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Hand Part Classification Using Single Depth Images
[chapter]
2015
Lecture Notes in Computer Science
Hand pose recognition has received increasing attention as an area of HCI. Recently with the spreading of many low cost 3D camera, researches for understanding more natural gestures have been studied. In this paper we present a method for hand part classification and joint estimation from a single depth image. We apply random decision forests(RDF) for hand part classification. Foreground pixels in the hand image are estimated by RDF, which is called per-pixel classification. Then hand joints
doi:10.1007/978-3-319-16631-5_19
fatcat:4mmhtqjkovhmrd4y7le3qpgcj4