Image head counting method and device based on context attention

Abstract

The invention discloses a picture head counting method and device based on context attention. According to the method, a part of a convolutional layer of VGG16 is used as a front-end network, four 64-channel density maps are generated in a middle-end network and a rear-end network, context feature sampling is introduced, and a four-channel coefficient feature map is formed. And further performing convolution and stacking on the four 64-channel density maps in the fusion network to obtain a four-channel intermediate density map. The intermediate density map and the coefficient feature map after Sigmoid or Softmax operation are multiplied pixel by pixel and then fused, a final crowd density map is obtained, and finally the number of people is obtained according to integral accumulation of the crowd density map. Compared with head counting based on a multi-column neural network, the counting efficiency can be improved to a certain extent, and compared with existing counting, the accuracy is greatly improved.

Description

technical field [0001] The present invention relates to a picture head counting technology, in particular to a picture head counting technology based on deep learning of convolutional neural networks. Background technique [0002] Patent document CN 112651390 A discloses a method and device for counting people in pictures based on convolutional neural network. The convolutional neural network-based image head counting method adopts a single-column convolutional neural network. There are many methods for image head counting based on multi-column convolutional neural networks. Compared with these methods for counting heads in pictures based on multi-column convolutional neural networks, the above methods for counting heads in pictures based on single-column convolutional neural networks can effectively reduce the amount of model parameters, thereby improving the efficiency of counting. At the same time, the method has a high accuracy in counting the heads of pictures in gene...

AI Technical Summary

Problems solved by technology

However, this method has the problem that the accuracy of head counting in pictures is poor and the error is large in the scene of high-density crowds.

Images