Augmented reality virtual glasses try-on technology based on iOS platform

Abstract

With the development of e-commerce, network virtual try-on, as a new online shopping mode, fills the gap that the goods cannot be tried on in traditional online shopping. In the work, we discussed augmented reality virtual glasses try-on technology on iOS platform to achieve optimal purchase of online glasses, improving try-on speed of virtual glasses, user senses of reality, and immersion. Face information was collected by the input device-monocular camera. After face detection by SVM classifier, the local face features were extracted by robust SIFT. Combined with SDM, the feature points were iteratively solved to obtain more accurate feature point alignment model. Through the head pose estimation, the virtual model was accurately superimposed on the human face, thus realizing the try-on of virtual glasses. The above research was applied in iOS glasses try-on APP system to design the try-on system of augmented reality virtual glasses on iOS mobile platform. It is proved that the method can achieve accurate identification of face features and quick try-on of virtual glasses.