Method and system for assisting human flow regulation at public place based on deep learning
A public place and deep learning technology, applied in the field of deep learning, can solve the problems of lack of flexibility and freedom in the schedule of the target population, low utilization of public resources, waste of time for the target population, etc., to achieve improved resource utilization and good detection Speed, the effect of regulating the flow of people
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Embodiment 1
[0062] This embodiment provides an auxiliary method for regulating the flow of people in public places based on deep learning, see figure 2 , the method includes:
[0063] 201: Obtain the flow of people at N time points before the current time point; wherein, N is an integer greater than or equal to 2;
[0064] 202: According to the acquired flow of people at N time points before the current time point, predict the flow of people at several time points in the future;
[0065] 203: According to the predicted human flow at several time points in the future, adjust the actual human flow at several time points in the future by recommending to the user.
[0066] In this embodiment, according to the obtained flow of people at N time points before the current time point, the flow of people at several time points in the future is predicted, so that according to the flow of people at several points in the future predicted, the user flow is recommended to the user. The actual flow of...
Embodiment 2
[0068] This embodiment provides an auxiliary method for regulating the flow of people in public places based on deep learning, see image 3 , the method includes:
[0069] In this embodiment, the image acquisition device 120 is a surveillance camera, the processor 140 is a computer, the terminal 160 is a mobile phone, and the implementation environment is illustrated by taking a university campus public bathroom as an example;
[0070] 301: Obtain crowd images at N time points before the current time point;
[0071] Specifically, the monitoring camera is installed in the direction of the entrance of the public bathroom on the university campus, and the people entering and leaving the entrance are overlooked at a certain angle, and the captured crowd images are transmitted to the computer in real time. The computer has received the crowd images at the current time point. Crowd images at the previous N time points.
[0072] 302: According to the acquired crowd images at N time...
Embodiment 3
[0101] This embodiment provides an auxiliary system for regulating the flow of people in public places based on deep learning, see Figure 5 , the system includes:
[0102] An acquisition module 510, configured to acquire the flow of people at N time points before the current time point; wherein, N is an integer greater than or equal to 2;
[0103] Prediction module 520, for predicting the number of people flow at several time points in the future according to the flow of people at N time points before the current time point acquired by the acquisition module 510;
[0104] The adjustment module 530 is configured to adjust the actual number of people at several time points in the future according to the number of people at several time points in the future predicted by the prediction module 520 by recommending to the user.
[0105] In this embodiment, according to the obtained flow of people at N time points before the current time point, the flow of people at several time poi...
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