基于Tensor-SIFT的地球移动器距离轮廓跟踪
Tensor-SIFT based Earth Mover's Distance for Contour Tracking
摘要：
在恶劣环境中的轮廓跟踪是一个具有挑战性的问题，由于杂乱的背景，光照变化，遮挡和噪声，等等。本文提出了一个强大的轮廓跟踪方法，通过贡献的一些关键问题，包括（a）区域功能制定和优化;（b）设计一个强大的和有效的功能;和（c）开发一个综合的跟踪算法。首先，我们制定了一个区域功能的基础上强大的地球移动器的距离（EMD）与核密度分布建模，并提出了一个两阶段的优化方法。在第一阶段，假设候选轮廓是固定的，我们表示EMD运输问题，并解决它的单纯形算法。其次，利用形状导数理论，对运输问题最优解附近的轮廓进行扰动分析。这导致了一个偏微分方程（PDE），支配的轮廓演变。其次，我们设计了一个新颖而有效的跟踪应用程序的功能。提出了一种基于张量分解的降维方法，实现了一种用于表征图像局部区域特性的SIFT特征的低维描述，称为Tensor-SIFT。Tensor-SIFT适用于彩色和灰度图像，非常独特，对照度变化和噪音不敏感。最后，我们开发了一个综合算法，结合了各种技术的单纯形算法，窄带水平集和快速行进算法。特别地，我们介绍了帧间初始化方法和终止PDE迭代的停止准则。在具有挑战性的图像序列上的实验表明，所提出的工作具有良好的性能。
英文摘要：
Contour tracking in adverse environments is a challenging problem due to cluttered background, illumination variation, occlusion, and noise, among others. This paper presents a robust contour tracking method by contributing to some of the key issues involved, including (a) a region functional formulation and its optimization; (b) design of a robust and effective feature; and (c) development of an integrated tracking algorithm. First, we formulate a region functional based on robust Earth Mover's distance (EMD) with kernel density for distribution modeling, and propose a two-phase method for its optimization. In the first phase, letting the candidate contour be fixed, we express EMD as the transportation problem and solve it by the simplex algorithm. Next, using the theory of shape derivative, we make a perturbation analysis of the contour around the best solution to the transportation problem. This leads to a partial differential equation (PDE) that governs the contour evolution. Second, we design a novel and effective feature for tracking applications. We propose a dimensionality reduction method by tensor decomposition, achieving a low-dimensional description of SIFT features called Tensor-SIFT for characterizing local image region properties. Applicable to both color and gray-level images, Tensor-SIFT is very distinctive, insensitive to illumination changes, and noise. Finally, we develop an integrated algorithm that combines various techniques of the simplex algorithm, narrow-band level set and fast marching algorithms. Particularly, we introduce an inter-frame initialization method and a stopping criterion for the termination of PDE iteration. Experiments in challenging image sequences show that the proposed work has promising performance.
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