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This paper presents the performance analysis of various contemporary feature detector and descriptor pair for real time face tracking. These feature detectors/descriptors are mostly used in image matching applications. Some feature detectors/descriptors like STAR, FAST, BRIEF, FREAK, and ORB can also be used for SLAM applications due to their high performance. However using only one of these feature detectors for object tracking may not provide good accuracy due to various challenges in tracking like abrupt change in object motion, non-rigid object structure, change in appearance of object, occlusions in the scene and camera motion. But it can be combined other object tracking algorithm to improve the overall tracking accuracy. In this paper we have measured the tracking speed and accuracy of these feature detectors in real time video for face tracking using parameters like average number of detected key points, average detection time of key-point, frame per second and number of matches using OpenCV.

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Although various techniques of image deformation have been developed and generally applied in animation and morphing, there are a few mechanisms to spread out these techniques to handle videos, especially real-time warping of an expressive moving part in the video like human face. This work presents a system which provides real-time deformation of the shape and appearance of face of people who are standing in front of a D-RGB camera, such as the Microsoft Kinect. This system allows the user to manipulate human face shape parameters such as jaw, chin, nose, mouth; eyes etc. i.e. the user is allowed to concentrate only on what they require to change about the face and observe the manipulated appearance in real-time. Thus, instead of posing in front of a real mirror and imagining their appearance, our system allows the users to pose in front of a digital 'virtual mirror' and visualize themselves in different face features.

In the contemporary world today, computer vision applications make use of 4G technology and high-definition (HD) video calling on mobile phones. People frequently utilize 4G video calling to communicate with friends and family. The technology is capable of projecting minute elements from the real world, such as background, facial features, and behavior, among other things. We developed a video processing system that lets users alter the shape and look of facial features such as the eyebrows, eyes, nose, lip, jaw, and chin. Our work improves users’ facial look during live 4G video calls; the user sees the desired modified face feature in real-time, as if in a virtual mirror, and can then use it. Abstract environment.