A Framework of Video News System Using Image Segmentation and Augmented Reality
Jia‐Hong Lee, Mei-Yi Wu, Tzu-Hao Tseng · 2011
Abstract—In this paper, we propose a framework of video news system using image segmentation and augmented reality scheme. The goal of proposed system is to provide users with realistic audio-visual contents when they are interested in reading some topics on newspapers. In our approach, pictures on the newspapers were used as markers of augmented reality. Users can pick up these pictures to watch the corresponding video news to obtain more information. The proposed system consists of image segmentation, image recognition and augmented reality engine with audio-visual contents. In image segmentation, skew angle detection and Hough transform techniques are applied to extract pictures on newspapers. In image recognition, image calibration using four-point mapping and Harris corner detection are proposed to identify different pictures on the newspapers. In augmented reality, four-point transformation is reused to add video image frame on the captured image by camera. We expect that the proposed system is popular and can be applied as a kind of advertisement of products in business applications.