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A Similarity Measure for Vision-Based Sign Recognition
 

Summary: A Similarity Measure for Vision-Based Sign
Recognition
Haijing Wang, Alexandra Stefan, and Vassilis Athitsos
Computer Science and Engineering Department, University of Texas at Arlington
Arlington, Texas, USA
Abstract. When we encounter an English word that we do not understand, we
can look it up in a dictionary. However, when an American Sign Language
(ASL) user encounters an unknown sign, looking up the meaning of that sign is
not a straightforward process. It has been recently proposed that this problem
can be addressed using a computer vision system that helps users look up the
meaning of a sign. In that approach, sign lookup can be treated as a video data-
base retrieval problem. When the user encounters an unknown sign, the user
provides a video example of that sign as a query, so as to retrieve the most simi-
lar signs in the database. A necessary component of such a sign lookup system
is a similarity measure for comparing sign videos. Given a query video of a
specific sign, the similarity measure should assign high similarity values to vid-
eos from the same sign, and low similarity values to videos from other signs.
This paper evaluates a state-of-the-art video-based similarity measure called
Dynamic Space-Time Warping (DSTW) for the purposes of sign retrieval. The
paper also discusses how to specifically adapt DSTW so as to tolerate differ-

  

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

 

Collections: Computer Technologies and Information Sciences