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Unlike other gamesourcing approaches, our method does not require a specific game, but runs alongside any gesture-based game using RGB-D sensors. The automatically generated datasets resulting from this approach contain joint estimates within a few pixel units of manually labeled data, and a gamesourced dataset created using a relatively small number of players, games, and locations performs as well as large-scale, manually annotated datasets when used as training data with recent learning-based human pose estimation methods for 2D images.<\/jats:p>","DOI":"10.1145\/2629465","type":"journal-article","created":{"date-parts":[[2015,4,3]],"date-time":"2015-04-03T20:29:44Z","timestamp":1428092984000},"page":"1-16","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["An Evaluation of Gamesourced Data for Human Pose Estimation"],"prefix":"10.1145","volume":"6","author":[{"given":"Scott","family":"Spurlock","sequence":"first","affiliation":[{"name":"University of North Carolina at Charlotte, Charlotte, NC, USA"}]},{"given":"Richard","family":"Souvenir","sequence":"additional","affiliation":[{"name":"University of North Carolina at Charlotte, Charlotte, NC, USA"}]}],"member":"320","published-online":{"date-parts":[[2015,3,31]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459303"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/997817.997857"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.5244\/C.23.3"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2009.167"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2008.4587468"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1162\/pres_a_00036"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2207676.2208303"},{"volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence. 1359--1364","year":"2007","author":"Ho Chien-Ju","key":"e_1_2_1_8_1"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2011.6130382"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.5244\/C.24.12"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995318"},{"volume-title":"Retrieved","year":"2012","author":"Hacks Kinect","key":"e_1_2_1_12_1"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2011.5980382"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2012.6288004"},{"key":"e_1_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Deva Ramanan. 2007. 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