{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T15:01:04Z","timestamp":1761490864103,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":11,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,9,9]],"date-time":"2019-09-09T00:00:00Z","timestamp":1567987200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,9,9]]},"DOI":"10.1145\/3341162.3345581","type":"proceedings-article","created":{"date-parts":[[2019,9,11]],"date-time":"2019-09-11T16:16:21Z","timestamp":1568218581000},"page":"689-692","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["Activity recognition using ST-GCN with 3D motion data"],"prefix":"10.1145","author":[{"given":"Xin","family":"Cao","sequence":"first","affiliation":[{"name":"Tokyo Denki University, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wataru","family":"Kudo","sequence":"additional","affiliation":[{"name":"Tokyo Denki University, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chihiro","family":"Ito","sequence":"additional","affiliation":[{"name":"Tokyo Denki University, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masaki","family":"Shuzo","sequence":"additional","affiliation":[{"name":"Tokyo Denki University, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eisaku","family":"Maeda","sequence":"additional","affiliation":[{"name":"Tokyo Denki University, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,9,9]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Nurse Care Activity Recognition Challenge","author":"Inoue S.","year":"2019","unstructured":"S. Inoue , P. Lago , S. Takeda , A. Shamma , F. Faiz , N. Mairittha , and T. Mairittha , \" Nurse Care Activity Recognition Challenge ,\" 2019 . S. Inoue, P. Lago, S. Takeda, A. Shamma, F. Faiz, N. Mairittha, and T. Mairittha, \"Nurse Care Activity Recognition Challenge,\" 2019."},{"key":"e_1_3_2_1_2_1","first-page":"7","volume-title":"A Survey on Human Motion Analysis from Depth Data,\" In M","author":"Ye M.","year":"2013","unstructured":"M. Ye , Q. Zhang , L. Wang , J. Zhu , R. Yang , and J. Gall , \" A Survey on Human Motion Analysis from Depth Data,\" In M . Grzegorzek, C. Theobal, R. Koch, and A. Kolb (eds.) \"Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications,\" Lecture Notes in Computer Science, vol. 8200 , pp. 7 -- 45 , Springer , Berlin, Heidelberg, 2013 . M. Ye, Q. Zhang, L. Wang, J. Zhu, R. Yang, and J. Gall, \"A Survey on Human Motion Analysis from Depth Data,\" In M. Grzegorzek, C. Theobal, R. Koch, and A. Kolb (eds.) \"Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications,\" Lecture Notes in Computer Science, vol. 8200, pp. 7--45, Springer, Berlin, Heidelberg, 2013."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2015.11.019"},{"key":"e_1_3_2_1_4_1","volume-title":"Convolutional Pose Machines,\" arXiv preprint, arXiv:1602.00134","author":"Wei S.-E.","year":"2016","unstructured":"S.-E. Wei , V. Ramakrishna , T. Kanade , and Y. Sheikh , \" Convolutional Pose Machines,\" arXiv preprint, arXiv:1602.00134 , 2016 . S.-E. Wei, V. Ramakrishna, T. Kanade, and Y. Sheikh, \"Convolutional Pose Machines,\" arXiv preprint, arXiv:1602.00134, 2016."},{"key":"e_1_3_2_1_5_1","volume-title":"Co-Occurrence Feature Learning for Skeleton Based Action Recognition Using Regularized Deep LSTM Networks,\" arXiv preprint, arXiv:1603.07772","author":"Zhu W.","year":"2016","unstructured":"W. Zhu , C. Lan , J. Xing , W. Zeng , Y. Li , L. Shen , and X. Xie , \" Co-Occurrence Feature Learning for Skeleton Based Action Recognition Using Regularized Deep LSTM Networks,\" arXiv preprint, arXiv:1603.07772 , 2016 . W. Zhu, C. Lan, J. Xing, W. Zeng, Y. Li, L. Shen, and X. Xie, \"Co-Occurrence Feature Learning for Skeleton Based Action Recognition Using Regularized Deep LSTM Networks,\" arXiv preprint, arXiv:1603.07772, 2016."},{"key":"e_1_3_2_1_6_1","volume-title":"An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data,\" arXiv preprint, arXiv:1611.06067","author":"Song S.","year":"2016","unstructured":"S. Song , C. Lan , J. Xing , W. Zeng , and J. Liu , \" An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data,\" arXiv preprint, arXiv:1611.06067 , 2016 . S. Song, C. Lan, J. Xing, W. Zeng, and J. Liu, \"An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data,\" arXiv preprint, arXiv:1611.06067, 2016."},{"key":"e_1_3_2_1_7_1","volume-title":"arXiv:1801.07455","author":"Yan S.","year":"2018","unstructured":"S. Yan , Y. Xiong , D. Lin \" Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition,\" arXiv preprint , arXiv:1801.07455 , 2018 . S. Yan, Y. Xiong, D. Lin \"Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition,\" arXiv preprint, arXiv:1801.07455, 2018."},{"key":"e_1_3_2_1_8_1","first-page":"12026","volume-title":"IEEE CVPR","author":"Shi L.","year":"2019","unstructured":"L. Shi , Y. Zhang , J. Cheng , and H. Lu , \" Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition,\" Proc . IEEE CVPR , pp. 12026 -- 12035 , 2019 . L. Shi, Y. Zhang, J. Cheng, and H. Lu, \"Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition,\" Proc. IEEE CVPR, pp. 12026--12035, 2019."},{"key":"e_1_3_2_1_9_1","volume-title":"Dynamic Graph CNN for Learning on Point Clouds,\" arXiv preprint, arXiv:1801.07829","author":"Wang Y.","year":"2018","unstructured":"Y. Wang , Y. Sun , Z. Liu , S. E. Sarma , M. M. Bronstein , and J. M. Solomon , \" Dynamic Graph CNN for Learning on Point Clouds,\" arXiv preprint, arXiv:1801.07829 , 2018 . Y. Wang, Y. Sun, Z. Liu, S. E. Sarma, M. M. Bronstein, and J. M. Solomon, \"Dynamic Graph CNN for Learning on Point Clouds,\" arXiv preprint, arXiv:1801.07829, 2018."},{"key":"e_1_3_2_1_10_1","volume-title":"A Method for Stochastic Optimization,\" arXiv preprint, arXiv:1412.6980","author":"Diederik P.","year":"2014","unstructured":"P. Diederik and J, Lei. \"Adam : A Method for Stochastic Optimization,\" arXiv preprint, arXiv:1412.6980 , 2014 . P. Diederik and J, Lei. \"Adam: A Method for Stochastic Optimization,\" arXiv preprint, arXiv:1412.6980, 2014."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341162.3345577"}],"event":{"name":"UbiComp '19: The 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing","sponsor":["SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing","SIGCHI ACM Special Interest Group on Computer-Human Interaction"],"location":"London United Kingdom","acronym":"UbiComp '19"},"container-title":["Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3341162.3345581","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3341162.3345581","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:13:09Z","timestamp":1750201989000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3341162.3345581"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,9]]},"references-count":11,"alternative-id":["10.1145\/3341162.3345581","10.1145\/3341162"],"URL":"https:\/\/doi.org\/10.1145\/3341162.3345581","relation":{},"subject":[],"published":{"date-parts":[[2019,9,9]]},"assertion":[{"value":"2019-09-09","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}