Crowd counting model based on deep learning and implementation method thereof

Abstract

The invention discloses a crowd counting model based on deep learning and an implementation method thereof, and the method comprises the steps: S1, obtaining a crowd image, carrying out the preprocessing of the obtained crowd image, and generating a corresponding crowd density map through marking information; s2, zooming the input crowd image into a plurality of scale versions, extracting featuresof each scale through a plurality of sub-networks, and enhancing the features of each scale by using a feature enhancement module; s3, combining the features generated by the plurality of sub-networks to generate an estimated crowd density map; s4, calculating loss by utilizing the estimated crowd density map and the real crowd density map, and updating model parameters; and S5, iteratively carrying out the training process of the steps S1-S4 for multiple times by utilizing different crowd images until a stop condition is met.

Description

technical field [0001] The present invention relates to the technical field of computer vision based on deep learning, in particular to a crowd counting model based on deep learning and its implementation method. Background technique [0002] Crowd counting is an important research topic in computer vision, whose goal is to automatically generate crowd density maps from crowd images and estimate the number of people in a scene. Recently, this task has received increasing attention in both academia and industry due to its wide range of practical applications, such as video surveillance, traffic management, and crowd flow prediction. [0003] Traditional crowd counting algorithms generally require complex preprocessing of images, and require manual design and feature extraction. In the case of cross-scenes, features often need to be re-extracted, which has poor adaptability. In recent years, the successful application of convolutional neural networks has brought a major break...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a crowd counting model based on deep learning and its implementation method to solve the problems of the prior art The problem of crowd size differences in different scenarios

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