• Karthik Vas S
• Anisha B.S

Nowadays Computer plays a crucial role in daily activities and used among various fields in society. The Interactions between a computer and human is done by basic input devices like keyboard, mouse etc. Hand Gestures can be one of the best and effective medium for human-computer interactions which help in interactions between the both easier. Convolution Neural Network (CNN) which is basically used for image classification and image representation. Also, CNN can learn nonlinear relationships among set of images, considering this we propose a gesture recognition system using CNN. Face recognition software’s are used in various fields like user detection, automobile control, bio metrics and security authentication and enhancements. This project focuses on developing a model to control a system using gestures, while simultaneously monitoring continuously for user and their profile using face recognition to avoid unauthorized access. An effective gesture recognition is developed and applied in conjunction with face recognition system to perform a mapped function in real time.

Facial Recognition, Gesture Recognition, Background Subtraction, Convolutional Neural Network.

"Real Time Contextual Based Gesture Recognition System Using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.c805-c811, May-2021, Available :http://www.jetir.org/papers/JETIR2105357.pdf

"Real Time Contextual Based Gesture Recognition System Using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppc805-c811, May-2021, Available at : http://www.jetir.org/papers/JETIR2105357.pdf