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Marker Detection by Using Affine-SIFT Matching Points for Marker Occlusion of Augmented Reality  

Kim, Yong-Min (Dept. of Comp. Sci. and Eng., Hanyang University)
Park, Chan-Woo (Dept. of Comp. Sci. and Eng., Hanyang University)
Park, Ki-Tae (Ambient Intelligence Software Team, Institute of Hanyang BK21, Hanyang University)
Moon, Young-Shik (Dept. of Comp. Sci. and Eng., Hanyang University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.48, no.2, 2011 , pp. 55-65 More about this Journal
Abstract
In this paper, a novel method of marker detection robust against marker occlusion in augmented reality is proposed. the proposed method consists of four steps. In the first step, in order to effectively detect an occluded marker, we first utilize the Affine-SIFT (ASIFT, Affine-Scale Invariant Features Transform) for detecting matching points between an enrolled marker and an input images with an occluded marker. In the second step, we apply the Principal Component Analysis (PCA) for eliminating outlier of the matching points in the enrolled marker. And then matching points are projected to the first and second axis for longest value and the shortest value of an ellipse are determined by average distance between the projected points and a center of the points. In the third step, Convex-hull vertices including matching points are considered as polygon vertices for estimating a geometric affine transformation. In the final step, by estimating the geometric affine transformation of the points, a marker robust against a marker occlusion is detected. Experimental results have shown that the proposed method effectively detects occlude markers.
Keywords
Augmented Reality; Affine-SIFT; Occlusion; Principal Component Analysis; Marker Detection;
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