I am currently a Masters student at Indiana University, Bloomington. I have serious passion for Machine Learning, Data Analysis and driving insights from data. My major focus in my degree right now is Machine learning. I have worked on a number of end-to-end Machine Learning Projects. I personally believe that the most important step in any Data Science Project is EDA. I spend most of my time in projects working on extracting the best features and meticulously engineering them to get the best results out of the model.

Abstract:
Keywords:Deep Learning, Computer Vision, OpenCV, Boosting(Haar Cascade)

Every year, between 250000 and 500000 people across the world suffer a major spinal cord injury, many of which result in motor impairment. A set of physical gestures can comprise an entire language which makes it a powerful form of communication for people who suffer from motor impairment. Most gesture recognition systems require the user to learn specific gestures prescribed by the system. This turns out to be a major disadvantage of these systems as most motor impaired individuals are heavily constrained in terms of movement. Hence they may not be able to accomplish certain gestures defined by the system. So in this paper we propose a realtime system which can be customized to user-specific dynamic hand movements. This system can be used to carry out certain tasks. Haar Cascade detection algorithm was used in order to track the movements of the hand and trace the path. Siamese neural network was used for the purpose of customization and recognition of the gestures.