系统仿真学报 ›› 2020, Vol. 32 ›› Issue (7): 1294-1300.doi: 10.16182/j.issn1004731x.joss.19-VR0514

• 仿真建模理论与方法 • 上一篇    下一篇

基于邻近目标置信度评估的视觉目标跟踪与定位

柳有权1, *, 裴雪1, 李婉1, 刘正雄2   

  1. 1. 长安大学信息工程学院,陕西 西安 710064;
    2. 西北工业大学航天学院,陕西 西安 710072
  • 收稿日期:2019-09-09 修回日期:2019-12-16 出版日期:2020-07-25 发布日期:2020-07-15
  • 作者简介:柳有权(1976-),男,湖北秭归,博士,教授,硕导,研究方向为计算机图形学、虚拟现实技术;裴雪(1992-),女,河南新乡,硕士生,研究方向为计算机图形学、虚拟现实技术。

Visual Tracking and Localization Based on Confidence Evaluation of Adjacent Targets

Liu Youquan1, *, Pei Xue1, Li Wan1, Liu Zhengxiong2   

  1. 1. School of information Engineering, Chang'an University, Xi'an 710064, China;
    2. School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China;
  • Received:2019-09-09 Revised:2019-12-16 Online:2020-07-25 Published:2020-07-15

摘要: 针对视觉目标跟踪与定位中,目标因为无特征或被严重遮挡导致无法定位的问题,设计了一种基于邻近目标置信度评估的视觉目标跟踪与定位算法。在跟踪过程中,通过检测提取邻近目标的标记特征,然后结合每个特征标记的汉明距离和相对其他标记的归一化结果以及每个标记发生的概率,得到每个标记最终置信度,选择置信度最大的邻近标记来确定目标位置。实验结果表明,该算法在对目标存在遮挡或目标没有特征的情况可以大大提高跟踪的鲁棒性和准确性。

关键词: 目标跟踪与定位, 邻近标记, 置信度评估, 汉明距离

Abstract: In visual target tracking and localization, the target could not be located due to the lack of features or the severe occlusion. Aiming at this, an algorithm based on confidence evaluation of neighboring targets is designed. In the tracking process, by detecting and extracting the marker features of neighboring targets, and combining the Hamming distance of each feature marker and the normalized result with respect to other markers as well as the probability of occurrence of each marker, the final confidence of each marker is obtained. The marker with the maximum confidence is to used determine the target location. Experimental results show that the algorithm can greatly improve the robustness and accuracy of tracking during occlusion or target features missing.

Key words: target tracking and localization, proximity marking, confidence evaluation, Hamming distance

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