FACE RECOGNITION IN JAVA ENVIRONMENT ABSTRACT: In today’s world, face recognition has its application in many fields incorporating:Automotive sector, image enhancing, robotics, gaming & manufacturing. It is an exciting field with hurdles. Such as limited hardware, poor visualisation or quality & connectivity. This paper demonstrates a face recognition system in JAVA environment. The aim is to have high recognition rate. Key words:Face recognition, Open CV, JAVA environment. I. Introduction:Image
There are many biometric techniques in existence today. Face recognition technology is one of them which make use of computer software to determine the identity of the person. Today conservative methods of identification like possession of certain type of identity cards, use of passwords etc. are not at all reliable for identity purposes where security is a critical factor. There is no surety in the fact that person using ATM card to withdraw money from any ATM machine is actual owner of the card
SECURITY SURVEILLANCE SYSTEM Security Through Image Processing Prof.Vishal Meshram,Jayendra More Department of Electronics & Telecommunication Engineering (ExTC), University Of Mumbai Vishwatmak Om Gurudev College Of Engineering Maharashtra State Highway 79, Mohili, Maharashtra 421601, India. Vishalmmeshram19@gmail.com, more.jayendra@yahoo.in Bhagyesh Birari,Swapnil Mahajan Department of Electronics & Telecommunication Engineering (ExTC), University Of Mumbai Vishwatmak Om Gurudev College Of
Seminar topic focuses on talking head system.Talking head system is a technique in which an animated talking head generates lifelike face which is based on speech recognition. Talking head system converts this speech to an animated talking head having facial expressions and mouth movements.The seminar focuses on an approach that synthesizes ones’ face using a two and half D head model, with the facial expression driven by speech.Such system can be made web enabled to take advantage of streaming technology
video has been the focus of several researchers’ efforts and several systems have been described in the literature. Action recognition is the process of labelling image sequences with action labels. The task is challenging due to variations in motion performance, recording settings and inter-object differences. Generally, the action recognition process can be divided into two steps 1st feature extraction and representation and 2nd action class prediction. The first step deals with the extraction and encoding
Representation 6.Emotion Recognition 7.Multimedia content analysis(MCA) for emotional characterization of music video clips. 8.Conclusion Introduction The existing research on automatic perception of human emotions has opened up a new dimension for Human-Computer Interaction research, and also showed great potential to benefit and support a wide variety of applications, including computer assisted learning. Emotional analysis and Facial expression recognition are of next great field
Cognitive processes involved with face recognition To human beings, facial recognition is not only essential for identification of persons in the social context, but also a vital social tool. There are various reasons why facial recognition process is a vital to human beings. Facial recognition serves an essential purpose of identifying members within our society; as a result, we are able to select those that we can socialize with that aid our survival in society. For instance, the males are
IV. PROPOSED SYSTEM A. Block diagram Fig 3: Block Diagram of Proposed System B. Proposed system In mostly emotion recognition system use Principal Component Analysis (PCA) algorithm for detection. However, in that detection of action unit not done properly so it has some limitation. Recognizing emotion from ensemble of features uses patch descriptors like histogram of oriented gradients, local binary patterns and scale invariant feature transform. It has two outcomes one is person specific
Designation: Student Contact Number: 9637064965 Maharashtra Institute of Technology, Aurangabad, Maharashtra ABSTRACT : Extracting and understanding of emotion is of high importance for the interaction among human and machine communication systems. The most expressive way to display the human’s emotion is through facial expression analysis. This paper presents and implements an automatic extraction of facial expression and emotion from still image. There are steps to detect
Generally, most biometric-based authentication systems consist of two phases, Enrolment Phase and Verification Phase - Figure 5. In the Enrolment/ Training Phase, users deal with different kind of sensors depends on the kind of biometric used for authentication system. Those biometric sensors scan and capture the repeated user’s basic login data till finishing the system number of training sessions for specific number of time to train the system. After that the feature extractor extracts the features