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Our method consists of the following stages: a randomized decision forest classifier for image segmentation, a robust method for labeled dataset generation, a convolutional network for dense feature extraction, and finally an inverse kinematics stage for stable real-time pose recovery. As one possible application of this pipeline, we show state-of-the-art results for real-time puppeteering of a skinned hand-model.<\/jats:p>","DOI":"10.1145\/2629500","type":"journal-article","created":{"date-parts":[[2014,10,1]],"date-time":"2014-10-01T13:34:59Z","timestamp":1412170499000},"page":"1-10","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":637,"title":["Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks"],"prefix":"10.1145","volume":"33","author":[{"given":"Jonathan","family":"Tompson","sequence":"first","affiliation":[{"name":"New York University, New York, NY"}]},{"given":"Murphy","family":"Stein","sequence":"additional","affiliation":[{"name":"New York University, New York, NY"}]},{"given":"Yann","family":"Lecun","sequence":"additional","affiliation":[{"name":"New York University, New York, NY"}]},{"given":"Ken","family":"Perlin","sequence":"additional","affiliation":[{"name":"New York University, New York, NY"}]}],"member":"320","published-online":{"date-parts":[[2014,9,23]]},"reference":[{"key":"e_1_2_2_1_1","unstructured":"3GEAR. 2014. 3gear sytems hand-tracking development platform. http:\/\/www.threegear.com\/.  3GEAR. 2014. 3gear sytems hand-tracking development platform. http:\/\/www.threegear.com\/."},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/882262.882311"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33783-3_46"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.969114"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2207676.2208335"},{"key":"e_1_2_2_6_1","unstructured":"R. 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