Crowd counting method and system based on bimodal network
A crowd counting and dual-modal technology, applied in the field of computer vision, can solve problems such as deviation and difficult detection of crowds, and achieve the effects of reduced calculation, high resolution, and improved calculation efficiency
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Embodiment 1
[0046] like figure 1 As shown, this embodiment provides a method for crowd counting based on a dual-modal network. This embodiment uses this method as an example to illustrate the application of the server. It can be understood that this method can also be applied to terminals, and can also be applied to It includes terminals, servers and systems, and is realized through the interaction between terminals and servers. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or it can provide cloud services, cloud database, cloud computing, cloud function, cloud storage, network server, cloud communication, intermediate Cloud servers for basic cloud computing services such as software services, domain name services, security service CDN, and big data and artificial intelligence platforms. The terminal may be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart ...
Embodiment 2
[0057] This embodiment provides a crowd counting system based on a bimodal network.
[0058] A bimodal network-based crowd counting system comprising:
[0059] An image acquisition unit configured to: acquire an image data set of the crowd to be tested, and perform preprocessing;
[0060] A crowd counting unit configured to: input the preprocessed crowd image data set into a pre-trained crowd counting network, generate a density map and count the number of people;
[0061] Wherein, the crowd counting network includes three parallel branches in the vertical direction and three stages in the horizontal direction, and the three parallel branches include: two specific modality branches and a shared modality branch; the three stages include : front-end network, middle-end network and back-end network; the front-end network extracts the specific modal features extracted by two specific modal branches, and obtains the basic features of the two modalities, the basic features of the t...
Embodiment 3
[0064] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps in the method for crowd counting based on a dual-mode network as described in the first embodiment above are implemented.
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