CN112668458A - Experience hall management system based on face recognition - Google Patents
Experience hall management system based on face recognition Download PDFInfo
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- CN112668458A CN112668458A CN202011563797.8A CN202011563797A CN112668458A CN 112668458 A CN112668458 A CN 112668458A CN 202011563797 A CN202011563797 A CN 202011563797A CN 112668458 A CN112668458 A CN 112668458A
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Abstract
The invention relates to the technical field of experience hall management, and particularly discloses an experience hall management system based on face recognition, which comprises a first camera, a second camera, experience equipment, a network switch, a video processor, a background processor and a hall terminal, wherein the first camera, the second camera and the experience equipment are all in communication connection with the network switch, the network switch is in communication connection with the background processor through the video processor, the network switch is also in direct communication connection with the background processor, and the background processor is in communication connection with the hall terminal. The experience hall management system based on the face recognition can effectively cooperate with experience hall managers and experience activity organizers to visually know the actual conditions and the experience effect conditions of the experience hall managers participating in the experience projects, and can evaluate the mastering degree of the safety precaution consciousness of the experience hall managers participating in the experience projects, so that powerful support is provided for further deepening and strengthening public safety precaution work.
Description
Technical Field
The invention relates to the technical field of experience hall management, in particular to an experience hall management system based on face recognition.
Background
The main purpose in public safety experience shop is to promote the public safety precaution consciousness of experience person, and experience person experiences equipment through the operation, learns safety precaution knowledge.
However, at present, a plurality of experience shops do not manage the information of experience personnel and do not manage the experience results of the experience personnel, so that managers or experience activity organizers of the experience shops cannot judge which experience items the experience personnel actually participate in, and cannot judge the public safety precaution consciousness degree and the improvement condition of the experience personnel.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, provides an experience hall management system based on face recognition, can effectively cooperate with experience hall managers and experience activity organizers to visually know the actual conditions and the experience effects of the experience players participating in the experience project, and can evaluate the mastering degree of the safety precaution consciousness of the experience players.
As a first aspect of the present invention, an experience center management system based on face recognition is provided, including a first camera, a second camera, an experience device, a network switch, a video processor, a background processor, and a venue terminal, where the first camera, the second camera, and the experience device are all communicatively connected to the network switch, the network switch is communicatively connected to the background processor through the video processor, the network switch is further directly communicatively connected to the background processor, and the background processor is communicatively connected to the venue terminal; wherein the content of the first and second substances,
the first camera is used for acquiring a first target face image and transmitting the first target face image to the video processor through the network switch;
the second camera is used for acquiring a second target face image and transmitting the second target face image to the video processor through the network switch;
the video processor is used for receiving the first target face image and the second target face image; judging whether the first target face image exists in a preset sample training library, if so, judging that the first target face image is recorded into the preset sample training library, otherwise, recording the first target face image into the preset sample training library; judging whether the second target face image exists in the preset sample training library, if so, sending a device starting instruction to the background processor, otherwise, not outputting any instruction to the background processor;
the background processor is configured to send the received device start instruction to the experience device through the network switch, and send an experience result corresponding to the second target face image generated by the experience device to the venue terminal;
and the experience equipment is used for starting when the equipment starting instruction is received and generating an experience result corresponding to the second target face image.
Further, the video processor comprises an image acquisition module, a feature extraction and selection module, a face recognition module and an image training module, wherein,
the image acquisition module is used for acquiring first target face video stream information from the first camera, storing the first target face video stream information into a plurality of static first target face images in a frame mode, carrying out image normalization processing on the static first target face images and converting the first target face images into first target face gray level images;
the feature extraction and selection module is used for extracting feature points of each first target face gray level image and generating feature vectors of each first target face gray level image according to the feature points of each first target face gray level image;
the face recognition module is used for comparing the feature vector of each generated first target face gray level image with the feature vector of the sample image in the preset sample training library, wherein a judgment threshold value is set as S, if the comparison result is greater than S, the first target face image is judged to be an unknown face, and the first target face image is sent to the image training module for inputting; if the comparison result is smaller than S, judging that the first target face image is recorded into the preset sample training library;
the image training module comprises the preset sample training library and is used for inputting the received first target face image into the preset sample training library.
Further, the image acquisition module is further configured to acquire second target face video stream information from the second camera, store the second target face video stream information as a plurality of static second target face images in a frame manner, perform image normalization processing on the static second target face images, and convert the second target face images into second target face grayscale images;
the feature extraction and selection module is further configured to extract feature points of each second target face grayscale image, and generate a feature vector of each second target face grayscale image according to the feature points of each second target face grayscale image;
the face recognition module is further configured to compare the feature vector of each generated second target face grayscale image with the feature vector of the sample image in the preset sample training library, where a determination threshold is set to be S, and if the comparison result is greater than S, it is determined that the second target face image is an unknown face, and no instruction is output to the background processor; and if the comparison result is smaller than S, judging that the second target face image exists in the preset sample training library, and sending the equipment starting instruction to the background processor.
Further, the frequency of storing the first target face image is not less than 15 sheets/second.
Further, the frequency of storing the second target face image is not less than 15 sheets/second.
Further, the image training module is specifically configured to,
adding 10 first target face images as sample images in the preset sample training library;
and performing recognition and comparison on the added 10 sample images through KL (karhunen-Loeve) conversion, if the recognition rate is 100%, recording the added 10 sample images into the preset sample training library, otherwise, adding 10 new first target face images as the sample images in the preset sample training library again, and performing subsequent recognition and comparison actions to circulate until the recognition rate reaches 100%.
Further, the first camera is mounted at an entrance of the experience hall.
Further, the second camera is mounted above the experience device.
The experience hall management system based on the face recognition provided by the invention has the following advantages:
(1) according to the invention, the image recognition technology and the equipment experience management are combined, so that the automatic matching of experience personnel and experience results is realized;
(2) the invention provides effective support for the normal operation management of the venue, and reduces the management cost;
(3) the present invention makes a beneficial attempt at venue automation management.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
Fig. 1 is a block diagram of an experience center management system based on face recognition according to the present invention.
Fig. 2 is a block diagram of a video processor according to the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description will be given to the specific implementation, structure, features and effects of the human face recognition based experience hall management system according to the present invention with reference to the accompanying drawings and the preferred embodiments. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without any inventive step, are within the scope of the present invention.
In this embodiment, a system for managing an experience hall based on face recognition is provided, as shown in fig. 1, the system for managing an experience hall based on face recognition includes a first camera, a second camera, experience equipment, a network switch, a video processor, a background processor, and a venue terminal, where the first camera, the second camera, and the experience equipment are all communicatively connected to the network switch, the network switch is communicatively connected to the background processor through the video processor, the network switch is further directly communicatively connected to the background processor, and the background processor is communicatively connected to the venue terminal; wherein the content of the first and second substances,
the first camera is used for acquiring a first target face image and transmitting the first target face image to the video processor through the network switch;
the second camera is used for acquiring a second target face image and transmitting the second target face image to the video processor through the network switch;
the video processor is used for receiving the first target face image and the second target face image; judging whether the first target face image exists in a preset sample training library, if so, judging that the first target face image is recorded into the preset sample training library, otherwise, recording the first target face image into the preset sample training library; judging whether the second target face image exists in the preset sample training library, if so, sending a device starting instruction to the background processor, otherwise, not outputting any instruction to the background processor;
the background processor is configured to send the received device start instruction to the experience device through the network switch, and send an experience result corresponding to the second target face image generated by the experience device to the venue terminal;
and the experience equipment is used for starting when the equipment starting instruction is received and generating an experience result corresponding to the second target face image.
Preferably, as shown in fig. 2, the video processor includes an image acquisition module, a feature extraction and selection module, a face recognition module, and an image training module, wherein,
the image acquisition module is used for acquiring first target face video stream information from the first camera, storing the first target face video stream information into a plurality of static first target face images in a frame mode, carrying out image normalization processing on the static first target face images and converting the first target face images into first target face gray level images;
the feature extraction and selection module is used for extracting feature points of each first target face gray level image and generating feature vectors of each first target face gray level image according to the feature points of each first target face gray level image;
the face recognition module is used for comparing the feature vector of each generated first target face gray level image with the feature vector of the sample image in the preset sample training library, wherein a judgment threshold value is set as S, if the comparison result is greater than S, the first target face image is judged to be an unknown face, and the first target face image is sent to the image training module for inputting; if the comparison result is smaller than S, judging that the first target face image is recorded into the preset sample training library;
the image training module comprises the preset sample training library and is used for inputting the received first target face image into the preset sample training library.
Preferably, the image acquisition module is further configured to acquire second target face video stream information from the second camera, store the second target face video stream information as a plurality of static second target face images in a frame manner, perform image normalization processing on the static second target face images, and convert the second target face images into second target face grayscale images;
the feature extraction and selection module is further configured to extract feature points of each second target face grayscale image, and generate a feature vector of each second target face grayscale image according to the feature points of each second target face grayscale image;
the face recognition module is further configured to compare the feature vector of each generated second target face grayscale image with the feature vector of the sample image in the preset sample training library, where a determination threshold is set to be S, and if the comparison result is greater than S, it is determined that the second target face image is an unknown face, and no instruction is output to the background processor; and if the comparison result is smaller than S, judging that the second target face image exists in the preset sample training library, and sending the equipment starting instruction to the background processor.
Preferably, the frequency of storing the first target face image is not less than 15 sheets/second.
Preferably, the frequency of storing the second target face image is not less than 15 sheets/second.
Preferably, the image training module is specifically adapted to,
adding 10 first target face images as sample images in the preset sample training library;
and performing recognition and comparison on the added 10 sample images through KL (karhunen-Loeve) conversion, if the recognition rate is 100%, recording the added 10 sample images into the preset sample training library, otherwise, adding 10 new first target face images as the sample images in the preset sample training library again, and performing subsequent recognition and comparison actions to circulate until the recognition rate reaches 100%.
Specifically, the working process of the image training module is as follows:
1. adding 10 pieces of the first target face images as sample images in a preset sample training library for the collected face images which are not in the preset sample training library;
2. identifying and comparing the newly added 10 sample images through KL (karhunen-Loeve) conversion, wherein the identification time of the newly added sample images is not more than 10 seconds;
3. if the recognition rate is 100%, compiling the new 10 sample images into a preset sample training library; if the recognition rate does not reach 100%, repeating the step 1 to make the recognition rate reach 100%.
Preferably, the first camera is mounted at an entrance to the experience hall.
Preferably, the second camera is mounted above the experience device.
The detailed working flow of the experience hall management system based on the face recognition provided by the invention is as follows:
step S1, installing a first camera, a second camera and a plurality of experience equipment in the venue in place; the second cameras are installed above the experience equipment, and the heights of the installation positions of the first cameras and the second cameras are not more than 1.8 m;
step S2, when the experiential person enters the venue, the face information needs to be collected in front of the first camera at the door, namely the experiential person stands in front of the first camera at the door for 2-3 seconds;
step S3, the first camera at the door transmits the human face video stream information of the experiential person to the video processor through the network switch, the video processor judges whether the experiential person entering the venue enters the venue for the first time, if so, the face information is input and marked;
s3.1, an image acquisition module acquires face video stream information of an experiencer from a first camera at a door, stores the face video stream information as a static picture in a frame mode, and performs image normalization processing on the static picture to convert an original face image into a gray image;
s3.2, extracting the characteristic points of the gray level images by a characteristic extraction and selection module, and extracting the characteristic vector of each gray level image;
s3.3, comparing the extracted feature vector with an image in a preset sample training library by the face recognition module, setting a judgment threshold value to be S, and when the comparison result is greater than S, the image is an unknown face, and inputting the image into the preset sample training library; if the comparison result is less than S, the image is determined to be recorded into the sample training library;
s3.4, images in the sample training library are continuously increased along with the increase of the collection quantity;
s3.5, transmitting the information of the existing images and the newly added images in the sample training library to a background processor through a network;
step S4, after the experiential staff enters the venue, before the experiential staff experiences at the experiential equipment, the second camera above the experiential equipment collects the face information of the experiential staff, the face information is judged through the video processor, when the judgment result shows that the face information is recorded into the sample training library, the experiential equipment can normally operate, and the judgment time is not more than 10 seconds; if the face information is judged not to be recorded into the sample training library, the experience equipment cannot be started;
step S5, after the experience equipment is started, experience personnel perform equipment experience, and the experience equipment records the operation time and the experience result of the experience personnel and transmits the operation time and the experience result to the background processor through the network switch;
s6, repeating the steps S4 and S5 every time experience personnel perform experiences of different projects;
step S7, the background processor collects the experience report results of the experience personnel each time and generates an experience report;
step S8, the venue manager can obtain the experience report of the experiencer through the venue terminal.
The experience hall management system based on the face recognition can effectively cooperate with experience hall managers and experience activity organizers to visually know the actual conditions and the experience effect conditions of the experience hall managers participating in the experience projects, and can evaluate the mastering degree of the safety precaution consciousness of the experience hall managers participating in the experience projects, so that powerful support is provided for further deepening and strengthening public safety precaution work.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (8)
1. An experience center management system based on face recognition is characterized by comprising a first camera, a second camera, experience equipment, a network switch, a video processor, a background processor and a venue terminal, wherein the first camera, the second camera and the experience equipment are all in communication connection with the network switch, the network switch is in communication connection with the background processor through the video processor, the network switch is also in direct communication connection with the background processor, and the background processor is in communication connection with the venue terminal; wherein the content of the first and second substances,
the first camera is used for acquiring a first target face image and transmitting the first target face image to the video processor through the network switch;
the second camera is used for acquiring a second target face image and transmitting the second target face image to the video processor through the network switch;
the video processor is used for receiving the first target face image and the second target face image; judging whether the first target face image exists in a preset sample training library, if so, judging that the first target face image is recorded into the preset sample training library, otherwise, recording the first target face image into the preset sample training library; judging whether the second target face image exists in the preset sample training library, if so, sending a device starting instruction to the background processor, otherwise, not outputting any instruction to the background processor;
the background processor is configured to send the received device start instruction to the experience device through the network switch, and send an experience result corresponding to the second target face image generated by the experience device to the venue terminal;
and the experience equipment is used for starting when the equipment starting instruction is received and generating an experience result corresponding to the second target face image.
2. The face recognition based experience hall management system of claim 1, wherein the video processor comprises an image acquisition module, a feature extraction and selection module, a face recognition module, and an image training module, wherein,
the image acquisition module is used for acquiring first target face video stream information from the first camera, storing the first target face video stream information into a plurality of static first target face images in a frame mode, carrying out image normalization processing on the static first target face images and converting the first target face images into first target face gray level images;
the feature extraction and selection module is used for extracting feature points of each first target face gray level image and generating feature vectors of each first target face gray level image according to the feature points of each first target face gray level image;
the face recognition module is used for comparing the feature vector of each generated first target face gray level image with the feature vector of the sample image in the preset sample training library, wherein a judgment threshold value is set as S, if the comparison result is greater than S, the first target face image is judged to be an unknown face, and the first target face image is sent to the image training module for inputting; if the comparison result is smaller than S, judging that the first target face image is recorded into the preset sample training library;
the image training module comprises the preset sample training library and is used for inputting the received first target face image into the preset sample training library.
3. The face recognition based experience hall management system of claim 2,
the image acquisition module is further configured to acquire second target face video stream information from the second camera, store the second target face video stream information as a plurality of static second target face images in a frame manner, perform image normalization processing on the static second target face images, and convert the second target face images into second target face grayscale images;
the feature extraction and selection module is further configured to extract feature points of each second target face grayscale image, and generate a feature vector of each second target face grayscale image according to the feature points of each second target face grayscale image;
the face recognition module is further configured to compare the feature vector of each generated second target face grayscale image with the feature vector of the sample image in the preset sample training library, where a determination threshold is set to be S, and if the comparison result is greater than S, it is determined that the second target face image is an unknown face, and no instruction is output to the background processor; and if the comparison result is smaller than S, judging that the second target face image exists in the preset sample training library, and sending the equipment starting instruction to the background processor.
4. The human face recognition-based experience hall management system of claim 2, wherein the first target facial image is stored at a frequency of not less than 15 sheets/second.
5. The human face recognition-based experience hall management system of claim 3, wherein the second target facial image is stored at a frequency of not less than 15 sheets/second.
6. The face recognition based experience hall management system of claim 2, wherein the image training module is specifically configured to,
adding 10 first target face images as sample images in the preset sample training library;
and performing recognition and comparison on the added 10 sample images through KL (karhunen-Loeve) conversion, if the recognition rate is 100%, recording the added 10 sample images into the preset sample training library, otherwise, adding 10 new first target face images as the sample images in the preset sample training library again, and performing subsequent recognition and comparison actions to circulate until the recognition rate reaches 100%.
7. The face recognition-based experience hall management system of claim 1, wherein the first camera is installed at an entrance to the experience hall.
8. The face recognition-based experience hall management system of claim 1, wherein the second camera is mounted above the experience device.
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