Hand Gesture Recognition from Surveillance Video Using Surf Feature

Abstract The Sign language is very important for people who have hearing and speaking deficiency. It is the only mode of communication for such people to convey their messages. In this paper, a feature detection scheme is introduced called SURF, which stands for Speeded Up Robust Features. The real time images will be captured first and then stored in directory and on recently captured image and feature extraction will take place to identify which sign has been articulated by the user through SURF algorithm. A Text to Speech conversion is also included in this project. An experimental result shows that the proposed approach performs well with low time.

Keywords speeded up robust feature, Convolutional neural network, Text to speech, Deep dynamic neural network.

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Engineering Journal: Hand Gesture Recognition from Surveillance Video Using Surf Feature

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