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A finite element contour approach to affine invariant shape representation

机译:仿射不变形状表示的有限元轮廓方法

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This paper1 presents a novel shape representation approach, Finite Element Contour (FEC), based on studies of shape analysis from the perspective of Finite Element Method (FEM). We assume that an edge of a contour can be modeled as a bendable beam element. Linking finite number of beam elements end to end along the contour, we obtain a closed-loop Finite Element Contour model as an approximate physical model of the original shape. By this model, we can calculate its natural frequency, which is one of mechanical properties that directly related to the geometric shape, and employed it as the shape representation. FEC shape feature possesses translation and rotation invariant properties naturally. We also realized scale and unique affine normalization in few simple steps based on intrinsic physical properties of shape from FEM viewpoint. Experimental results validated that the proposed FEC feature is capable of identifying shape in object recognition task. It also can describe shape deformation. In the well-known MPEG 7 shape retrieval task, the enhanced FEC approach obtains Bullseye score 87.11%.
机译:本文 1 在基于有限元方法(FEM)的形状分析研究的基础上,提出了一种新颖的形状表示方法,即有限元轮廓(FEC)。我们假设轮廓的边缘可以建模为可弯曲梁单元。沿轮廓线将有限数量的梁单元首尾相连,我们获得了一个闭环有限元轮廓模型,作为原始形状的近似物理模型。通过该模型,我们可以计算其固有频率,该固有频率是与几何形状直接相关的机械特性之一,并将其​​用作形状表示。 FEC形状特征自然具有平移和旋转不变的特性。从FEM的角度出发,我们还基于形状的固有物理特性,通过几个简单的步骤就实现了规模化和独特的仿射归一化。实验结果验证了所提出的FEC功能能够识别物体识别任务中的形状。它还可以描述形状变形。在众所周知的MPEG 7形状检索任务中,增强的FEC方法获得了Bullseye得分87.11%。

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