运动图像中多目标的聚类分离

K. Inoue, K. Urahama
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引用次数: 17

摘要

提出了一种估计独立运动的刚体数量,并通过聚类方法将运动图像上跟踪的特征点分离成单个物体的方法。在该方法中,首先将特征点映射到适合于将其分组到每个对象的低维空间中。在该低维空间中,采用图谱法对聚类进行顺序提取。可以根据提取的聚类的内聚性变化来估计聚类即对象的数量。数值实验表明,该方法对透视投影的测量噪声和失真具有较强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Separation of multiple objects in motion images by clustering
A method is presented for estimating the number of rigid objects moving independently and separating the feature points tracked on a motion image into individual objects by clustering. In the method, feature points are firstly mapped into a low dimensional space suitable for grouping them into each object. In this low dimensional space, clusters are extracted sequentially by a graph spectral method. The number of clusters i.e. objects can be estimated on the basis of the variation in the cohesiveness of extracted clusters. We show by numerical experiments that the present method is robust to moderate measurement noises and distortion by perspective projection.
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