Face Recognition with Age,Gender,Ethnicity
The main motive is to develop an automatic age and gender estimation method towards human faces which will continue to possess an important role in computer vision and pattern recognition. Apart from age estimation, facial emotion recognition also plays an important role in computer vision. Non-verbal communication methods such as facial expressions, eye movement and gestures are used in many applications of human computer interaction. In order to create computer modeling of humans age, gender and emotions a plenty of research has been accomplished. But it is still far behind the human vision system. In this project, we propose a Convolutional Neural Network (CNN) based architecture for age & gender classification. The architecture is trained to label the input images into 8 labels of age and 2 labels of gender. Our approach shows better accuracy in both age and gender classification compared to classifier-based methods. In order for computer modeling of human’s emotions we are planning to predict human emotions using deep CNN and observe how emotional intensity changes on a face from low level to high level of emotion. With a proper user interface, the result of the prediction is revealed.
PROJECT OUTPUT VIDEO:
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- Monitor : 15’’ LED
- Input Devices : Keyboard, Mouse
- Ram : 2 GB
- Operating system : Windows 10.
- Coding Language : Python