Robust online tracking using orientation and color incorporated adaptive models in particle filter

Chengjiao Guo, Ying Lu, Takeshi Ikenaga

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Moving object tracking has received much interest in the field of computer vision due to the increasing need for automated video analysis. Particles Filter is a very promising object tracking method since it is suitable for non-linear and/or non-Gaussian applications. Most particle filter applies color information in target model which might fail in the presence of similar colored objects in the scene. This paper presents the integration of color and orientation features in particle filter to make full use of the distinctive target features. Also, an improved Gaussian weighting function for target models and an updating scheme with an adaptive updating ratio are proposed. The proposed approaches are applied in the real-time video sequences with different occlusion conditions to test the robustness of the proposal. Experiment results show that stable and accurate tracking performance is achieved even when the target is occluded by a similar colored object.

本文言語English
ホスト出版物のタイトルNISS2010 - 4th International Conference on New Trends in Information Science and Service Science
ページ281-286
ページ数6
出版ステータスPublished - 2010 10 15
イベント4th International Conference on New Trends in Information Science and Service Science, NISS2010 - Gyeongju, Korea, Republic of
継続期間: 2010 5 112010 5 13

出版物シリーズ

名前NISS2010 - 4th International Conference on New Trends in Information Science and Service Science

Conference

Conference4th International Conference on New Trends in Information Science and Service Science, NISS2010
国/地域Korea, Republic of
CityGyeongju
Period10/5/1110/5/13

ASJC Scopus subject areas

  • 情報システムおよび情報管理

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