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Grouping method based on feature matching for tracking and recognition of complex objects

机译:基于特征匹配的分组方法,用于跟踪和识别复杂对象的

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We propose a grouping algorithm for tracking and recognition of complex objects in video images. The algorithm is based on region-growing image segmentation for dividing each image into its constituent elements or segments and feature matching using the characteristic features of these elements. All segments in video images, which can be viewed as simple objects, can be detected and tracked with this algorithm no matter whether they are moving or not. But, for complex-object tracking and recognition, it is additionally necessary to group all elements belonging to these complex objects based on common characteristic features. As a result of the grouping method, the proposed algorithm is able to detect and track moving complex objects like e.g. cars in video images. This paper describes the proposed algorithm in detail and verifies its capabilities by simulation results with MATLAB [1].
机译:我们提出了一种用于跟踪和识别视频图像中复杂对象的分组算法。该算法基于区域生长的图像分割,用于将每个图像划分为其组成元素或片段,并且使用这些元素的特征特征匹配。无论是移动还是没有,都可以通过该算法检测和跟踪视频图像中的所有段,它可以被视为简单的对象。但是,对于复杂对象跟踪和识别,另外需要基于公共特征特征对属于这些复杂对象的所有元素进行分组。作为分组方法的结果,所提出的算法能够检测和跟踪移动复杂的对象,如例如,在视频图像中的汽车。本文详细介绍了所提出的算法,并通过Matlab [1]的仿真结果来验证其功能。

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