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Detection of obscured and partially covered objects using partial network matching and an image feature network-based object recognition algorithm

机译:使用部分网络匹配和基于图像特征网络的对象识别算法检测被遮挡和部分覆盖的对象

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摘要

An approach to image classification based on the analysis of the network of points generated by an image feature detection algorithm has been proposed. This network-based approach looks at the networks produced by two images and scale and then compare them, making a classification decision. This paper considers techniques to handle the problem posed by input images that are obscured or in which the target is partially covered. These approaches are compared with the base algorithm to assess the impact on performance in the general case, obscured scenarios and obstructed scenarios.
机译:提出了一种基于图像特征检测算法生成的点网络分析的图像分类方法。这种基于网络的方法查看由两个图像生成的网络并进行缩放,然后将它们进行比较,从而做出分类决策。本文考虑了处理因输入图像模糊或部分覆盖目标而造成的问题的技术。将这些方法与基本算法进行比较,以评估一般情况,模糊场景和阻塞场景对性能的影响。

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