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| Content Provider | ACM Digital Library |
|---|---|
| Author | Conly, Christopher Zhang, Zhong Athitsos, Vassilis |
| Abstract | Users of written languages have the ability to quickly and easily look up the meaning of an unknown word. Those who use sign languages, however, lack this advantage, and it can be a challenge to find the meaning of an unknown sign. While some sign-to-written language dictionaries do exist, they are cumbersome and slow to use. We present an improved American Sign Language video dictionary system that allows a user to perform an unknown sign in front of a sensor and quickly retrieve a ranked list of similar signs with a video example of each. Earlier variants of the system required the use of a separate piece of software to record the query sign, as well as user intervention to provide bounding boxes for the hands and face in the first frame of the sign. The system presented here integrates all functionality into one piece of software and automates head and hand detection with the use of an RGB-D sensor, eliminating some of the shortcomings of the previous system, while improving match accuracy and shortening the time required to perform a query. |
| Starting Page | 1 |
| Ending Page | 8 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781450334525 |
| DOI | 10.1145/2769493.2769534 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-07-01 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Kinect Tracking Gesture recognition Hand location |
| Content Type | Text |
| Resource Type | Article |
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