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Modified Adaptive Implicit Shape Model for Object Detection

  • Ziyan Xu
  • , Shujing Lyu*
  • , Weiping Jin
  • , Yue Lu
  • *此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Automated threat object detection in X-ray images is needed urgently in baggage inspection at airports, railway stations and other public places. However, the works on object detection are still very limited to meet the needs of practical application. In this paper, we propose a modified adaptive implicit shape model (MAISM) to detect threat objects in X-ray images, in which the triangle patches are used to compute occurrence of the centroid of object instead of keypoints. This model is adaptive for object detection in images of variable scales through triangle patch matching. Experiments on three different threat objects images (razor blades, shuriken, handguns) of various scales demonstrate the effectiveness of the proposed method.

源语言英语
主期刊名Neural Information Processing - 26th International Conference, ICONIP 2019, Proceedings
编辑Tom Gedeon, Kok Wai Wong, Minho Lee
出版商Springer
144-151
页数8
ISBN(印刷版)9783030368012
DOI
出版状态已出版 - 2019
活动26th International Conference on Neural Information Processing, ICONIP 2019 - Sydney, 澳大利亚
期限: 12 12月 201915 12月 2019

出版系列

姓名Communications in Computer and Information Science
1143 CCIS
ISSN(印刷版)1865-0929
ISSN(电子版)1865-0937

会议

会议26th International Conference on Neural Information Processing, ICONIP 2019
国家/地区澳大利亚
Sydney
时期12/12/1915/12/19

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