Crowd counting method and system based on multi-scale feature information

Abstract

The invention provides a crowd counting method based on multi-scale feature information, and belongs to the technical field of computer vision, and the method comprises the steps: carrying out the preprocessing of an obtained image, and obtaining a crowd density map corresponding to the image; inputting the obtained crowd density map into a preset multi-feature extraction network model, performinglayer-by-layer calculation to obtain a plurality of feature maps of which the scales are gradually reduced, and performing reverse layer-by-layer side edge connection on the obtained feature maps ofthe scales to obtain a plurality of connected feature maps; performing feature fusion on the plurality of obtained connected feature maps to obtain a multi-scale feature map, performing density map regression to obtain a final crowd density map, and further obtaining a final crowd counting value. According to the method and the device, the influence of large-scale change of crowds on crowd counting is solved, the loss caused by detail information loss after layer-by-layer abstract expression and down-sampling of a pooling layer is further reduced by adopting a feature map fusion mode, and moredetail information can be reserved, so counting of multi-scale dense crowds with a relatively good effect is realized.

Description

technical field [0001] The present disclosure relates to the technical field of computer vision, in particular to a crowd counting method and system based on multi-scale feature information. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art. [0003] Focusing on the current era theme of peace and development, the world today has entered a stage of rapid peaceful development. The population has grown exponentially, and the resulting dense crowd gatherings in public places have become more and more frequent, such as large-scale concerts, sports competitions, and large-scale crowd gatherings and parades that are commonplace today. Under such circumstances, crowd stampedes and riots have become more and more frequent. For example, the stampede on the Bund in Shanghai in 2015 has reached the level of major casualty accidents stipulated by our country. ...

AI Technical Summary

Problems solved by technology

[0006] However, the inventors of the present disclosure found that the existing multi-column CNN generally uses the highest-level feature map to regress to generate a density map, and the high-level feature map will be lost after being abstracted layer by layer and down-sampled by the pooling layer. More detailed information even filters out some small-scale targets, resulting in poor counting ability of the algorithm for small targets

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