{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T07:26:22Z","timestamp":1742801182148},"publisher-location":"Berlin, Heidelberg","reference-count":19,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642408458"},{"type":"electronic","value":"9783642408465"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013]]},"DOI":"10.1007\/978-3-642-40846-5_30","type":"book-chapter","created":{"date-parts":[[2013,8,14]],"date-time":"2013-08-14T15:08:26Z","timestamp":1376492906000},"page":"294-303","source":"Crossref","is-referenced-by-count":4,"title":["Fall Detection Using Kinect Sensor and Fall Energy Image"],"prefix":"10.1007","author":[{"given":"Bogdan","family":"Kwolek","sequence":"first","affiliation":[]},{"given":"Michal","family":"Kepski","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"issue":"2","key":"30_CR1","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/s00138-010-0298-4","volume":"23","author":"M.A.R. Ahad","year":"2012","unstructured":"Ahad, M.A.R., Tan, J.K., Kim, H., Ishikawa, S.: Motion history image: its variants and applications. Mach. Vision Appl.\u00a023(2), 255\u2013281 (2012)","journal-title":"Mach. Vision Appl."},{"issue":"2","key":"30_CR2","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1016\/j.gaitpost.2006.09.012","volume":"26","author":"A. Bourke","year":"2007","unstructured":"Bourke, A., O\u2019Brien, J., Lyons, G.: Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm. Gait & Posture\u00a026(2), 194\u2013199 (2007)","journal-title":"Gait & Posture"},{"key":"30_CR3","doi-asserted-by":"crossref","unstructured":"Cleary, J., Trigg, L.: An instance-based learner using an entropic distance measure. In: Int. Conf. on Machine Learning, pp. 108\u2013114 (1995)","DOI":"10.1016\/B978-1-55860-377-6.50022-0"},{"key":"30_CR4","doi-asserted-by":"crossref","unstructured":"Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley (1992)","DOI":"10.1002\/0471200611"},{"key":"30_CR5","volume-title":"Data Mining: Practical machine learning tools and techniques","author":"T.M. Cover","year":"2005","unstructured":"Cover, T.M., Thomas, J.A.: Data Mining: Practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)","edition":"2"},{"issue":"5","key":"30_CR6","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1111\/j.1468-0394.2007.00438.x","volume":"24","author":"R. Cucchiara","year":"2007","unstructured":"Cucchiara, R., Prati, A., Vezzani, R.: A multi-camera vision system for fall detection and alarm generation. Expert Systems\u00a024(5), 334\u2013345 (2007)","journal-title":"Expert Systems"},{"key":"30_CR7","doi-asserted-by":"crossref","unstructured":"Foroughi, H., Naseri, A., Saberi, A., Yazdi, H.: An eigenspace-based approach for human fall detection using integrated time motion image and neural network. In: 9th Int. Conf. on Signal Processing, pp. 1499\u20131503 (2008)","DOI":"10.1109\/ICOSP.2008.4697417"},{"key":"30_CR8","volume-title":"Robot Vision","author":"B. Horn","year":"1986","unstructured":"Horn, B.: Robot Vision. The MIT Press, Cambridge (1986)"},{"key":"30_CR9","doi-asserted-by":"crossref","unstructured":"Jansen, B., Deklerck, R.: Context aware inactivity recognition for visual fall detection. In: Proc. IEEE Pervasive Health Conference and Workshops, pp. 1\u20134 (2006)","DOI":"10.1109\/PCTHEALTH.2006.361657"},{"key":"30_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1007\/978-3-642-29347-4_31","volume-title":"Artificial Intelligence and Soft Computing","author":"M. Kepski","year":"2012","unstructured":"Kepski, M., Kwolek, B., Austvoll, I.: Fuzzy inference-based reliable fall detection using Kinect and accelerometer. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2012, Part I. LNCS, vol.\u00a07267, pp. 266\u2013273. Springer, Heidelberg (2012)"},{"key":"30_CR11","series-title":"AISC","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1007\/978-3-319-00969-8_73","volume-title":"Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013","author":"M. Kepski","year":"2013","unstructured":"Kepski, M., Kwolek, B.: Human fall detection using Kinect sensor. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds.) CORES 2013. AISC, vol.\u00a0226, pp. 743\u2013752. Springer, Heidelberg (2013)"},{"key":"30_CR12","unstructured":"Labayrade, R., Aubert, D., Tarel, J.P.: Real time obstacle detection in stereovision on non flat road geometry through \u201dv-disparity\u201d representation. In: Intelligent Vehicle Symposium, vol.\u00a02, pp. 646\u2013651. IEEE (June 2002)"},{"issue":"1","key":"30_CR13","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.amepre.2004.09.015","volume":"8","author":"S.W. Marshall","year":"2005","unstructured":"Marshall, S.W., Runyan, C.W., Yang, J., Coyne-Beasley, T., Waller, A.E., Johnson, R.M., Perkis, D.: Prevalence of selected risk and protective factors for falls in the home. American J. of Preventive Medicine\u00a08(1), 95\u2013101 (2005)","journal-title":"American J. of Preventive Medicine"},{"key":"30_CR14","doi-asserted-by":"crossref","unstructured":"Mastorakis, G., Makris, D.: Fall detection system using Kinect\u2019s infrared sensor. J. of Real-Time Image Processing, 1\u201312 (2012)","DOI":"10.1007\/s11554-012-0246-9"},{"key":"30_CR15","unstructured":"Miaou, S.G., Sung, P.H., Huang, C.Y.: A customized human fall detection system using omni-camera images and personal information. Distributed Diagnosis and Home Healthcare, 39\u201342 (2006)"},{"key":"30_CR16","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.neucom.2011.09.037","volume":"100","author":"M. Mubashir","year":"2013","unstructured":"Mubashir, M., Shao, L., Seed, L.: A survey on fall detection: Principles and approaches. Neurocomputing 100, 144\u2013152 (2013), special issue: Behaviours in video","journal-title":"Neurocomputing"},{"key":"30_CR17","doi-asserted-by":"crossref","unstructured":"Noury, N., Fleury, A., Rumeau, P., Bourke, A., \u00d3Laighin, G., Rialle, V., Lundy, J.: Fall detection - principles and methods. In: Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, pp. 1663\u20131666 (2007)","DOI":"10.1109\/IEMBS.2007.4352627"},{"key":"30_CR18","doi-asserted-by":"crossref","unstructured":"Rougier, C., Meunier, J., St-Arnaud, A., Rousseau, J.: Monocular 3D head tracking to detect falls of elderly people. In: Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society, pp. 6384\u20136387 (2006)","DOI":"10.1109\/IEMBS.2006.4398921"},{"issue":"5","key":"30_CR19","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1109\/JSEN.2008.2012212","volume":"9","author":"G. Shi","year":"2009","unstructured":"Shi, G., Chan, C.S., Li, W.J., Leung, K.S., Zou, Y., Jin, Y.: Mobile human airbag system for fall protection using MEMS sensors and embedded SVM classifier. IEEE Sensors Journal\u00a09(5), 495\u2013503 (2009)","journal-title":"IEEE Sensors Journal"}],"container-title":["Lecture Notes in Computer Science","Hybrid Artificial Intelligent Systems"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-40846-5_30","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,3,3]],"date-time":"2022-03-03T19:25:38Z","timestamp":1646335538000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-40846-5_30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013]]},"ISBN":["9783642408458","9783642408465"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-40846-5_30","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2013]]}}}