American Sign Language Recognition Based on MobileNetV2
نویسندگان
چکیده
منابع مشابه
Appearance Based Recognition of American Sign Language Using Gesture Segmentation
The work presented in this paper goals to develop a system for automatic translation of static gestures of alphabets in American Sign Language. In doing so three feature extraction methods and neural network is used to recognize signs. The system deals with images of bare hands, which allows the user to interact with the system in a natural way. An image is processed and converted to a feature ...
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In this paper, we present how appearance-based features can be used for the recognition of words in American sign language (ASL) from a video stream. The features are extracted without any segmentation or tracking of the hands or head of the signer, which avoids possible errors in the segmentation step. Experiments are performed on a database that consists of 10 words in ASL with 110 utterances...
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The major challenge that faces American Sign Language (ASL) recognition now is to develop methods that will scale well with increasing vocabulary size. Unlike in spoken languages, phonemes can occur simultaneously in ASL. The number of possible combinations of phonemes after enforcing linguistic constraints is approximately 5:5 108: Gesture recognition, which is less constrained than ASL recogn...
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For the recognition of continuous sign language we analyse whether we can improve the results by explicitly incorporating depth information. Accurate hand tracking for sign language recognition is made difficult by abrupt and fast changes in hand position and configuration, overlapping hands, or a hand signing in front of the face. In our system depth information is extracted using a stereo-vis...
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The paper aims to propose a novel technique that recognizes finger spelled American Sign Language (ASL) gestures. The external characteristic of hand, i.e. shape based algorithm is being used for recognition. Since almost all of the alphabets have a unique shape, each alphabet is characterized on the basis landmark points marked on the boundary of the hand shown by the signer. A training set is...
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ژورنال
عنوان ژورنال: Advances in Science, Technology and Engineering Systems Journal
سال: 2020
ISSN: 2415-6698,2415-6698
DOI: 10.25046/aj050657