Soc Behav Sci 97:723\u2013729","journal-title":"Proc Soc Behav Sci"}],"container-title":["International Journal of Computer Assisted Radiology and Surgery"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-019-02044-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11548-019-02044-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-019-02044-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,4]],"date-time":"2020-08-04T23:28:33Z","timestamp":1596583713000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11548-019-02044-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,6]]},"references-count":40,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2019,11]]}},"alternative-id":["2044"],"URL":"https:\/\/doi.org\/10.1007\/s11548-019-02044-7","relation":{},"ISSN":["1861-6410","1861-6429"],"issn-type":[{"type":"print","value":"1861-6410"},{"type":"electronic","value":"1861-6429"}],"subject":[],"published":{"date-parts":[[2019,8,6]]},"assertion":[{"value":"16 February 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 August 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no relevant conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Statement of informed consent was not applicable since the manuscript does not contain any participants\u2019 data.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}