Recognition and Analysis of Human Faces and Facial Expressions using Computer vision
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Humans detect and identify faces in a scene with little or no effort. However, building an automated system that accomplishes this task is very difficult. There are several related sub-problems: detection of a pattern as a face, identification of the face, analysis of facial expressions, and classification based on physical features of the face. A system that performs these operations will find many applications,e.g personality analysis, criminal identification, lie detection, authentication in secure systems, etc. ...learn more
Project status: Under Development
Overview / Usage
The system developed here is for Detecting, Recognition of a person and further analyze the behavior/mood/expression using face features. The system uses Computer Vision to understand the digital images and video streams and do the above mentioned task in real-time.
Methodology / Approach
Using Convolution Neural Network(CNN), Deep Neural Network(DNN), Computer Vision(CV), Transfer Learning, building a Neural Network to Detect, Recognize and extract human face and face features.
Technologies Used
Anaconda(Software development) Environment, Ubuntu Operating System, Webcam, Graphical Processing Unit(GPU), File Management System, etc.
Python, Machine learning, Deep learning, libraries like OpenCV, sklearn, mumpy, pandas, matplotlib, dlib, tensorflow, etc.