Show simple item record

dc.contributor.authorAthitsos, Vassilisen_US
dc.contributor.authorSclaroff, Stanen_US
dc.date.accessioned2011-10-20T04:12:50Z
dc.date.available2011-10-20T04:12:50Z
dc.date.issued2003-04-01
dc.identifier.urihttps://hdl.handle.net/2144/1506
dc.description.abstractEstimation of 3D hand pose is useful in many gesture recognition applications, ranging from human-computer interaction to automated recognition of sign languages. In this paper, 3D hand pose estimation is treated as a database indexing problem. Given an input image of a hand, the most similar images in a large database of hand images are retrieved. The hand pose parameters of the retrieved images are used as estimates for the hand pose in the input image. Lipschitz embeddings of edge images into a Euclidean space are used to improve the efficiency of database retrieval. In order to achieve interactive retrieval times, similarity queries are initially performed in this Euclidean space. The paper describes ongoing work that focuses on how to best choose reference images, in order to improve retrieval accuracy.en_US
dc.description.sponsorshipNational Science Foundation (IIS-0208876, IIS-9912573, EIA-9809340)en_US
dc.language.isoen_US
dc.publisherBoston University Computer Science Departmenten_US
dc.relation.ispartofseriesBUCS Technical Reports;BUCS-TR-2003-010
dc.titleDatabase Indexing Methods for 3D Hand Pose Estimationen_US
dc.typeTechnical Reporten_US


This item appears in the following Collection(s)

Show simple item record