Summary: Nearest Neighbor Search Methods for Handshape
Recognition
Michalis Potamias 1 and Vassilis Athitsos 2
1 Computer Science Department, Boston University
2 Computer Science and Engineering Department, University of Texas at Arlington
ABSTRACT
Gestures are an important modality for human­machine communi­
cation, and robust gesture recognition can be an important com­
ponent of intelligent homes and assistive environments in general.
An important aspect of gestures is handshape. Handshapes can
hold important information about the meaning of a gesture, for ex­
ample in sign languages, or about the intent of an action, for ex­
ample in manipulative gestures or in virtual reality interfaces. At
the same time, recognizing handshape can be a very challenging
task, because the same handshape can look very different in dif­
ferent images, depending on the 3D orientation of the hand and
the viewpoint of the camera. In this paper we examine a database
approach for handshape classification, whereby a large database
of tens of thousands of images is used to represent the wide vari­
ability of handshape appearance. Efficient and accurate indexing

Source: Athitsos, Vassilis - Department of Computer Science and Engineering, University of Texas at Arlington

Collections: Computer Technologies and Information Sciences