Real-Time Label Insertion in Live Video Through Online Trifocal Tensor Estimation

Abstract

Abstract:We present an augmented reality application that can supplement a live video sequence with virtual labels associated with the scene content captured by an agile video camera moving inside an explored environment. The method proposed is composed of two main phases. First, a matching phase where reference images are successively compared with the captured images. And, second, a tracking phase that aims at maintaining the correspondence between a successfully matched reference image and each frame of a captured sequence. Labels insertion is based on projective transfer using the trifocal tensor, this one being estimated and continuously updated as the camera is moved inside the scene.