A method and system for counting crowds

Abstract

The invention discloses a crowd counting method and a system based on a scale pyramid neural network, wherein the scale pyramid neural network structure is composed of VGG-16 as the basic skeleton, and multi-scale high-level features are extracted by embedding a scale pyramid module in the high-level. The scale pyramid module consists of four parallel cavities with different expansion ratios. Themethod comprises steps: inputting a picture to network, after a series of convolution, getting high-level features and transfering them to scale pyramid module, generating four kinds of feature maps,these four kinds of feature maps and the feature maps input to the module being in the 'channel' dimension series connection, transfering to the next convolution layer, and finally getting the densitymap through the convolution of 1*1. Compared with the prior art, the method of the invention has more efficient, more accurate and simpler network structure, and can apply modules for handling multi-scale problems to deep networks.

Description

technical field [0001] The invention belongs to the field of computer vision, and more specifically relates to a method and system for crowd counting or crowd density estimation. Background technique [0002] Crowd counting is an important research direction in the field of computer vision, and it has a wide range of applications in video surveillance, public safety, traffic monitoring, traffic monitoring, and scene understanding. A major difficulty of this task is the scale variation within and between scenes, that is, the multi-scale problem. At present, the methods for solving multi-scale problems are mainly divided into three categories: the first category is based on the multi-column structure method, which uses a multi-column structure, and sets different sizes for each column of convolution kernels to obtain different receptive fields to adapt to Human heads of different sizes. The second category is based on the image pyramid method, which scales the image into mul...

AI Technical Summary

Problems solved by technology

[0003] Aiming at the above defects or improvement needs of the prior art, the present invention provides a crowd counting method and system, thereby solving the problems of long training time, large amount of calculation, and high training complexity existing in the existing multi-column structure-based method. Technical issues with high and difficult training

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