Yong-Joon Joo, Myung-Duk Hong, Ui-Nyoung Yoon, Seung-Hyun Go, Geun-Sik Jo

KIPS Transactions on Software and Data Engineering, Vol. 8, No. 2, pp. 61-66, Feb. 2019
https://doi.org/10.3745/KTSDE.2019.8.2.61,   PDF Download:
Keywords: Augmented Reality, Homography, Ransac, Depth Image
Abstract

Augmented reality is a technology that makes a virtual object appear as if it exists in reality by composing a virtual object in real time with the image captured by the camera. In order to augment the virtual object on the object existing in reality, the homography of images utilized to estimate the position and orientation of the object. The homography can be estimated by applying the RANSAC algorithm to the feature points of the images. But the homography estimation method using the RANSAC algorithm has a problem that accurate homography can not be estimated when there are many feature points in the background. In this paper, we propose a method to filter feature points of a background when the object is near and the background is relatively far away. First, we classified the depth image into relatively near region and a distant region using the Otsu's method and improve homography estimation performance by filtering feature points on the relatively distant area. As a result of experiment, processing time is shortened 71.7% compared to a conventional homography estimation method, and the number of iterations of the RANSAC algorithm was reduced 69.4%, and Inlier rate was increased 16.9%.

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