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VASLs:
a tool set for annotate ASL video sequence
VASLs is the byproduct of our automatic ASL video sequence
recognizer. It is a set of tools that can help annotate ASL video
sequences. The purpose of building these tools is to facilitate us to
generate large amount of ASL training data. The main task of these tools is
to segment the videos into ASL sentences, label each frame in the sentences
as their corresponding signs, extract signs from the sentences, build
candidate hand sets, extract the hand and face areas for training purpose.
We have tested it on
Microsoft Windows XP and Intel Pentium III
Related
Publications:
- R.D.
Yang. , S. Sarkar, B. Loeding and A. Karshmer, “Efficient Generation of Large
Amount of Training Data for Sign Language Recognition: A
semi-automatic tool”, International Conference on Computers
Helping People with Special Needs (ICCHP’06), 2006.
- R.D.
Yang. and S. Sarkar,
"Gesture Recognition using HMM from fragmented observation
", IEEE International Conference on Computer Vision and Pattern
Recognition 2006.
VASLs is based
on the Intel OpenCV Library:
VASLs used the meanshift
algorithm source code from Robust
Image Understanding Laboratory
The core algorithm of VASLs
is developed and discussed by the ASL Group at USF
VASLs was written and is now being updated by Alan Yang.
Special Thanks to Melinda Black for
testing the software and editing the documentation.
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