Using Multiple Sensors for Mobile Sign Language Recognition
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We build upon a constrained, lab-based Sign Language recognition system with the goal of making it a mobile assistive technology. We examine using multiple sensors for disambiguation of noisy data to improve recognition accuracy. Our experiment compares the results of training a small gesture vocabulary using noisy vision data, accelerometer data and both data sets combined.