利用多级量化局部纹理特征的图像跟踪算法

摘要

针对传统的基于纹理特征的跟踪算法采用统计直方图描述目标，表达不够精确且计算量较大的问题，提出一种基于多级量化的局部纹理特征的点对点的图像跟踪算法。首先定义了一种高维纹理特征，其对单个的点具有较强的描述能力；随后通过矢量运算进行点对点匹配，根据匹配得出的点集的空间位置，利用均值漂移矢量实现初步定位；最后通过连续缩放窗口比例，同时使用颜色信息验证候选窗口与原始窗口的相似度，确定目标的位置和尺度。实验结果表明，该算法在场景复杂、噪声较大的环境中仍能准确地搜索到目标；在目标尺度变化时也具有较强的鲁棒性。%To solve the problem of inaccuracy and large calculation of traditional histogram-based tracker, this paper proposes a local feature-based tracking algorithm using multi-scale texture descriptor for each point. A high-dimensional texture descriptor with discriminative power is defined. Vector operation is applied to points matching and primary mapping is implemented through mean-shift according to the position of spatial point set. Subsequently, the location and scale of the object is determined by verifying the similarity between candidates and original target according to color information while the window is zooming. The results show the robustness of this algorithm against clutter, noise and change in target scale.