ltfschoen/AIND-Recognizer
Term 1 Project 3 Design a Sign Language Recognition System by Luke Schoen for Udacity Artificial Intelligence Nanodegree (AIND)
This project helps researchers and engineers create and evaluate systems that can automatically understand American Sign Language (ASL) from video data. It takes in preprocessed sequences of hand and nose positions, then outputs identified ASL words. The primary user would be a machine learning practitioner or an AI student working on real-time sign language interpretation.
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Use this if you need to build and test a probabilistic model to recognize individual ASL words from motion-tracked hand and nose data.
Not ideal if you need a ready-to-use application for live sign language translation, as this project focuses on the underlying recognition system.
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May 02, 2017
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