Department of Electrical Engineering, Ben-Gurion University, Beer-Sheva, Israel.
IEEE Trans Image Process. 2010 May;19(5):1319-27. doi: 10.1109/TIP.2010.2040448. Epub 2010 Jan 12.
We propose two computational approaches for improving the retrieval of planar shapes. First, we suggest a geometrically motivated quadratic similarity measure, that is optimized by way of spectral relaxation of a quadratic assignment. By utilizing state-of-the-art shape descriptors and a pairwise serialization constraint, we derive a formulation that is resilient to boundary noise, articulations and nonrigid deformations. This allows both shape matching and retrieval. We also introduce a shape meta-similarity measure that agglomerates pairwise shape similarities and improves the retrieval accuracy. When applied to the MPEG-7 shape dataset in conjunction with the proposed geometric matching scheme, we obtained a retrieval rate of 92.5%.
我们提出了两种计算方法来提高平面形状的检索性能。首先，我们提出了一种基于几何的二次相似性度量，该度量通过二次分配的谱松弛进行优化。通过利用最新的形状描述符和一对序列化约束，我们得到了一种对边界噪声、关节和非刚体变形具有鲁棒性的公式，这允许进行形状匹配和检索。我们还引入了一种形状元相似性度量，它可以聚集成对的形状相似性并提高检索准确性。当与我们提出的几何匹配方案一起应用于 MPEG-7 形状数据集时，我们获得了 92.5%的检索率。
