CN113747640B - Intelligent central control method and system for digital exhibition hall lamplight - Google Patents
Intelligent central control method and system for digital exhibition hall lamplight Download PDFInfo
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Abstract
The invention provides an intelligent central control method and system for digital exhibition hall lamplight, wherein the method comprises the following steps: acquiring an environment image of an exhibition hall site; analyzing the environment image to determine the age group distribution condition of tourists on the exhibition hall; based on the age group distribution condition, the lamplight in the exhibition hall is controlled. The intelligent central control method and system for the digital exhibition hall lamplight are used for meeting the common experience demands of exhibitors of different age groups on the exhibition hall lamplight and improving the experience comfort level of most people during the exhibitions.
Description
Technical Field
The invention relates to the field of automatic control of digital exhibition hall lights, in particular to an intelligent central control method and system of digital exhibition hall lights.
Background
The exhibition hall is an important exhibition mode of culture, commodity and the like, and the exhibition hall is set up by the museum to the enterprises to exhibit products or promote the brand image of the enterprises. Along with the continuous development of information technology, the exhibition hall also develops towards modernization and intellectualization, and more people are participating in the exhibition at the same time, the experience demand of people on the exhibition hall is increased, the age of people is not only limited to middle and young people, and some fixed groups can also have senile groups and juvenile groups to participate in the exhibition, so that knowledge is increased, and knowledge is improved.
The lighting system of the exhibition hall is an important component part of the exhibition hall, but the existing lighting system of the exhibition hall is single in layout and not flexible enough, the difference of the experience requirements of the participants and the participants in different age groups on the lights is not considered, the people in different age groups feel different in mind at different colors, for example, the old people are relatively sensitive to some warm lights due to the physical constitution of the old people; at present, the lamplight adjustment of the exhibition hall is mostly in a manual control mode, and the different preference and preference conditions of people of different ages for illumination brightness and chromaticity are not considered.
Disclosure of Invention
The invention provides an intelligent central control method and system for digital exhibition hall lamplight, which are used for meeting the common experience demands of exhibitors of different age groups on the exhibition hall lamplight and improving the experience comfort level of most people during exhibition.
The invention provides an intelligent central control method for digital exhibition hall lamplight, which comprises the following steps:
s1, acquiring an environment image of an exhibition hall site;
s2, analyzing the environment image to determine the age group distribution condition of tourists on the exhibition hall site;
and step S3, controlling the lamplight in the exhibition hall based on the age group distribution condition.
Preferably, the acquiring the environmental image of the exhibition hall site includes:
Shooting the exhibition hall through a plurality of cameras arranged at a plurality of preset positions on the exhibition hall to obtain a plurality of shooting images;
and splicing the plurality of shot images to obtain the environment image.
Preferably, the analyzing the environmental image, and determining the age group distribution condition of the tourists on the exhibition hall includes:
recognizing the face in the environment image to obtain the face position in the environment image;
image segmentation is carried out on a plurality of continuous environmental images according to the face positions in the environmental images, so that a plurality of face images are obtained and a spread face image set is generated;
and carrying out age identification on the showcase tourists according to the showman face image set, and determining the age group distribution condition of the tourists on the exhibition hall.
Preferably, the identifying the face in the environmental image to obtain the face position in the environmental image includes:
selecting an image with simple facial features in the environment image as an initial facial image, and extracting a first facial feature vector from the initial facial image;
obtaining a trained second face feature vector from a pre-stored face feature vector library;
and matching the first face feature vector with the second face feature vector, and determining the initial face image position as a face position when the matching degree is larger than a preset matching threshold value.
Preferably, the step of selecting the image with the face feature in the environment image as the initial face image by the box includes:
detecting image features of two eyes and lips in the environment image, determining positions of the image features of the two eyes and lips meeting the facial triangle position relation feature in the image, normalizing and affine transforming the environment image, enabling a triangle area to be located at a fixed position, scaling according to a preset proportion, and intercepting an initial facial image with a surrounding preset size;
and extracting a first face feature vector in the initial face image by adopting a principal component analysis or feature point extraction wavelet transformation coefficient method.
Preferably, the image segmentation of the continuous plurality of environmental images according to the face positions in the environmental images, and the obtaining the plurality of face images and generating the extended face image set include:
determining an area with a preset size around a face position in an environment image, performing image segmentation on the image of the area to obtain a face image, and labeling a unique tourist label for the face position;
dividing face images with the same tourist labels in a plurality of continuous environment images into the same group to obtain a tourist face image group;
And generating a showman face image set based on the group of the guest face images corresponding to each guest in the environment image.
Preferably, the step of identifying the ages of the tourists according to the face image set includes:
extracting a guest face image group of a guest in a showman face image set, and identifying the age bracket of the guest by utilizing the guest face image group, wherein the identification process is as follows:
preprocessing each face image in a tourist face image group of the tourist to obtain first-class face region pictures of a plurality of positions on a face;
classifying the first type face region pictures according to the positions to obtain a first type region picture group consisting of a plurality of face region pictures of the same part on the tourist face;
carrying out common feature extraction on each first type region picture group by using a feature extraction algorithm to obtain a plurality of first type features;
acquiring face images of different ages, dividing the face images into a plurality of face image sets according to a plurality of age groups to be identified, wherein each age group corresponds to one face image set;
preprocessing each face image in a face image set of a certain age group to obtain second-class face region pictures of a plurality of positions,
Classifying the second type face region pictures according to the positions to obtain a second type region picture group consisting of a plurality of face region pictures of the same part on the tourist face;
extracting common features of each second type region picture group by using a feature extraction algorithm to obtain a plurality of second type features of the face of the crowd in the age group;
matching the first type of features with the second type of features corresponding to a certain age group according to the corresponding positions to obtain matching degree;
taking an age group corresponding to the second type of characteristics with the largest matching degree as an age group of the tourist;
and performing age group identification on all the tourist face image groups in the exhibition face image set to obtain age group distribution conditions of tourists on the exhibition hall.
Preferably, the pretreatment includes:
positioning key points of the face images in the face image group or the face image data of the tourist by adopting a multi-key-point positioning method, wherein the key points comprise any one or a combination of a plurality of pupils, mouth angles, noses and ears;
according to the positional relationship of the plurality of key points in the face image, the face image is subjected to rotation, translation, scaling and stretching operations, so that the face image is aligned according to a preset standard;
And respectively taking the positions of a plurality of key points of the aligned face image as the center, and carrying out segmentation processing of a preset size to obtain a face region picture.
Preferably, the controlling the lamplight in the exhibition hall based on the age group distribution condition includes the following steps:
step S400, marking the number of tourists for each age group according to the age group distribution condition, and calculating the weight coefficient of the number of the tourists corresponding to each age group to the total number of the tourists;
step S401, sorting the age groups according to the number of tourists marked correspondingly from large to small to obtain an age group sorting sequence;
step S402, extracting a first age bracket in the age bracket ordering sequence, and placing the age bracket into a main age bracket group;
step S403, counting the sum of the number of tourists corresponding to each of a plurality of age groups in all main age groups, and calculating the percentage value of the sum to the total number of tourists;
step S404, repeating the steps S402 to S403 when the percentage value is smaller than a preset percentage threshold value;
step S405, when the percentage value is greater than or equal to a preset percentage threshold value, taking the existing age groups in the main age group as statistical age groups;
Step S406, determining a first type of light environment characteristic and a second type of light environment characteristic which correspond to each statistical age group;
step S407, obtaining third-class light environment characteristics required by the exhibited article;
step S408, according to the first type light environment characteristic, the second type light environment characteristic and the third type light environment characteristic, obtaining a fourth light environment characteristic by comprehensive weighted calculation of corresponding parameter values based on weight coefficients, where a calculation formula is as follows:
in which Q 4 ，S 4 Respectively represent the light intensity and chromaticity in the fourth light environment characteristic, Q 3 ，S 3 Respectively represent the light intensity and chromaticity in the third light environment characteristic, Q 2 ，S 2 Respectively represent the light intensity and chromaticity in the second light environment characteristic, Q 1 ，S 1 Respectively represent the light intensity and chromaticity, K in the first light environment characteristic N The weight coefficient corresponding to the N statistical age group is represented, and M represents the total number of the statistical age groups;
setting a lower limit value Q of light intensity min When Q min <Q 4 At the time, let Q 4 Take the value Q min Setting an upper limit value Q of light intensity max When Q 4 <Q max At the time, let Q 4 Take the value Q max ；
Setting the lower limit value S of chromaticity min When S min <S 4 Make S 4 Take the value S min Setting the upper limit value S of chromaticity max When S 4 <S max At the time, make S 4 Take the value S max ；
And S409, taking the fourth light environment characteristic as an optimal light environment characteristic, and controlling the light equipment on the exhibition hall according to the parameters of the light intensity and the chromaticity corresponding to the optimal light environment characteristic.
In order to achieve the above objective, the embodiment of the present invention further provides an intelligent central control system for digital exhibition hall lights, including:
the image acquisition module is used for acquiring an environment image of the exhibition hall site;
the image analysis module is used for analyzing the environment image and determining the age group distribution condition of tourists on the exhibition hall site;
and the lamplight control module is used for controlling lamplight in the exhibition hall based on the age group distribution condition.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a method for intelligent central control of digital exhibition hall lights in an embodiment of the invention;
FIG. 2 is a flowchart illustrating steps of a method for controlling a light environment according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an intelligent central control system for digital exhibition hall lights in an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The invention provides an intelligent central control method for digital exhibition hall lamplight, which comprises the following steps:
s1, acquiring an environment image of an exhibition hall site;
s2, analyzing the environment image to determine the age group distribution condition of tourists on the exhibition hall site;
and step S3, controlling the lamplight in the exhibition hall based on the age group distribution condition.
The working principle and beneficial effects of the technical scheme are as follows: the method comprises the steps of collecting and processing the image of the people stream in the exhibition hall at intervals, analyzing the distribution of the number and age groups of the exhibitors of the exhibition hall, counting the whole age groups of tourists, then combining the mapping corresponding relation between the age groups and the required light environment, adjusting the light system of the exhibition hall to achieve the optimal illumination intensity and chromaticity suitable for the number and the whole age groups of the tourists, for example, if only the people in the exhibition hall in the age groups ranging from 30 years old to 40 years old and from 10 years old to 20 years old are suitable for the light environment, one age group likes strong light and dislikes weak light, and one age group likes weak light and dislikes strong light, at the moment, comprehensively calculating the light environment preset by the two age groups according to the light environment preset by the weak light, finally obtaining the light environment characteristic with moderate light intensity, so that the two parties can not feel objection, comprehensively considering the common experience, thereby improving the light experience and the comfort of the exhibitors, and shooting in the exhibition hall at fixed time, being more flexibly controlled according to the change of the number of the exhibitors and the age groups.
In a preferred embodiment, acquiring an environmental image of the exhibition site includes:
shooting the exhibition hall through a plurality of cameras arranged at a plurality of preset positions on the exhibition hall to obtain a plurality of shooting images;
and splicing the plurality of shot images to obtain an environment image.
The technical principle and beneficial effects of the technical scheme are as follows: the cameras are respectively arranged at a plurality of positions on the exhibition hall to acquire multi-azimuth shooting images of the population on the exhibition hall, the continuous shooting images are used for acquiring, tracking and positioning of the tourists can be realized, linkage tracking shooting can be realized on the tourists from a plurality of angles, more comprehensive face images of the tourists are acquired, so that the recognition accuracy of age recognition is improved, tracking and labeling can be carried out on the position of the tourists after the age determination is carried out on the tourists, and when the tourists walk to one exhibition stand, the exhibition stand directly acquires the age recognition result of the tourists without calculating the age of the tourists again, so that the calculation amount is reduced. The environment image obtained by stitching the plurality of photographed images can be displayed in all directions in the exhibition hall.
In a preferred embodiment, analyzing the environmental image to determine an age group distribution of guests at the exhibition site includes:
Recognizing the face in the environment image to obtain the face position in the environment image;
image segmentation is carried out on a plurality of continuous environmental images according to the face positions in the environmental images, so that a plurality of face images are obtained and a spread face image set is generated;
and carrying out age identification on the showcase tourists according to the showman face image set, and determining the age group distribution condition of the tourists on the exhibition hall.
The working principle and beneficial effects of the technical scheme are as follows: firstly, recognizing human faces in a plurality of continuous environment images to obtain human face positions in the environment images, then cutting a region with a preset size around the human face positions to obtain human face images, and before cutting, scaling and changing the images of the human face positions to reach standard sizes to prevent the human faces from being different in size in the images due to different distance relations between tourists and cameras. After the face images are obtained, generating a showman face image set by utilizing a plurality of face images, and finally carrying out age identification on showmen according to the showman face image set to determine age bracket distribution conditions of the visitors on the exhibition hall. The plurality of face images of a plurality of tourists are obtained by cutting a plurality of environment images, the age of a certain tourist is identified by comprehensively identifying the plurality of face images of the tourist, accidental judgment errors can be prevented, and finally, after each tourist is identified by age, the age range of each tourist is obtained, and the age range distribution condition of the tourists on the exhibition hall is determined by statistics.
In a preferred embodiment, identifying the face in the environmental image, the obtaining the face position in the environmental image includes:
selecting an image with simple facial features in the environment image as an initial facial image by a frame, and extracting a first facial feature vector in the initial facial image;
obtaining a trained second face feature vector from a pre-stored face feature vector library;
and matching the first face feature vector with the second face feature vector, and determining the initial face image position as the face position when the matching degree is larger than a preset matching threshold value.
The working principle and beneficial effects of the technical scheme are as follows: the method comprises the steps of selecting an image with simple facial features in an environment image as an initial facial image, roughly judging the initial facial image, further accurately judging the initial facial image, extracting a first facial feature vector in the initial facial image, wherein the feature vector comprises relative position relation features among various local parts such as pupils, eye corners, noses, mouth corners, forehead hair, chin, ears and the like, obtaining a trained second facial feature vector from a pre-stored facial feature vector library, matching the first facial feature vector with the second facial feature vector, and determining the position of the initial facial image as a facial position when the matching degree is larger than a preset matching threshold. Therefore, the method and the device realize finer judgment on the initial face image, determine whether the initial face image position is the true face image position, track and capture objects at the initial face image position during the first quick judgment through the first quick judgment and the second accurate judgment, and then further judge whether the initial face image position truly exists the face through a slower and accurate feature vector matching algorithm, so that the face recognition on the patterns of the quick motion transformation in the environment image can be realized.
In a preferred embodiment, the step of selecting the image with the face feature in the environment image as the initial face image, and the step of extracting the first face feature vector includes:
detecting image features of two eyes and lips in an environment image, determining positions of the image features of the two eyes and lips meeting the facial triangle position relation features in the image, normalizing and affine transforming the environment image, scaling the triangle area according to a preset proportion after the triangle area is positioned at a fixed position, and intercepting an initial facial image with a surrounding preset size;
and extracting a first face feature vector in the initial face image by adopting a principal component analysis or feature point extraction wavelet transformation coefficient method.
The working principle and beneficial effects of the technical scheme are as follows: the method comprises the steps of detecting image characteristics of two eyes and lips in an environment image, taking the triangle position relationship characteristics formed by the two eyes and the lips as more obvious salient characteristics on a human face, carrying out quicker and coarser judgment on the position of the human face according to the characteristic, carrying out normalization and affine transformation on the environment image, enabling a triangle area to be located at a fixed position and then scaling the image according to a preset proportion, enabling the size of the triangle area to be consistent with the standard specification, conveniently cutting the image of the area, cutting out an initial human face image with the preset size around the triangle area, realizing cutting out of the human face image in the environment image, reducing the influence of characteristic points outside the initial human face image on a judging result, and finally extracting a first human face characteristic vector in the initial human face image by adopting a method of principal component analysis or characteristic point extraction wavelet transformation coefficient, so as to obtain the characteristic vector in the initial human face image, and facilitating more accurate calculation and analysis of the initial human face image.
In a preferred embodiment, image segmentation is performed on a plurality of continuous environmental images according to face positions in the environmental images, and obtaining a plurality of face images and generating a set of extended face images includes:
determining an area with a preset size around the face position in the environment image, performing image segmentation on the image of the area to obtain the face image, and labeling a unique tourist label for the face position;
dividing face images with the same tourist labels in a plurality of continuous environment images into the same group to obtain a tourist face image group;
and generating a showman face image set based on the group of the guest face images corresponding to each guest in the environment image.
The working principle and beneficial effects of the technical scheme are as follows: the face position in the environment image is subjected to image segmentation to obtain a face image, and unique tourist labels are marked on the face position, so that the position of the face of the same tourist is conveniently tracked and positioned according to the tourist labels, the face images with the same tourist labels in the continuous environment images are divided into the same group, a plurality of face images of the same tourist are obtained, the group of the tourist face images is formed, more accurate calculation is conveniently carried out on the specific age of the tourist through a large number of face images in the group of the tourist face images, and the condition that the calculation result and the actual age are inconsistent due to the influence of accidental conditions on the calculation result is reduced.
In a preferred embodiment, the step of identifying the ages of the tourists according to the face image set comprises the steps of:
extracting a guest face image group of a guest in the showman face image set, and identifying the age bracket of the guest by using the guest face image group, wherein the identification process is as follows:
preprocessing each face image in a tourist face image group of the tourist to obtain first-class face region pictures of a plurality of positions on a face;
classifying the first type face region pictures according to the positions to obtain a first type region picture group consisting of a plurality of face region pictures of the same part on the tourist face;
carrying out common feature extraction on each first type region picture group by using a feature extraction algorithm to obtain a plurality of first type features;
acquiring face images of different ages, dividing the face images into a plurality of face image sets according to a plurality of age groups to be identified, wherein each age group corresponds to one face image set;
preprocessing each face image in a face image set of a certain age group to obtain second-class face region pictures of a plurality of positions,
classifying the second type face region pictures according to the positions to obtain a second type region picture group consisting of a plurality of face region pictures of the same part on the tourist face;
Extracting common features of each second type region picture group by using a feature extraction algorithm to obtain a plurality of second type features of the face of the crowd in the age group;
matching the first type of features with the second type of features corresponding to a certain age group according to the corresponding positions to obtain matching degree;
taking an age group corresponding to the second type of characteristics with the largest matching degree as an age group of the tourist;
and performing age group identification on all the tourist face image groups in the exhibition face image set to obtain age group distribution conditions of tourists on the exhibition hall.
The working principle and beneficial effects of the technical scheme are as follows: and (3) carrying out age identification on a tourist, extracting a tourist face image group of the tourist during identification, preprocessing each face image in the tourist face image group of the tourist to obtain first face region pictures such as eye region pictures, nose region pictures and mouth region pictures at a plurality of positions on a face, and obtaining 2n eye region pictures, n nose region pictures and n mouth region pictures if n face images exist in the tourist face image group. Classifying the first type face region pictures according to the positions to obtain a first type region picture group consisting of a plurality of face region pictures of the same part on the face of the tourist, for example, an eye region picture group, a nose region picture group and a mouth region picture group. And extracting common features of each first type region picture group by using a feature extraction algorithm to obtain a plurality of first type features of the face of the tourist, such as eye features, nose features and mouth features of the tourist. Preprocessing each face image in a face image set of a certain age group to obtain second-class face region pictures of multiple positions, for example, preprocessing the pictures in the image set to obtain second-class face region pictures, classifying the second-class face region pictures according to positions to obtain second-class region picture groups formed by multiple face region pictures of the same part on the face image set of the 70-80-year-old group, and extracting common features of each second-class region picture group by using a feature extraction algorithm to obtain multiple second-class features of the face of the 70-year-old group to the 80-year-old group, such as eye features, nose features and mouth features of the face of the 70-year-old group to the 80-year-old group. Matching the first type of features with the second type of features corresponding to a certain age group according to the corresponding positions to obtain a matching degree, for example, matching the eye features in the first type of features with the eye features in the second type of features, correspondingly matching the mouth features in the first type of features with the mouth features in the second type of features, and finally obtaining the comprehensive matching degree of a plurality of first type of features and a plurality of second type of features, wherein the matching degree is used as the similarity degree between the age of the tourist and the age group, and the age group corresponding to the second type of features with the largest matching degree is used as the age group of the tourist. And finally, performing age group identification on all the tourist face image groups in the exhibition face image set to obtain age group distribution conditions of tourists on the exhibition hall.
In a preferred embodiment, the pre-treatment comprises:
positioning key points of face images in a tourist face image group or face image data by adopting a multi-key point positioning method, wherein the key points comprise any one or more of pupil, mouth angle, nose and ears;
according to the positional relationship of the plurality of key points in the face image, the face image is subjected to rotation, translation, scaling and stretching operations, so that the face image is aligned according to a preset standard;
and respectively taking the positions of a plurality of key points of the aligned face image as the center, and carrying out segmentation processing of the preset size on the area around the key points according to the types of the key points to obtain the face area picture.
The working principle and beneficial effects of the technical scheme are as follows: because the face images have the conditions of different sizes and uneven angles, a multi-key point positioning method is adopted to position key points of the face images in the face image group or the face image data of tourists, and the face images are rotated, translated, scaled and stretched according to the positional relationship of the plurality of positioned key points in the face images, so that the face images finish alignment work according to preset standards, the subsequent age identification work is convenient, and the accuracy of the face positioning and the age identification can be improved. The method comprises the steps of respectively taking the positions of a plurality of key points of the aligned face image as the center, carrying out segmentation processing of the preset size on the areas around the key points according to the types of the key points to obtain a face area image, for example, for eyes of the key points, mainly extracting images of the corners of eyes to judge the age through wrinkles of the corners of eyes and extracting images of eyeground bags to judge the age of tourists, and when the segmentation processing is carried out, the images of the two positions are required to be segmented and classified to finally obtain the face area image of a plurality of areas of the face, so that the age of the tourists can be comprehensively judged according to the conditions of different areas on the face.
In a preferred embodiment, controlling the lights in the exhibition hall based on the age group distribution comprises the steps of:
step 400, marking the number of tourists for each age group according to the age group distribution condition, and calculating the weight coefficient of the number of the tourists corresponding to each age group to the total number of the tourists;
step S401, sorting the age groups according to the number of tourists marked correspondingly from large to small to obtain an age group sorting sequence;
step S402, extracting a first age bracket in the age bracket ordering sequence, and placing the age bracket into a main age bracket group;
step S403, counting the sum of the number of tourists corresponding to each of a plurality of age groups in all main age groups, and calculating the percentage value of the sum to the total number of tourists;
step S404, repeating the steps S402 to S403 when the percentage value is smaller than a preset percentage threshold value;
step S405, when the percentage value is greater than or equal to a preset percentage threshold value, taking the existing age groups in the main age group as statistical age groups;
step S406, determining a first type of light environment characteristic and a second type of light environment characteristic which correspond to each statistical age group;
step S407, obtaining third-class light environment characteristics required by the exhibited article;
Step S408, according to the first type light environment characteristic, the second type light environment characteristic and the third type light environment characteristic, obtaining a fourth light environment characteristic by comprehensive weighted calculation of corresponding parameter values based on weight coefficients, where a calculation formula is as follows:
in which Q 4 ，S 4 Respectively represent the light intensity and chromaticity in the fourth light environment characteristic, Q 3 ，S 3 Respectively represent the light intensity and chromaticity in the third light environment characteristic, Q 2 ，S 2 Respectively represent the light intensity and chromaticity in the second light environment characteristic, Q 1 ，S 1 Respectively represent the light intensity and chromaticity, K in the first light environment characteristic N The weight coefficient corresponding to the N statistical age group is represented, and M represents the total number of the statistical age groups;
setting a lower limit value Q of light intensity min When Q min <Q 4 At the time, let Q 4 Take the value Q min Setting an upper limit value Q of light intensity max When Q 4 <Q max At the time, let Q 4 Take the value Q max ；
Setting the lower limit value S of chromaticity min When S min <S 4 Make S 4 Take the value S min Setting the upper limit value S of chromaticity max When S 4 <S max At the time, make S 4 Take the value S max ；
And S409, taking the fourth light environment characteristic as the optimal light environment characteristic, and controlling the light equipment on the exhibition hall according to the parameters of the light intensity and the chromaticity corresponding to the optimal light environment characteristic.
The working principle and beneficial effects of the technical scheme are as follows: marking the number of tourists for each age group according to the distribution condition of the age groups, calculating a weight coefficient of the number of the tourists corresponding to each age group to the total number of the tourists, grasping the importance degree of the light parameter corresponding to a certain age group in the calculation process through the weight coefficient, and sequencing the age groups from large to small according to the number of the tourists corresponding to the marking to obtain an age group sequencing sequence, so that the age groups with the maximum number of the tourists can be conveniently extracted; extracting a first age group in the age group ordering sequence, and placing the first age group in a main age group, so that the first position in a plurality of remaining age groups in the age group ordering sequence is circularly extracted; counting the sum value of the number of tourists corresponding to each of a plurality of age groups in all main age groups, and calculating the percentage value of the sum value to the total number of tourists; repeating the above cyclic extraction step when the percentage value is smaller than a preset percentage threshold, and breaking the cyclic extraction step when the percentage value is larger than or equal to the preset percentage threshold, wherein the existing age groups in the main age group are used as statistical age groups; determining a first type light environment characteristic and a second type light environment characteristic which correspond to each statistical age group, wherein the first type light environment parameter is mainly light environments which are more comfortable for most people in the main age group, and the second type light environment parameter is mainly light environments which are uncomfortable for most people in the main age group; acquiring third-class light environment characteristics required by the exhibited item, wherein the third-class light environment parameters are the optimal light supplementing environment required by the exhibited item; according to the first type of light environment characteristic, the second type of light environment characteristic and the third type of light environment characteristic, the fourth light environment characteristic is obtained through comprehensive weighted calculation of corresponding parameter values based on weight coefficients, the fourth light environment characteristic is used as the optimal light environment characteristic, and the light equipment on the exhibition hall site is controlled according to the parameters of light intensity and chromaticity corresponding to the optimal light environment characteristic, so that the light experience feeling and the exhibition comfort level of the exhibitors are improved.
In order to achieve the above purpose, the embodiment of the present invention further provides an intelligent central control system for digital exhibition hall lights, including:
the image acquisition module is used for acquiring an environment image of the exhibition hall site;
the image analysis module is used for analyzing the environment image and determining the age bracket distribution condition of tourists on the exhibition hall site;
and the lamplight control module is used for controlling lamplight in the exhibition hall based on the age group distribution condition.
The working principle and beneficial effects of the technical scheme are as follows: the method comprises the steps of acquiring images in an exhibition hall through an image acquisition module at intervals, processing the images through an image analysis module, analyzing and determining the number and age group distribution of the exhibitors of the exhibition hall, counting the whole age groups of visitors through a light control module, adjusting a lighting system of the exhibition hall to achieve optimal illumination intensity and chromaticity suitable for the whole age groups, for example, if only people with ages of 30 to 40 years and ages of 10 to 20 years in the exhibition hall have inconsistent suitability for light environments, one age group likes strong light and dislikes weak light, and one age group likes weak light and dislikes strong light, at the moment, comprehensively calculating the light environment parameters preset according to the two age groups, finally obtaining light environment parameters with moderate light intensity, enabling the two parties not to feel adverse effects, comprehensively considering the same feeling, improving the light experience feeling and the exhibition comfort of the exhibitors, and carrying out shooting in the exhibition hall at fixed time intervals, and being capable of flexibly controlling according to the change of the number and age groups of the exhibitors, and being more intelligent.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. An intelligent central control method for digital exhibition hall lamplight is characterized by comprising the following steps:
s1, acquiring an environment image of an exhibition hall site;
s2, analyzing the environment image to determine the age group distribution condition of tourists on the exhibition hall site;
step S3, controlling the lamplight in the exhibition hall based on the age group distribution condition;
based on the age group distribution condition, the lamplight in the exhibition hall is controlled by the following steps:
step S400, marking the number of tourists for each age group according to the age group distribution condition, and calculating the weight coefficient of the number of the tourists corresponding to each age group to the total number of the tourists;
step S401, sorting the age groups according to the number of tourists marked correspondingly from large to small to obtain an age group sorting sequence;
step S402, extracting a first age bracket in the age bracket ordering sequence, and placing the age bracket into a main age bracket group;
Step S403, counting the sum of the number of tourists corresponding to each of a plurality of age groups in all main age groups, and calculating the percentage value of the sum to the total number of tourists;
step S404, repeating the steps S402 to S403 when the percentage value is smaller than a preset percentage threshold value;
step S405, when the percentage value is greater than or equal to a preset percentage threshold value, taking the existing age groups in the main age group as statistical age groups;
step S406, determining a first type of light environment characteristic and a second type of light environment characteristic which correspond to each statistical age group;
step S407, obtaining third-class light environment characteristics required by the exhibited article;
step S408, according to the first type light environment characteristic, the second type light environment characteristic and the third type light environment characteristic, obtaining a fourth light environment characteristic by comprehensive weighted calculation of corresponding parameter values based on weight coefficients, where a calculation formula is as follows:
in the method, in the process of the invention,respectively representing the light intensity and chromaticity in the fourth light environment characteristic, +.>Respectively representing the light intensity and chromaticity in the third light environment characteristic, +.>Respectively representing the light intensity and chromaticity in the second light environment characteristic corresponding to the Nth statistical age group, +. >Respectively representing the light intensity and chromaticity in the first light environment characteristic corresponding to the Nth statistical age group, < ->The weight coefficient corresponding to the N statistical age group is represented, and M represents the total number of the statistical age groups;
setting the lower limit value of the light intensityWhen->When in use, make->The value is +.>Setting the upper limit value of the light intensity +.>When->When in use, make->The value is +.>；
Setting the lower limit value of chromaticityWhen->Make->The value is +.>Setting the upper limit value of chroma +.>When->When in use, make->The value is +.>；
Step S409, taking the fourth light environment characteristic as an optimal light environment characteristic, and controlling the light equipment on the exhibition hall according to the parameters of the light intensity and the chromaticity corresponding to the optimal light environment characteristic;
the first type of light environment parameters are light environments which are preset and feel comfortable corresponding to all the statistical age groups in the main age group, and the second type of light environment parameters are light environments which are preset and feel uncomfortable corresponding to all the statistical age groups in the main age group; the third type of light environment parameter is the optimal light supplementing environment required by the exhibited article.
2. The intelligent central control method for digital exhibition hall lights according to claim 1, wherein the acquiring the environmental image of the exhibition hall site comprises:
Shooting the exhibition hall through a plurality of cameras arranged at a plurality of preset positions on the exhibition hall to obtain a plurality of shooting images;
and splicing the plurality of shot images to obtain the environment image.
3. The intelligent central control method for digital exhibition hall lights according to claim 1, wherein the analyzing the environmental image to determine the age group distribution of tourists on the exhibition hall comprises:
recognizing the face in the environment image to obtain the face position in the environment image;
image segmentation is carried out on a plurality of continuous environmental images according to the face positions in the environmental images, so that a plurality of face images are obtained and a spread face image set is generated;
and carrying out age identification on the showcase tourists according to the showman face image set, and determining the age group distribution condition of the tourists on the exhibition hall.
4. The intelligent central control method for digital exhibition hall lights according to claim 3, wherein the step of identifying the face in the environmental image to obtain the face position in the environmental image comprises the steps of:
selecting an image with simple facial features in the environment image as an initial facial image, and extracting a first facial feature vector from the initial facial image;
Obtaining a trained second face feature vector from a pre-stored face feature vector library;
and matching the first face feature vector with the second face feature vector, and determining the initial face image position as a face position when the matching degree is larger than a preset matching threshold value.
5. The intelligent central control method for digital exhibition hall lights according to claim 4, wherein the step of selecting the image with the face feature in the environment image as the initial face image by the frame, and the step of extracting the first face feature vector comprises:
detecting image features of two eyes and lips in the environment image, determining positions of the image features of the two eyes and lips meeting the facial triangle position relation feature in the image, normalizing and affine transforming the environment image, enabling a triangle area to be located at a fixed position, scaling according to a preset proportion, and intercepting an initial facial image with a surrounding preset size;
and extracting a first face feature vector in the initial face image by adopting a principal component analysis or feature point extraction wavelet transformation coefficient method.
6. The intelligent central control method for digital exhibition hall lamplight according to claim 3, wherein the image segmentation of a plurality of continuous environmental images according to the face positions in the environmental images to obtain a plurality of face images and generate a set of exhibited face images comprises:
Determining an area with a preset size around a face position in an environment image, performing image segmentation on the image of the area to obtain a face image, and labeling a unique tourist label for the face position;
dividing face images with the same tourist labels in a plurality of continuous environment images into the same group to obtain a tourist face image group;
and generating a showman face image set based on the group of the guest face images corresponding to each guest in the environment image.
7. The intelligent central control method for digital exhibition hall lights according to claim 3, wherein the step of identifying the ages of the tourists according to the set of the face images comprises the steps of:
extracting a guest face image group of a guest in a showman face image set, and identifying the age bracket of the guest by utilizing the guest face image group, wherein the identification process is as follows:
preprocessing each face image in a tourist face image group of the tourist to obtain first-class face region pictures of a plurality of positions on a face;
classifying the first type face region pictures according to the positions to obtain a first type region picture group consisting of a plurality of face region pictures of the same part on the tourist face;
Carrying out common feature extraction on each first type region picture group by using a feature extraction algorithm to obtain a plurality of first type features;
acquiring face images of different ages, dividing the face images into a plurality of face image sets according to a plurality of age groups to be identified, wherein each age group corresponds to one face image set;
preprocessing each face image in a face image set of a certain age group to obtain second-class face region pictures of a plurality of positions,
classifying the second type face region pictures according to the positions to obtain a second type region picture group consisting of a plurality of face region pictures of the same part on the tourist face;
extracting common features of each second type region picture group by using a feature extraction algorithm to obtain a plurality of second type features of the face of the crowd in the age group;
matching the first type of features with the second type of features corresponding to a certain age group according to the corresponding positions to obtain matching degree;
taking an age group corresponding to the second type of characteristics with the largest matching degree as an age group of the tourist;
and performing age group identification on all the tourist face image groups in the exhibition face image set to obtain age group distribution conditions of tourists on the exhibition hall.
8. The intelligent central control method for the digital exhibition hall light according to claim 7, wherein the preprocessing comprises:
positioning key points of the face images in the face image group or the face image data of the tourist by adopting a multi-key-point positioning method, wherein the key points comprise any one or a combination of a plurality of pupils, mouth angles, noses and ears;
according to the positional relationship of the plurality of key points in the face image, the face image is subjected to rotation, translation, scaling and stretching operations, so that the face image is aligned according to a preset standard;
and respectively taking the positions of a plurality of key points of the aligned face image as the center, and carrying out segmentation processing of a preset size to obtain a face region picture.
9. An intelligent central control system for digital exhibition hall lamplight, which is characterized by comprising:
the image acquisition module is used for acquiring an environment image of the exhibition hall site;
the image analysis module is used for analyzing the environment image and determining the age group distribution condition of tourists on the exhibition hall site;
the lamplight control module is used for controlling lamplight in the exhibition hall based on the age group distribution condition;
The lamplight control module is used for controlling lamplight in the exhibition hall based on the age group distribution condition, and comprises the following steps of:
step S400, marking the number of tourists for each age group according to the age group distribution condition, and calculating the weight coefficient of the number of the tourists corresponding to each age group to the total number of the tourists;
step S401, sorting the age groups according to the number of tourists marked correspondingly from large to small to obtain an age group sorting sequence;
step S402, extracting a first age bracket in the age bracket ordering sequence, and placing the age bracket into a main age bracket group;
step S403, counting the sum of the number of tourists corresponding to each of a plurality of age groups in all main age groups, and calculating the percentage value of the sum to the total number of tourists;
step S404, repeating the steps S402 to S403 when the percentage value is smaller than a preset percentage threshold value;
step S405, when the percentage value is greater than or equal to a preset percentage threshold value, taking the existing age groups in the main age group as statistical age groups;
step S406, determining a first type of light environment characteristic and a second type of light environment characteristic which correspond to each statistical age group;
Step S407, obtaining third-class light environment characteristics required by the exhibited article;
step S408, according to the first type light environment characteristic, the second type light environment characteristic and the third type light environment characteristic, obtaining a fourth light environment characteristic by comprehensive weighted calculation of corresponding parameter values based on weight coefficients, where a calculation formula is as follows:
in the method, in the process of the invention,respectively representing the light intensity and chromaticity in the fourth light environment characteristic, +.>Respectively representing the light intensity and chromaticity in the third light environment characteristic, +.>Respectively representing the light intensity and chromaticity in the second light environment characteristic corresponding to the Nth statistical age group, +.>Respectively represent pairs ofLight intensity and chromaticity in the first light environment characteristic of the nth statistical age group, +.>The weight coefficient corresponding to the N statistical age group is represented, and M represents the total number of the statistical age groups;
setting the lower limit value of the light intensityWhen->When in use, make->The value is +.>Setting the upper limit value of the light intensity +.>When->When in use, make->The value is +.>；
Setting the lower limit value of chromaticityWhen->Make->The value is +.>Setting the upper limit value of chroma +.>When->When in use, make->The value is +.>；
Step S409, taking the fourth light environment characteristic as an optimal light environment characteristic, and controlling the light equipment on the exhibition hall according to the parameters of the light intensity and the chromaticity corresponding to the optimal light environment characteristic;
The first type of light environment parameters are light environments which are preset and feel comfortable corresponding to all the statistical age groups in the main age group, and the second type of light environment parameters are light environments which are preset and feel uncomfortable corresponding to all the statistical age groups in the main age group; the third type of light environment parameter is the optimal light supplementing environment required by the exhibited article.
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