Region-based tracking using sequences of relevance measures

Sandy Martedi, Bruce Thomas, Hideo Saito

研究成果: Conference contribution

5 被引用数 (Scopus)

抄録

We present the preliminary results of our proposal: a region-based detection and tracking method of arbitrary shapes. The method is designed to be robust against orientation and scale changes and also occlusions. In this work, we study the effectiveness of sequence of shape descriptors for matching purpose. We detect and track surfaces by matching the sequences of descriptor so called relevance measures with their correspondences in the database. First, we extract stable shapes as the detection target using Maximally Stable Extreme Region (MSER) method. The keypoints on the stable shapes are then extracted by simplifying the outline of the stable regions. The relevance measures that are composed by three keypoints are then computed and the sequences of them are composed as descriptors. During runtime, the sequences of relevance measures are extracted from the captured image and are matched with those in the database. When a particular region is matched with one in the database, the orientation of the region is then estimated and virtual annotations can be superimposed. We apply this approach in an interactive task support system that helps users for creating paper craft objects.

本文言語English
ホスト出版物のタイトル2013 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2013
DOI
出版ステータスPublished - 2013 12 1
イベント12th IEEE and ACM International Symposium on Mixed and Augmented Reality, ISMAR 2013 - Adelaide, NSW, Australia
継続期間: 2013 10 12013 10 4

出版物シリーズ

名前2013 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2013

Other

Other12th IEEE and ACM International Symposium on Mixed and Augmented Reality, ISMAR 2013
CountryAustralia
CityAdelaide, NSW
Period13/10/113/10/4

ASJC Scopus subject areas

  • Artificial Intelligence

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