Department of Computer Science, York University, Toronto, Ont. M3J 1P3, Canada.
IEEE Trans Image Process. 2000;9(1):141-7. doi: 10.1109/83.817606.
We propose a shape matching algorithm for deformed shapes based on dynamic programming. Our algorithm is capable of grouping together segments at finer scales in order to come up with appropriate correspondences with segments at coarser scales. We illustrate the effectiveness of our algorithm in retrieval of shapes by content on two different two-dimensional (2-D) datasets, one of static hand gesture shapes and another of marine life shapes. We also demonstrate the superiority of our approach over traditional approaches to shape matching and retrieval, such as Fourier descriptors and geometric and sequential moments. Our evaluation is based on human relevance judgments following a well-established methodology from the information retrieval field.
我们提出了一种基于动态规划的变形形状匹配算法。我们的算法能够在更精细的尺度上对片段进行分组，以便在更粗糙的尺度上找到与片段相对应的合适匹配。我们在两个不同的二维（2-D）数据集上，一个是静态手势形状，另一个是海洋生物形状，通过内容检索展示了我们算法的有效性。我们还展示了我们的方法相对于传统的形状匹配和检索方法，如傅里叶描述符、几何和顺序矩的优越性。我们的评估是基于信息检索领域的一种成熟方法的人类相关性判断。
