Particle Filter Vehicle Tracking Based on SURF Feature Matching

カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門（英文）

発行日: 2014/03/01

タイトル(英語): Particle Filter Vehicle Tracking Based on SURF Feature Matching

著者名: Xiaofeng Lu (Graduate School of Science and Technology, Nihon University/Faculty of Computer Science and Engineering, Xi'an University of Technology), Takashi Izumi (Graduate School of Science and Technology, Nihon University), Lin Teng (Graduate School o

著者名(英語): Xiaofeng Lu (Graduate School of Science and Technology, Nihon University/Faculty of Computer Science and Engineering, Xi'an University of Technology), Takashi Izumi (Graduate School of Science and Technology, Nihon University), Lin Teng (Graduate School of Science and Technology, Nihon University), Lei Wang (Faculty of Computer Science and Engineering, Xi'an University of Technology)

キーワード: particle filter，vehicle tracking，SURF，multiple features

要約(英語): In this paper, we propose a robust vehicle tracking method based on speeded-up robust features (SURF) feature matching in a particle filter framework. In this framework, the color feature and the local binary pattern (LBP) texture feature are also combined to improve the representation of the tracking target. To further improve the tracking performance, three strategies are used. First, a dynamic update mechanism of the target template is proposed to capture appearance changes. Second, the size of the tracking window is also modified dynamically by balancing the weights of three feature distributions. Third, the weight of each particle is allocated with an improved distance kernel function method in the tracking process. Specifically, the proposed method of adopting new feature points for the target template can objectively reflect tracking target changes and effectively overcome the disadvantages of the random selection mechanism. We test the proposed approach on numerous sequences involving different types of challenges, including variations in illumination, scale changes, and rotation. The experimental results show that the proposed method is more efficient and robust than the classical approaches.

本誌: IEEJ Journal of Industry Applications Vol.3 No.2 （2014） Special Issue on Motor Drive and its Related Technologies

本誌掲載ページ: 182-191 p

原稿種別: 論文／英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejjia/3/2/3_182/_article/-char/ja/