吉林大学学报(信息科学版) ›› 2023, Vol. 41 ›› Issue (3): 566-573.

• • 上一篇    

考虑遮挡因素的视频人体运动目标自适应跟踪

窦海波   

  1. 咸阳师范学院 体育学院, 陕西 咸阳 712000
  • 收稿日期:2022-05-27 出版日期:2023-06-08 发布日期:2023-06-15
  • 作者简介:窦海波(1985— ), 男, 山东淄博人, 咸阳师范学院讲师, 主要从事体育教育训练学研究, (Tel)86-13636898609(E-mail)zkkqq11@ 163. com。
  • 基金资助:
    陕西省教育厅专项科研计划基金资助项目(19JK0915); 陕西省教育科学“十三五冶规划基金资助项目(SGH17H201)

Adaptive Tracking Algorithm for Video Human Moving Objects Considering Occlusion

DOU Haibo   

  1. College of Physical Education, Xianyang Normal University, Xianyang 712000, China
  • Received:2022-05-27 Online:2023-06-08 Published:2023-06-15

摘要: 针对视频人体运动目标跟踪过程中遮挡导致跟踪能力下降的问题, 提出考虑遮挡因素的视频人体运动目 标自适应跟踪算法。 采用区域生长和视觉阈值效应相结合算法粗检测目标, 以粗检测结果为基础通过 Kalman 滤波器和 Meanshift 跟踪算法跟踪视频人体运动目标。 在目标尺度改变、 旋转以及光线变化等情况导致跟踪效 果不佳时引入 SIFT(Scale Invariant Feature Transform)算法提高跟踪能力, 实现抗遮挡的视频人体运动目标自适 应跟踪。 实验结果表明, 该方法的跟踪精确度较高, 在遮挡程度为 0. 5 时, 跟踪成功率仍可以达到 75% 左右, 且平均跟踪帧率为 28. 9 frame / s, 实时性较强。

关键词: 遮挡因素,  , 人体运动目标,  , Kalman 滤波器,  , 目标跟踪,  , SIFT 算法

Abstract: Aiming at the problem that the tracking ability decreases due to occlusion during the tracking of video human moving objects, an adaptive tracking algorithm for video human moving objects considering the occlusion factor is proposed. The Kalman filter and the Meanshift tracking algorithm are used to track the video human moving target. When the target scale, rotation and light change there poor tracking results. The SIFT( Scale Invariant Feature Transform) algorithm is introduced to improve the tracking ability and achieve anti-occlusion video human moving target adaptive tracking. The experimental results show that the tracking accuracy of this method is high, and the tracking success rate can reach about 75% when the occlusion degree is 0. 5. The average tracking frame rate is 28. 9 frame / s, and the real-time performance is strong.

Key words: occlusion factor,  , human motion target,  , kalman filter,  , target tracking,  , scale invariant feature transform(SIFT) algorithm

中图分类号: 

  • TP391. 413