论文标题
带有图像分割的二进制标签的凸形表示：模型和快速算法
Convex Shape Representation with Binary Labels for Image Segmentation: Models and Fast Algorithms
论文作者
论文摘要
我们提出了一种新颖有效的二进制表示形状。我们显示了相关指标函数的形状凸度与某些属性之间的等效性。提出的方法具有两个优点。首先，表示形式基于对二进制函数的简单不平等约束，而不是凸形的定义，这使我们能够为具有凸面的各种应用程序获得有效的算法。其次，此方法与相关形状的维度无关。为了显示提出的表示方法的有效性，我们将其与基于概率的模型合并为对象分割，并以凸面性为先验。给出了有效的算法，以使用Lagrange乘数方法和线性近似来求解所提出的模型。进行了各种实验以显示所提出的方法的优越性。
We present a novel and effective binary representation for convex shapes. We show the equivalence between the shape convexity and some properties of the associated indicator function. The proposed method has two advantages. Firstly, the representation is based on a simple inequality constraint on the binary function rather than the definition of convex shapes, which allows us to obtain efficient algorithms for various applications with convexity prior. Secondly, this method is independent of the dimension of the concerned shape. In order to show the effectiveness of the proposed representation approach, we incorporate it with a probability based model for object segmentation with convexity prior. Efficient algorithms are given to solve the proposed models using Lagrange multiplier methods and linear approximations. Various experiments are given to show the superiority of the proposed methods.
