Augmenting Security Systems with Sign Language Recognition Using Deep Learning

Sign language is the ancient way of communication which was found before the vocal communication. It bridges the gap between people who are deaf and it overcome the barrier of language difference. Many people learn sign languages as they express themselves through hand movements and facial expressions in absent of spoken communication. The current security CCTV cameras with manual security is not efficient in critical situation, this novel approach overcome the limitation and immediately send assistance. If any distressing situation occurs in absent of vocal communication, how can a person seek help orescape the situation is still in dispute. To elucidate, this security assessment will help people in those critical cenarios. When a person shows help sign in the camera, the backend mechanism in the camera will detect and sends security alert to the registered emergency contacts. This can be implemented in public cameras for security purpose. Furthermore, it will be a great aid to women in any unexpected situation. This suggested mechanism emphasis the automated meta data such as the image captured by the camera. The Deep learning model implemented can be an effective mechanism in terms of risk assessment and security exclusive for deaf and dumb people. This study can further improve in future by detection of emotion along with the handgesture can increase the novelty of the gesture that is the real emergency and reduce people tampering the system for amusement.