{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T01:57:10Z","timestamp":1784080630222,"version":"3.55.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2018,10,30]],"date-time":"2018-10-30T00:00:00Z","timestamp":1540857600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100002920","name":"Research Grants Council, University Grants Committee","doi-asserted-by":"publisher","award":["14200618"],"award-info":[{"award-number":["14200618"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002920","name":"Research Grants Council, University Grants Committee","doi-asserted-by":"crossref","award":["14205914"],"award-info":[{"award-number":["14205914"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Shenzhen Science and Technology Innovation projects","award":["JCYJ20170413161616163"],"award-info":[{"award-number":["JCYJ20170413161616163"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J of Soc Robotics"],"published-print":{"date-parts":[[2019,4]]},"DOI":"10.1007\/s12369-018-0498-z","type":"journal-article","created":{"date-parts":[[2018,10,30]],"date-time":"2018-10-30T07:25:19Z","timestamp":1540884319000},"page":"219-234","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Skeleton-Based Human Action Recognition by Pose Specificity and Weighted Voting"],"prefix":"10.1007","volume":"11","author":[{"given":"Tingting","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0941-8003","authenticated-orcid":false,"given":"Jiaole","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seth","family":"Hutchinson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Max Q.-H.","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2018,10,30]]},"reference":[{"issue":"3","key":"498_CR1","doi-asserted-by":"publisher","first-page":"16:1","DOI":"10.1145\/1922649.1922653","volume":"43","author":"JK Aggarwal","year":"2011","unstructured":"Aggarwal JK, Ryoo MS (2011) Human activity analysis: a review. ACM Comput Surv 43(3):16:1\u201316:43","journal-title":"ACM Comput Surv"},{"issue":"Supplement C","key":"498_CR2","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.patrec.2014.04.011","volume":"48","author":"JK Aggarwal","year":"2014","unstructured":"Aggarwal JK, Xia L (2014) Human activity recognition from 3D data: a review. Pattern Recognit Lett 48(Supplement C):70\u201380","journal-title":"Pattern Recognit Lett"},{"issue":"1","key":"498_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TPAMI.2015.2439257","volume":"38","author":"BB Amor","year":"2016","unstructured":"Amor BB, Su J, Srivastava A (2016) Action recognition using rate-invariant analysis of skeletal shape trajectories. IEEE Trans Pattern Anal Mach Intell 38(1):1\u201313","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"3","key":"498_CR4","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/34.910878","volume":"23","author":"AF Bobick","year":"2001","unstructured":"Bobick AF, Davis JW (2001) The recognition of human movement using temporal templates. IEEE Trans Pattern Anal Mach Intell 23(3):257\u2013267","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"498_CR5","doi-asserted-by":"crossref","unstructured":"Chaaraoui AA, Climent-P\u00e9rez P, Fl\u00f3rez-Revuelta F (2012) An efficient approach for multi-view human action recognition based on bag-of-key-poses. In: International workshop on human behavior understanding, Springer, Berlin, pp 29\u201340","DOI":"10.1007\/978-3-642-34014-7_3"},{"issue":"3","key":"498_CR6","doi-asserted-by":"publisher","first-page":"786","DOI":"10.1016\/j.eswa.2013.08.009","volume":"41","author":"AA Chaaraoui","year":"2014","unstructured":"Chaaraoui AA, Padilla-L\u00f3pez JR, Climent-P\u00e9rez P, Fl\u00f3rez-Revuelta F (2014) Evolutionary joint selection to improve human action recognition with RGB-D devices. Expert Syst Appl 41(3):786\u2013794","journal-title":"Expert Syst Appl"},{"issue":"6","key":"498_CR7","doi-asserted-by":"publisher","first-page":"633","DOI":"10.1016\/j.cviu.2013.01.013","volume":"117","author":"JM Chaquet","year":"2013","unstructured":"Chaquet JM, Carmona EJ, Fern\u00e1ndez-Caballero A (2013) A survey of video datasets for human action and activity recognition. Comput Vis Image Underst 117(6):633\u2013659","journal-title":"Comput Vis Image Underst"},{"key":"498_CR8","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s11554-013-0370-1","volume":"12","author":"C Chen","year":"2016","unstructured":"Chen C, Liu K, Kehtarnavaz N (2016) Real-time human action recognition based on depth motion maps. J Real-Time Image Process 12:155\u2013163","journal-title":"J Real-Time Image Process"},{"key":"498_CR9","first-page":"21","volume":"2016","author":"E Cippitelli","year":"2016","unstructured":"Cippitelli E, Gasparrini S, Gambi E, Spinsante S (2016) A human activity recognition system using skeleton data from RGBD sensors. Intell Neurosci 2016:21\u201334","journal-title":"Intell Neurosci"},{"issue":"Supplement C","key":"498_CR10","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.jvcir.2015.12.006","volume":"35","author":"W Ding","year":"2016","unstructured":"Ding W, Liu K, Cheng F, Zhang J (2016) Learning hierarchical spatio-temporal pattern for human activity prediction. J Vis Commun Image Represent 35(Supplement C):103\u2013111","journal-title":"J Vis Commun Image Represent"},{"key":"498_CR11","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.image.2016.01.010","volume":"42","author":"W Ding","year":"2016","unstructured":"Ding W, Liu K, Fu X, Cheng F (2016) Profile hmms for skeleton-based human action recognition. Signal Process Image Commun 42:109\u2013119","journal-title":"Signal Process Image Commun"},{"key":"498_CR12","unstructured":"Du Y, Wang W, Wang L (2015) Hierarchical recurrent neural network for skeleton based action recognition. In: The IEEE conference on computer vision and pattern recognition (CVPR), IEEE, pp 1110\u20131118"},{"issue":"7","key":"498_CR13","doi-asserted-by":"publisher","first-page":"3010","DOI":"10.1109\/TIP.2016.2552404","volume":"25","author":"Y Du","year":"2016","unstructured":"Du Y, Fu Y, Wang L (2016) Representation learning of temporal dynamics for skeleton-based action recognition. IEEE Trans Image Process 25(7):3010\u20133022","journal-title":"IEEE Trans Image Process"},{"key":"498_CR14","unstructured":"Eweiwi A, Cheema MS, Bauckhage C, Gall J (2014) Efficient pose-based action recognition. In: Asian conference on computer vision (ACCV), Springer, Berlin, pp 428\u2013443"},{"key":"498_CR15","doi-asserted-by":"crossref","unstructured":"Faria DR, Premebida C, Nunes U (2014) A probabilistic approach for human everyday activities recognition using body motion from RGB-D images. In: The 23rd IEEE international symposium on robot and human interactive communication, IEEE, pp 732\u2013737","DOI":"10.1109\/ROMAN.2014.6926340"},{"key":"498_CR16","unstructured":"Gowayyed MA, Torki M, Hussein ME, El-Saban M (2013) Histogram of oriented displacements (hod): describing trajectories of human joints for action recognition. In: International joint conference on artificial intelligence, AAAI Press, pp 1351\u20131357"},{"key":"498_CR17","doi-asserted-by":"crossref","unstructured":"Gupta R, Chia AYS, Rajan D (2013) Human activities recognition using depth images. In: Proceedings of the 21st ACM international conference on multimedia, ACM, pp 283\u2013292","DOI":"10.1145\/2502081.2502099"},{"issue":"Supplement C","key":"498_CR18","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.image.2015.02.004","volume":"33","author":"M Jiang","year":"2015","unstructured":"Jiang M, Kong J, Bebis G, Huo H (2015) Informative joints based human action recognition using skeleton contexts. Signal Process Image Commun 33(Supplement C):29\u201340","journal-title":"Signal Process Image Commun"},{"key":"498_CR19","unstructured":"Joo SW, Chellappa R (2006) Attribute grammar-based event recognition and anomaly detection. In: 2006 conference on computer vision and pattern recognition workshop (CVPRW\u201906), IEEE, pp 107\u2013107"},{"issue":"2","key":"498_CR20","doi-asserted-by":"publisher","first-page":"88","DOI":"10.3390\/computers2020088","volume":"2","author":"SR Ke","year":"2013","unstructured":"Ke SR, Thuc HLU, Lee YJ, Hwang JN, Yoo JH, Choi KH (2013) A review on video-based human activity recognition. Computers 2(2):88\u2013131","journal-title":"Computers"},{"key":"498_CR21","doi-asserted-by":"crossref","unstructured":"Ke Y, Sukthankar R, Hebert M (2007) Spatio-temporal shape and flow correlation for action recognition. In: 2007 IEEE conference on computer vision and pattern recognition, IEEE, pp 1\u20138","DOI":"10.1109\/CVPR.2007.383512"},{"key":"498_CR22","doi-asserted-by":"crossref","unstructured":"Kitani KM, Sato Y, Sugimoto A (2007) Recovering the basic structure of human activities from a video-based symbol string. In: IEEE workshop on motion and video computing, 2007. WMVC\u201907, IEEE, pp 9\u20139","DOI":"10.1109\/WMVC.2007.34"},{"issue":"8","key":"498_CR23","doi-asserted-by":"publisher","first-page":"951","DOI":"10.1177\/0278364913478446","volume":"32","author":"HS Koppula","year":"2013","unstructured":"Koppula HS, Gupta R, Saxena A (2013) Learning human activities and object affordances from RGB-D videos. Int J Robot Res 32(8):951\u2013970","journal-title":"Int J Robot Res"},{"key":"498_CR24","unstructured":"Lai RYQ, Yuen PC, Lee KKW (2011) Motion capture data completion and denoising by singular value thresholding. In: Proceedings of Eurographics, pp 45\u201348"},{"key":"498_CR25","doi-asserted-by":"crossref","unstructured":"Li W, Zhang Z, Liu Z (2010) Action recognition based on a bag of 3D points. In: 2010 IEEE computer society conference on computer vision and pattern recognition\u2014workshops, IEEE, pp 9\u201314","DOI":"10.1109\/CVPRW.2010.5543273"},{"key":"498_CR26","doi-asserted-by":"crossref","unstructured":"Lublinerman R, Ozay N, Zarpalas D, Camps O (2006) Activity recognition from silhouettes using linear systems and model (in) validation techniques. In: 18th international conference on pattern recognition (ICPR\u201906), IEEE, vol\u00a01, pp 347\u2013350","DOI":"10.1109\/ICPR.2006.210"},{"issue":"5","key":"498_CR27","doi-asserted-by":"publisher","first-page":"1383","DOI":"10.1109\/TCYB.2013.2276433","volume":"43","author":"B Ni","year":"2013","unstructured":"Ni B, Pei Y, Moulin P, Yan S (2013) Multilevel depth and image fusion for human activity detection. IEEE Trans Cybern 43(5):1383\u20131394","journal-title":"IEEE Trans Cybern"},{"issue":"1","key":"498_CR28","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.jvcir.2013.04.007","volume":"25","author":"F Ofli","year":"2014","unstructured":"Ofli F, Chaudhry R, Kurillo G, Vidal R, Bajcsy R (2014) Sequence of the most informative joints (SMIJ): a new representation for human skeletal action recognition. J Vis Commun Image Represent 25(1):24\u201338","journal-title":"J Vis Commun Image Represent"},{"key":"498_CR29","doi-asserted-by":"publisher","first-page":"3","DOI":"10.3389\/fnbot.2015.00003","volume":"9","author":"GI Parisi","year":"2015","unstructured":"Parisi GI, Weber C, Wermter S (2015) Self-organizing neural integration of pose-motion features for human action recognition. Front Neurorobot 9:3","journal-title":"Front Neurorobot"},{"key":"498_CR30","doi-asserted-by":"crossref","unstructured":"Piyathilaka L, Kodagoda S (2013) Gaussian mixture based hmm for human daily activity recognition using 3D skeleton features. In: 2013 IEEE 8th conference on industrial electronics and applications (ICIEA), IEEE, pp 567\u2013572","DOI":"10.1109\/ICIEA.2013.6566433"},{"key":"498_CR31","unstructured":"Ryoo MS, Aggarwal JK (2006) Recognition of composite human activities through context-free grammar based representation. In: 2006 IEEE computer society conference on computer vision and pattern recognition (CVPR\u201906), IEEE, vol\u00a02, pp 1709\u20131718"},{"key":"498_CR32","unstructured":"Ryoo MS, Aggarwal JK (2009) Spatio-temporal relationship match: video structure comparison for recognition of complex human activities. In: 2009 IEEE 12th international conference on computer vision, IEEE, pp 1593\u20131600"},{"key":"498_CR33","doi-asserted-by":"crossref","unstructured":"Shan J, Akella S (2014) 3D human action segmentation and recognition using pose kinetic energy. In: 2014 IEEE international workshop on advanced robotics and its social impacts, IEEE, pp 69\u201375","DOI":"10.1109\/ARSO.2014.7020983"},{"issue":"1","key":"498_CR34","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1145\/2398356.2398381","volume":"56","author":"J Shotton","year":"2013","unstructured":"Shotton J, Sharp T, Kipman A, Fitzgibbon A, Finocchio M, Blake A, Cook M, Moore R (2013) Real-time human pose recognition in parts from single depth images. Commun ACM 56(1):116\u2013124","journal-title":"Commun ACM"},{"issue":"1","key":"498_CR35","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1108\/eb026526","volume":"28","author":"K Sparck Jones","year":"1972","unstructured":"Sparck Jones K (1972) A statistical interpretation of term specificity and its application in retrieval. J Doc 28(1):11\u201321","journal-title":"J Doc"},{"issue":"6","key":"498_CR36","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1016\/j.imavis.2012.03.006","volume":"30","author":"A Srivastava","year":"2012","unstructured":"Srivastava A, Turaga P, Kurtek S (2012) On advances in differential-geometric approaches for 2D and 3D shape analyses and activity recognition. Image Vis Comput 30(6):398\u2013416","journal-title":"Image Vis Comput"},{"key":"498_CR37","doi-asserted-by":"crossref","unstructured":"Sung J, Ponce C, Selman B, Saxena A (2012) Unstructured human activity detection from RGBD images. In: 2012 IEEE international conference on robotics and automation, IEEE, pp 842\u2013849","DOI":"10.1109\/ICRA.2012.6224591"},{"key":"498_CR38","doi-asserted-by":"crossref","unstructured":"Tao L, Vidal R (2015) Moving poselets: A discriminative and interpretable skeletal motion representation for action recognition. In: The IEEE international conference on computer vision (ICCV) workshops, pp 61\u201369","DOI":"10.1109\/ICCVW.2015.48"},{"issue":"2","key":"498_CR39","doi-asserted-by":"crossref","first-page":"247","DOI":"10.3233\/FI-2014-991","volume":"130","author":"TT Thanh","year":"2014","unstructured":"Thanh TT, Chen F, Kotani K, Le B (2014) Extraction of discriminative patterns from skeleton sequences for accurate action recognition. Fundam Inform 130(2):247\u2013261","journal-title":"Fundam Inform"},{"key":"498_CR40","doi-asserted-by":"crossref","unstructured":"Veeraraghavan A, Chellappa R, Roy-Chowdhury AK (2006) The function space of an activity. In: 2006 IEEE computer society conference on computer vision and pattern recognition (CVPR\u201906), IEEE, vol\u00a01, pp 959\u2013968","DOI":"10.1109\/CVPR.2006.304"},{"key":"498_CR41","doi-asserted-by":"crossref","unstructured":"Vemulapalli R, Arrate F, Chellappa R (2014) Human action recognition by representing 3D skeletons as points in a lie group. In: The IEEE conference on computer vision and pattern recognition (CVPR), IEEE, pp 588\u2013595","DOI":"10.1109\/CVPR.2014.82"},{"issue":"Supplement C","key":"498_CR42","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.neucom.2016.07.058","volume":"228","author":"Y Wang","year":"2017","unstructured":"Wang Y, Shi Y, Wei G (2017) A novel local feature descriptor based on energy information for human activity recognition. Neurocomputing 228(Supplement C):19\u201328","journal-title":"Neurocomputing"},{"issue":"1","key":"498_CR43","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.jvcir.2013.03.001","volume":"25","author":"X Yang","year":"2014","unstructured":"Yang X, Tian Y (2014) Effective 3D action recognition using eigenjoints. J Vis Commun Image Represent 25(1):2\u201311","journal-title":"J Vis Commun Image Represent"},{"key":"498_CR44","unstructured":"Yang X, Tian YL (2012) Eigenjoints-based action recognition using naive-bayes-nearest-neighbor. In: 2012 IEEE computer society conference on computer vision and pattern recognition workshops, IEEE, pp 14\u201319"},{"key":"498_CR45","doi-asserted-by":"crossref","unstructured":"Yu E, Aggarwal JK (2006) Detection of fence climbing from monocular video. In: 18th international conference on pattern recognition (ICPR\u201906), IEEE, vol\u00a01, pp 375\u2013378","DOI":"10.1109\/ICPR.2006.440"},{"issue":"4","key":"498_CR46","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4018\/ijcvip.2012100101","volume":"2","author":"C Zhang","year":"2012","unstructured":"Zhang C, Tian Y (2012) RGB-D camera-based daily living activity recognition. J Comput Vis Image Process 2(4):1\u20137","journal-title":"J Comput Vis Image Process"},{"issue":"3","key":"498_CR47","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1109\/TMM.2006.870735","volume":"8","author":"D Zhang","year":"2006","unstructured":"Zhang D, Gatica-Perez D, Bengio S, McCowan IA, Lathoud G (2006) Modeling individual and group actions in meetings with layered hmms. IEEE Trans Multimed 8(3):509\u2013520","journal-title":"IEEE Trans Multimed"},{"issue":"2","key":"498_CR48","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/MMUL.2012.24","volume":"19","author":"Z Zhang","year":"2012","unstructured":"Zhang Z (2012) Microsoft kinect sensor and its effect. IEEE MultiMed 19(2):4\u201310","journal-title":"IEEE MultiMed"},{"key":"498_CR49","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.image.2016.01.003","volume":"42","author":"G Zhu","year":"2016","unstructured":"Zhu G, Zhang L, Shen P, Song J (2016) Human action recognition using multi-layer codebooks of key poses and atomic motions. Signal Process Image Commun 42:19\u201330","journal-title":"Signal Process Image Commun"},{"issue":"2","key":"498_CR50","doi-asserted-by":"publisher","first-page":"161","DOI":"10.3390\/s16020161","volume":"16","author":"G Zhu","year":"2016","unstructured":"Zhu G, Zhang L, Shen P, Song J (2016) An online continuous human action recognition algorithm based on the kinect sensor. Sensors 16(2):161","journal-title":"Sensors"},{"issue":"8","key":"498_CR51","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1016\/j.imavis.2014.04.005","volume":"32","author":"Y Zhu","year":"2014","unstructured":"Zhu Y, Chen W, Guo G (2014) Evaluating spatiotemporal interest point features for depth-based action recognition. Image and Vis Comput 32(8):453\u2013464","journal-title":"Image and Vis Comput"}],"container-title":["International Journal of Social Robotics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12369-018-0498-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s12369-018-0498-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12369-018-0498-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,12,18]],"date-time":"2019-12-18T03:48:11Z","timestamp":1576640891000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s12369-018-0498-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,30]]},"references-count":51,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,4]]}},"alternative-id":["498"],"URL":"https:\/\/doi.org\/10.1007\/s12369-018-0498-z","relation":{},"ISSN":["1875-4791","1875-4805"],"issn-type":[{"value":"1875-4791","type":"print"},{"value":"1875-4805","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,10,30]]},"assertion":[{"value":"11 October 2018","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 October 2018","order":2,"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 conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}]}}