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A Survey on Crowd Counting Methods and Datasets

机译:人群计数方法和数据集调查

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摘要

Recent successful works of crowding counting are introduced. We summarize several classic achievements of traditional methods: regression methods, detection methods, and density map estimation methods. Some CNN models are categorized according to its function and structure. Specially, we discuss some problems have solved by CNN models like different scale, different background, and lack of label. CNN methods rely highly on the dataset, so several classic and popular datasets and some newly released dataset are presented. At last, we recognized probably the most convincing difficulties and issues which are investigated in crowd counting and density estimation utilizing computer vision and machine learning methods.
机译:介绍了最近成功的拥挤计数作品。 我们总结了传统方法的几种经典成就:回归方法,检测方法和密度图估计方法。 一些CNN模型根据其功能和结构进行分类。 特别是,我们讨论了不同规模,不同背景和缺乏标签的CNN模型解决了一些问题。 CNN方法高度依赖于数据集,因此呈现了几种经典和流行的数据集和一些新发布的数据集。 最后,我们可能认识到,利用计算机视觉和机器学习方法的人群计数和密度估计,可能是最令人信服的困难和问题。

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