NonLocal via Local–NonLinear via Linear: A New Part-coding Distance Field via Screened Poisson Equation
NonLocal via Local–NonLinear via Linear: A New Part-coding Distance Field via Screened Poisson Equation
复制标题
非局部通过局部–非线性通过线性：通过屏蔽泊松方程的新部分编码距离场
DOI：
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发表时间：
2016
影响因子：
2
通讯作者：
S. Tari
中科院分区：
文献类型：
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作者：
Murat Genctav;Asli Gençtav;S. Tari
形状感知中的有趣现象是非局部和非线性的。因此，至关重要的是，形状感知系统表现出非局部和非线性的行为。然而，从计算的角度来看，既不需要非线性，也不需要非局部性。我们提出了一个重复使用的筛选泊松偏微分方程（导致一个稀疏的线性系统）计算的部分编码和提取的距离场，从形状域$$varOmega子集R^n$$Ω <$Rn到真实的线的映射。尽管本地和线性计算，该领域表现出高度的非线性和非本地的行为，导致本地和全球结构的高效和鲁棒的编码。所提出的计算方案适用于任意尺寸的形状，以及由碎片部分轮廓所隐含的形状。局部行为独立于形状所在的图像上下文。
Interesting phenomena in shape perception is nonlocal and nonlinear. Thus, it is crucial that a shape perception system exhibits a nonlocal and nonlinear behaviour. From the computational point of view, however, neither nonlinearity nor nonlocality is desired. We propose a repeated use of Screened Poisson PDE (leading to a sparse linear system) to compute a part coding and extracting distance field, a mapping from the shape domain $$varOmega subset R^n$$Ω⊂Rn to the real line. Despite local and linear computations, the field exhibits highly nonlinear and nonlocal behaviour, leading to efficient and robust coding of both the local and the global structures. The proposed computation scheme is applicable to shapes in arbitrary dimensions as well as shapes implied by fragmented partial contours. The local behaviour is independent of the image context in which the shape resides.