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Affine-Invariant Multi-reference Shape Priors for Active Contours

机译:用于活动轮廓的仿射不变的多引用形状前导

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We present a new way of constraining the evolution of a region-based active contour with respect to a set of reference shapes. The approach is based on a description of shapes by the Legendre moments computed from their characteristic function. This provides a region-based representation that can handle arbitrary shape topologies. Moreover, exploiting the properties of moments, it is possible to include intrinsic affine invariance in the descriptor, which solves the issue of shape alignment without increasing the number of d.o.f. of the initial problem and allows introducing geometric shape variabilities. Our new shape prior is based on a distance between the descriptors of the evolving curve and a reference shape. The proposed model naturally extends to the case where multiple reference shapes are simultaneously considered. Minimizing the shape energy, leads to a geometric flow that does not rely on any particular representation of the contour and can be implemented with any contour evolution algorithm. We introduce our prior into a two-class segmentation functional, showing its benefits on segmentation results in presence of severe occlusions and clutter. Examples illustrate the ability of the model to deal with large affine deformation and to take into account a set of reference shapes of different topologies.
机译:我们提出了一种限制基于区域的有源轮廓的演变的新方法,相对于一组参考形状。该方法基于从其特征函数计算的图例矩的形状描述。这提供了一种基于区域的表示,其可以处理任意形状拓扑。此外,利用矩的性质,可以包括描述符中的内部仿射不变性,该描述符解决了形状对准的问题而不增加D.O.f的数量。初始问题,允许引入几何形状可变性。我们的新形状以前基于演进曲线的描述符和参考形状之间的距离。所提出的模型自然地延伸到同时考虑多个参考形状的情况。最小化形状能量,导致不依赖于轮廓的任何特定表示的几何流动,并且可以用任何轮廓演进算法实现。我们之前介绍了两类分段功能,在存在严重的闭塞和杂乱的情况下,对分段结果的益处。示例说明了模型处理大型仿射变形的能力,并考虑到不同拓扑的一组参考形状。

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