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Comparing Gesture Recognition Accuracy Using Color and Depth Information
 

Summary: Comparing Gesture Recognition Accuracy Using Color
and Depth Information
Paul Doliotis, Alexandra Stefan, Christopher McMurrough, David Eckhard, and Vassilis Athitsos
Computer Science and Engineering Department, University of Texas at Arlington
Arlington, Texas, USA
ABSTRACT
In human-computer interaction applications, gesture recognition
has the potential to provide a natural way of communication be-
tween humans and machines. The technology is becoming ma-
ture enough to be widely available to the public and real-world
computer vision applications start to emerge. A typical example
of this trend is the gaming industry and the launch of Microsoft's
new camera: the Kinect. Other domains, where gesture recognition
is needed, include but are not limited to: sign language recogni-
tion, virtual reality environments and smart homes. A key chal-
lenge for such real-world applications is that they need to oper-
ate in complex scenes with cluttered backgrounds, various moving
objects and possibly challenging illumination conditions. In this
paper we propose a method that accommodates such challenging
conditions by detecting the hands using scene depth information

  

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

 

Collections: Computer Technologies and Information Sciences