• Aishwarya Pravin Patil
• Pooja maske
• Ashvini maske
• Nitin ilhe

The face is one of the easiest ways to distinguish the individual identity of each other. Face recognition is a personal identification system that uses personal characteristics of a person to identify the person’s identity. Human face recognition procedure basically consists of two phases, namely face detection, where this process takes place very rapidly in humans and animals, except under conditions where the object is located at a short distance away, the next is the introduction, which recognize a face as individuals. Stage is then replicated and developed as a model for facial image recognition (face recognition) is one of the much-studied biometrics technology and developed by experts. There are two kinds of methods that are currently popular in developed face recognition pattern namely, Eigenface method and Fisherface method. Facial image recognition Eigenface method is based on the reduction of face-dimensional space using Principal Component Analysis (PCA) for facial features. The main purpose of the use of PCA on face recognition using Eigen faces was formed (face space) by finding the eigenvector corresponding to the largest eigenvalue of the face image. The area of this project face detection system with face recognition is Image processing. The software requirements for this project is Net- Beans/Eclipse Java software.In face recognition systems, variables such as direction of light, facial expression and reflection are making difficult to identify. Thus, in recent Years, Convolutional Neural Network (CNN) models, which are deep learning models as an alternative to traditional feature extraction and artificial neural network methods, have begun to be developed. Data mining is used to analyze human activities or machine learning techniques, these are infer properties such as the gender or age of the people. Different algorithms are implemented on static and nonstatic conditions. Static conditions include stable and uniform background, identical poses, similar illumination, neutral frontal face Non static conditions include position, partial occlusion and facial hair, which makes recognition process a complex problem. The main stages for face recognition include face detection, feature representation and classifications. In this work we present face detection techniques, methods used, their performance, limitations and proposed a new technique for Face Detection based on Viola and Jones algorithm and principal component analysis.

face detection,Gender Detection, Classification, Eigen face, PCA,java,Data Analytics, Machine learning, Object detection, CNN (Convolution Neural Network), Facial Expression Detection, deep learning

"Animate Object Detection Using Deep Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 5, page no.922-925, MAY-2018, Available :http://www.jetir.org/papers/JETIR1805572.pdf

"Animate Object Detection Using Deep Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 5, page no. pp922-925, MAY-2018, Available at : http://www.jetir.org/papers/JETIR1805572.pdf