ISMAR 2018
IEEEIEEE computer societyIEEE vgtc

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Atsunori Moteki, Nobuyasu Yamaguchi, Ayu Karasudani, Yoshie Kobayashi, Toshiyuki Yoshitake, Junya Kato, and Tomohiro Aoyagi. Manufacturing defects visualization via robust edge-based registration. In Adjunct Proceedings of the IEEE and ACM International Symposium for Mixed and Augmented Reality 2018 (To appear). 2018.
[BibTeX▼]

Abstract

We propose a visualization method for inspecting manufacturing defects. Industrial products have many straight lines and little texture; therefore; the proposed method uses edges for estimating 6DoF pose of the products (registration). To prevent combinatorial explosion; our method reduces the number of combinations by the condition of edges' geometrical distribution. Moreover; manufacturing defects are detected and visualized by robust registration based on the LMedS. This method realizes on-site product inspection for unskilled workers unfamiliar with AR; and decreases the cost of re-manufacturing. We evaluate our method quantitatively using original CG and real image dataset.