计算机工程与应用 ›› 2013, Vol. 49 ›› Issue (15): 157-161.

• 图形图像处理 • 上一篇    下一篇

基于尺度不变特征的光流法目标跟踪技术研究

吴  垠,李良福,肖樟树,刘侍刚   

  1. 陕西师范大学 计算机科学学院,西安 710062
  • 出版日期:2013-08-01 发布日期:2013-07-31

Optical flow motion tracking algorithm based on SIFT feature

WU Yin, LI Liangfu, XIAO Zhangshu, LIU Shigang   

  1. College of Computer Science, Shaanxi Normal University, Xi’an 710062, China
  • Online:2013-08-01 Published:2013-07-31

摘要: 针对目标跟踪问题中目标和场景动态变化的问题,提出了一种结合尺度不变特征变换(SIFT)和光流估计算法并改进模板更新策略的目标跟踪算法。SIFT特征是一种局部特征,具有尺度和旋转不变性。光流场反映的是一种全局特征,表示像素点强度的变化。SIFT特征点可以很好地满足光流估计的条件。实验结果表明这种改进后的目标跟踪算法能应用于部分遮挡的情况,并且相对于传统光流法具有更高的精确度。

关键词: 目标跟踪, 光流法, 尺度不变特征, 模板更新

Abstract: This paper presents an object tracking algorithm that combines the optical flow estimation algorithm and the Scale Invariant Feature Transform(SIFT) with a new template update strategy for the change of scene and object. The SIFT feature is local feature which is invariant to the scale and rotation change of the image. The optical flow is a velocity field and the whole feature which represents the change of intensity of the pixel. The SIFT feature satisfies the condition of the optical flow estimation method. The experimental results show that this improved method can be used in partial covering tracking, and can achieve more accurate tracking than the traditional method.

Key words: object tracking, optical flow, Scale Invariant Feature Transform(SIFT) feature extraction, template update