With the rapid development of science and technology and the rise of deep learning, in recent years, image-based people counting has become a hot research topic in the field of computer vision. The method based on the density map retains the spatial information of the crowd in the picture, and on this basis, the network model of deep learning training is also used to improve the accuracy of the people counting. This paper mainly analyzes the traditional counting methods, introduces the common datasets used in people counting. We mainly conducted research and analysis on recent years' people counting methods of generating high-quality population density map through CNN method, the end-to-end convolutional neural network model surprised us with the accuracy of the people counting. Finally, this paper prospects the future research trend of people counting.
people counting, computer vision, density map, convolutional neural network (CNN)
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