{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T06:12:04Z","timestamp":1744179124452,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030177706"},{"type":"electronic","value":"9783030177713"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-17771-3_14","type":"book-chapter","created":{"date-parts":[[2019,4,30]],"date-time":"2019-04-30T13:06:30Z","timestamp":1556629590000},"page":"169-182","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Real-Time Human Body Pose Estimation for In-Car Depth Images"],"prefix":"10.1007","author":[{"given":"Helena R.","family":"Torres","sequence":"first","affiliation":[]},{"given":"Bruno","family":"Oliveira","sequence":"additional","affiliation":[]},{"given":"Jaime","family":"Fonseca","sequence":"additional","affiliation":[]},{"given":"Sandro","family":"Queir\u00f3s","sequence":"additional","affiliation":[]},{"given":"Jo\u00e3o","family":"Borges","sequence":"additional","affiliation":[]},{"given":"N\u00e9lson","family":"Rodrigues","sequence":"additional","affiliation":[]},{"given":"Victor","family":"Coelho","sequence":"additional","affiliation":[]},{"given":"Johannes","family":"Pallauf","sequence":"additional","affiliation":[]},{"given":"Jos\u00e9","family":"Brito","sequence":"additional","affiliation":[]},{"given":"Jos\u00e9","family":"Mendes","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,4,16]]},"reference":[{"key":"14_CR1","doi-asserted-by":"crossref","unstructured":"Levinson, J., et al.: Towards fully autonomous driving: systems and algorithms. In: IEEE Intelligent Vehicles Symposium, pp. 163\u2013168 (2011)","DOI":"10.1109\/IVS.2011.5940562"},{"key":"14_CR2","unstructured":"Banks, V.A., Stanton, N.A.: Analysis of driver roles: modelling the changing role of the driver in automated driving systems using EAST analysis of driver roles: modelling the changing role of the driver in automated driving systems using EAST. Theor. Issues Ergon. Sci. 1\u201317 (2017)"},{"issue":"4","key":"14_CR3","doi-asserted-by":"publisher","first-page":"719","DOI":"10.1016\/j.jmsy.2014.07.011","volume":"33","author":"D Regazzoni","year":"2014","unstructured":"Regazzoni, D., De Vecchi, G., Rizzi, C.: RGB cams vs RGB-D sensors: Low cost motion capture technologies performances and limitations. J. Manuf. Syst. 33(4), 719\u2013728 (2014)","journal-title":"J. Manuf. Syst."},{"issue":"5","key":"14_CR4","doi-asserted-by":"publisher","first-page":"1314","DOI":"10.1109\/TCYB.2013.2276144","volume":"43","author":"L Shao","year":"2013","unstructured":"Shao, L., Han, J., Xu, D., Shotton, J.: Computer vision for RGB-D sensors: Kinect and its applications. IEEE Trans. Cybern. 43(5), 1314\u20131317 (2013)","journal-title":"IEEE Trans. Cybern."},{"key":"14_CR5","doi-asserted-by":"crossref","unstructured":"Cao, Z., Simon, T., Wei, S.-E., Sheikh, Y.: Realtime multi-person 2D pose estimation using part affinity fields. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7291\u20137299 (2017)","DOI":"10.1109\/CVPR.2017.143"},{"issue":"5","key":"14_CR6","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1145\/2830565","volume":"59","author":"Stephen M. Casner","year":"2016","unstructured":"Casner, B.Y.S.M., Hutchins, E.L., Norman, D.O.N., Promise, A.C.: The challenges of partially automated driving. In: Communications of the ACM, pp. 70\u201377 (2016)","journal-title":"Communications of the ACM"},{"key":"14_CR7","first-page":"167","volume":"77","author":"DJ Fagnant","year":"2015","unstructured":"Fagnant, D.J., Kockelman, K.: Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations. Transp. Res. Part A 77, 167\u2013181 (2015)","journal-title":"Transp. Res. Part A"},{"key":"14_CR8","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1016\/j.trc.2016.06.015","volume":"69","author":"R Krueger","year":"2016","unstructured":"Krueger, R., Rashidi, T.H., Rose, J.M.: Preferences for shared autonomous vehicles. Transp. Res. Part C Emerg. Technol. 69, 343\u2013355 (2016)","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"14_CR9","doi-asserted-by":"crossref","unstructured":"Demirdjian, D., Varri, C.: Driver pose estimation with 3D Time-of-Flight sensor. In: 2009 IEEE Workshop on Computational Intelligence in Vehicles and Vehicular Systems, pp. 16\u201322 (2009)","DOI":"10.1109\/CIVVS.2009.4938718"},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Ye, M., Yang, R.: Real-time simultaneous pose and shape estimation for articulated objects using a single depth camera. In: CVPR 2014, pp. 2345\u20132352 (2014)","DOI":"10.1109\/CVPR.2014.301"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Ye, M., Wang, X., Yang, R., Ren, L., Pollefeys, M.: Accurate 3D pose estimation from a single depth image. In: 2011 International Conference on Computer Vision, pp. 731\u2013738 (2011)","DOI":"10.1109\/ICCV.2011.6126310"},{"issue":"8","key":"14_CR12","doi-asserted-by":"publisher","first-page":"1569","DOI":"10.1109\/TPAMI.2015.2502582","volume":"38","author":"M Sigalas","year":"2016","unstructured":"Sigalas, M., Pateraki, M., Trahanias, P.: Full-body pose tracking? The top view reprojection approach. IEEE Trans. Pattern Anal. Mach. Intell. 38(8), 1569\u20131582 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"1","key":"14_CR13","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1145\/2398356.2398381","volume":"56","author":"J Shotton","year":"2013","unstructured":"Shotton, J., et al.: Real-time human pose recognition in parts from single depth images. Commun. ACM 56(1), 116\u2013124 (2013)","journal-title":"Commun. ACM"},{"issue":"12","key":"14_CR14","doi-asserted-by":"publisher","first-page":"2821","DOI":"10.1109\/TPAMI.2012.241","volume":"35","author":"J Shotton","year":"2013","unstructured":"Shotton, J., et al.: Efficient human pose estimation from single depth images. IEEE Trans. Pattern Anal. Mach. Intell. 35(12), 2821\u20132840 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Tsai, M.-H., Chen, K.-H., Lin, I.-C.: Real-time upper body pose estimation from depth images. In: 2015 IEEE International Conference on Image Processing (ICIP), pp. 2234\u20132238 (2015)","DOI":"10.1109\/ICIP.2015.7351198"},{"issue":"1","key":"14_CR16","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.jvcir.2013.03.011","volume":"25","author":"K Buys","year":"2014","unstructured":"Buys, K., Cagniart, C., Baksheev, A., De Laet, T., De Schutter, J., Pantofaru, C.: An adaptable system for RGB-D based human body detection and pose estimation. J. Vis. Commun. Image Represent. 25(1), 39\u201352 (2014)","journal-title":"J. Vis. Commun. Image Represent."},{"key":"14_CR17","first-page":"160","volume-title":"Towards Viewpoint Invariant 3D Human Pose Estimation","author":"A Haque","year":"2016","unstructured":"Haque, A., Peng, B., Luo, Z., Alahi, A., Yeung, S., Fei-Fei, L.: Towards Viewpoint Invariant 3D Human Pose Estimation, pp. 160\u2013177. Springer, Cham (2016)"},{"key":"14_CR18","doi-asserted-by":"crossref","unstructured":"Belagiannis, V., Zisserman, A., Group, V.G.: Recurrent human pose estimation. In: 12th IEEE International Conference on Automatic Face & Gesture Recognition (2017)","DOI":"10.1109\/FG.2017.64"},{"key":"14_CR19","unstructured":"Chu, X., Yang, W., Ouyang, W., Ma, C., Yuille, A.L., Wang, X.: Multi-context attention for human pose estimation, pp. 1831\u20131840. arXiv preprint \n                    arXiv:1702.07432"},{"key":"14_CR20","doi-asserted-by":"crossref","unstructured":"He, K, Gkioxari, G, Doll\u00e1r, P, Girshick, R.: Mask R-CNN. In: Computer Vision (ICCV), pp. 2980\u20132988 (2017)","DOI":"10.1109\/ICCV.2017.322"},{"key":"14_CR21","unstructured":"Chen, X., Yuille, A.: Articulated pose estimation by a graphical model with image dependent pairwise relations. In: Conference on Neural Information Processing Systems, pp. 1\u20139 (2014)"},{"key":"14_CR22","unstructured":"Tompson, J., Jain, A., Lecun, Y., Bregler, C.: Joint training of a convolutional network and a graphical model for human pose estimation. In: Advances in Neural Information Processing Systems, pp. 1\u20139 (2014)"},{"key":"14_CR23","unstructured":"Fan, X., Zheng, K., Lin, Y., Wang, S.: Combining Local Appearance and Holistic View: Dual-Source Deep Neural Networks for Human Pose Estimation"},{"key":"14_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1007\/978-3-319-46478-7_44","volume-title":"Computer Vision \u2013 ECCV 2016","author":"A Bulat","year":"2016","unstructured":"Bulat, A., Tzimiropoulos, G.: Human pose estimation via convolutional part heatmap regression. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9911, pp. 717\u2013732. Springer, Cham (2016). \n                    https:\/\/doi.org\/10.1007\/978-3-319-46478-7_44"},{"key":"14_CR25","doi-asserted-by":"crossref","unstructured":"Borghi, G.: POSEidon: Face-from-depth for driver pose estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5494\u20135503 (2017)","DOI":"10.1109\/CVPR.2017.583"},{"key":"14_CR26","unstructured":"Murthy, P., Kovalenko, O., Elhayek, A., Gava, C., Stricker, D.: 3D Human Pose Tracking inside Car using Single RGB Spherical Camera (2017)"},{"key":"14_CR27","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: Computer Vision and Pattern Recognition, pp. 1\u201314 (2014)"}],"container-title":["IFIP Advances in Information and Communication Technology","Technological Innovation for Industry and Service Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-17771-3_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,20]],"date-time":"2019-05-20T14:34:25Z","timestamp":1558362865000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-17771-3_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030177706","9783030177713"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-17771-3_14","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"type":"print","value":"1868-4238"},{"type":"electronic","value":"1868-422X"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"16 April 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DoCEIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Doctoral Conference on Computing, Electrical and Industrial Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Costa de Caparica","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 May 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 May 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"doceis2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/doceis.dee.fct.unl.pt\/index.html","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"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"73","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"36","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"49% - 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"}},{"value":"3.17","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"n\/a","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}