Advertisement data transmission method and system based on cloud platform

Abstract

The invention relates to the field of data transmission, in particular to an advertisement data transmission method and system based on a cloud platform. The method comprises the following steps: acquiring a merchant advertisement video; segmenting each frame of image of the merchant advertisement video to obtain foreground pixels and background pixels; recording a sequence formed by all background pixels at any position in all frames of images as a background pixel sequence; segmenting the background pixel sequence into a plurality of background segments which are distributed differently; a Gaussian distribution model of the background segment is constructed, the number of intervals is calculated, the Gaussian distribution model is divided into intervals of the interval number, the mean value of the intervals to which background pixels belong is used as an update value of the background pixels, and the update value of the background pixels in the background segment is coded by using a run length coding algorithm; encoding the foreground pixels; therefore, commercial tenant advertisement video transmission is realized. By reducing the value difference of the pixels, the compression effect of run length coding is improved.

Description

Technical Field

[0001] The present invention relates to the field of data transmission, and in particular to a cloud platform-based advertising data transmission method and system. Background Art

[0002] In order to improve the accuracy of advertising, optimize advertising efficiency and reduce advertising costs, companies often transfer advertisements to cloud platforms for management. Since there are many videos, images, audio and other data in advertising data, the transmission volume of advertising data is large, which will lead to low transmission efficiency of advertising data. In order to improve transmission efficiency, advertising data needs to be compressed. As a compression coding algorithm, the run-length coding algorithm encodes and compresses data by recording the starting position and continuous length of continuous identical data. Therefore, the run-length coding algorithm has a strong compression ability for data with the same continuous values. Since the values ​​of any pixel in the video are relatively similar in the frame sequence, the run-length coding algorithm can be used to compress the video. Although the values ​​of the pixels in the video are relatively similar in the frame sequence, they are not exactly the same. The diversity of their values ​​will lead to poor compression effect of run-length coding. How to improve the compression effect by reducing the diversity of pixel values ​​in the video becomes the research focus of this invention.

[0003] The patent application document with publication number CN103916448A discloses a data transmission method, system and corresponding cloud transmission platform based on a cloud transmission platform. The method in the patent application document improves data transmission efficiency by slicing data according to the location information of the transmission node. The method in the patent application document does not involve the content of run-length coding compression, and therefore the method in the patent application document cannot solve the technical problem of the present solution. Summary of the invention

[0004] In order to solve the problem of how to improve the compression effect by reducing the diversity of pixel values ​​in a video, the present invention provides an advertisement data transmission method and system based on a cloud platform.

[0005] In a first aspect, the present invention provides an advertisement data transmission method based on a cloud platform, which adopts the following technical solution: A cloud platform-based advertising data transmission method, comprising the steps of: Get the merchant's advertising video; Segment each frame of the merchant advertisement video to obtain foreground pixels and background pixels; The sequence of all background pixels at any position in all frame images is recorded as the background pixel sequence; the background pixel sequence is divided into several background segments with different distributions; a Gaussian distribution model of the background segment is constructed, and the number of intervals is calculated: , Indicates the information recurrence rate within the preset area of ​​the background pixel at that position, Indicates the information content of the background pixel at that location within the preset area. represents the peak value of the Gaussian distribution model, represents the mean of the differences between all two adjacent pixels in the background segment, Indicates the number of data values ​​in the background segment, norm() indicates the linear normalization method, S1 indicates the number of intervals, Indicates the rounding up symbol, divides the Gaussian distribution model into S1 intervals, takes the mean value of the interval to which the background pixel belongs as the update value of the background pixel, and uses the run-length encoding algorithm to encode the update value of the background pixel in the background segment; encodes the foreground pixel; To achieve merchant advertising video transmission.

[0006] The present invention analyzes the values ​​of background pixels and foreground pixels in the frame sequence separately, effectively reducing the difference in pixel values ​​in the frame sequence, and providing a basis for subsequently improving the compression effect of run-length coding; further, the values ​​of pixels in the frame sequence are segmented according to distribution characteristics, so that the pixel values ​​of each segment reflect the same object, further reducing the difference in values, and improving the compression effect of run-length coding; further, the segmented results of the pixel values ​​in the frame sequence are further divided into intervals for processing, and the mean of the intervals replaces each real value, effectively eliminating the differentiation of values, and further improving the effect of run-length coding; further, when dividing the segmented results into intervals, information such as information importance and value difference is considered, thereby improving the accuracy of the division of the divided intervals, and providing a basis for subsequently improving the compression effect of run-length coding.

[0007] Preferably, the segmentation process of each frame of the merchant advertisement video to obtain foreground pixels and background pixels includes: The merchant advertisement video is processed using background subtraction method to obtain the foreground area and background area of ​​each frame image; Obtain the bounding rectangle of the largest foreground area in all frame foreground areas as the reference rectangle; The geometric center of the foreground area in each frame image is taken as the center of the reference rectangle, the pixels within the reference rectangle are obtained and recorded as foreground pixels, and the pixels other than the foreground pixels in each frame image are taken as background pixels.

[0008] The present invention efficiently and accurately segments the motion area and the background area through a background subtraction method, providing a data basis for improving the compression effect of run-length coding.

[0009] Preferably, dividing the background pixel sequence into a plurality of background segments with different distributions includes: Taking any background pixel in the background pixel sequence as the center, a preset number of pixels are obtained as the reference pixels of the background pixel, and a Gaussian distribution model is fitted using the reference pixels of the background pixel. The difference in the Gaussian distribution model between every two adjacent background pixels is used as the clustering difference. All background pixels are clustered to obtain several categories, and the pixel segments composed of background pixels in each category are used as background segments.

[0010] According to the feature that the distribution of pixel values ​​of the same object is similar, the present invention separates the value data corresponding to different objects, thereby providing a basis for subsequent de-differentiation. Preferably, the method for obtaining the difference of the Gaussian distribution model includes: The difference between the two Gaussian distribution models is obtained by multiplying the absolute value of the difference between the means of the two Gaussian distribution models by the absolute value of the difference between the variances of the two Gaussian distribution models.

[0011] The present invention reflects the model differences through variance and mean differences. This calculation method is relatively simple and has higher implementation efficiency.

[0012] Preferably, the method for obtaining the information recurrence rate includes: Taking the background pixel at that position in each frame image as the center, obtain a preset area, record it as the local area of ​​the background pixel at that position, calculate the similarity between the background pixel at that position and the local areas of pixels at other positions, and take the average of the similarities between the background pixel at that position and the local areas of all other positions as the information recurrence rate of the background pixel at that position.

[0013] The present invention reflects the repetition of information through similarity and measures the importance of information more accurately.

[0014] Preferably, the method for obtaining the information content includes: The information entropy in the local area of ​​the background pixel at that position is taken as the information content.

[0015] Preferably, the step of dividing the Gaussian distribution model into S1 intervals includes: The Gaussian distribution model is evenly divided into S1 regions of equal area, and the pixel value interval corresponding to each region is obtained.

[0016] Preferably, encoding the foreground pixels comprises: The area formed by the foreground pixels in each frame of the image is recorded as the analysis foreground area; Aligning the analyzed foreground areas of all frames, and recording a sequence consisting of all foreground pixels at any position in the analyzed foreground areas of all frames as a foreground pixel sequence; Divide the foreground pixel sequence into several foreground segments with different distributions; Encode the foreground segment.

[0017] Preferably, the method of realizing the transmission of merchant advertisement video includes: The coding sequences of all background segments of the background pixel sequence are spliced ​​together to obtain the coding sequence of the background pixel sequence, the coding sequences of all foreground segments of the foreground pixel sequence are spliced ​​together to obtain the coding sequence of the foreground pixel sequence, the geometric center coordinates of the analyzed foreground area are obtained, the geometric center coordinates of all analyzed foreground areas are spliced ​​together to obtain a trajectory sequence, the starting frame number of the analyzed foreground area is obtained, the starting frame number, the length and width of the reference rectangle are inserted before the trajectory sequence, the trajectory sequence with the inserted starting frame number is spliced ​​together with the coding sequences of all foreground pixel sequences, and then a preset demarcation mark value is inserted, and then it is spliced ​​together with the coding sequences of all background pixel sequences to obtain a transmission sequence, and the transmission sequence is transmitted.

[0018] In a second aspect, the present invention provides an advertising data transmission system based on a cloud platform, which adopts the following technical solution: A cloud platform-based advertising data transmission system comprises: a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned cloud platform-based advertising data transmission method is implemented.

[0019] By adopting the above technical solution, the above-mentioned cloud platform-based advertising data transmission method is generated into a computer program and stored in a memory to be loaded and executed by a processor, so that a terminal device is manufactured according to the memory and the processor for easy use.

[0020] The present invention has the following technical effects: The present invention analyzes the values ​​of background pixels and foreground pixels in the frame sequence separately, effectively reducing the difference in pixel values ​​in the frame sequence, and providing a basis for improving the compression effect of run-length coding in the future; Furthermore, the pixel values ​​in the frame sequence are segmented according to the distribution characteristics, so that the pixel values ​​in each segment reflect the same object, further reducing the value difference and improving the compression effect of run-length coding; Furthermore, the segmented results of the pixel values ​​in the frame sequence are further divided into intervals for processing, and the mean of the intervals replaces the real values, effectively eliminating the differences in the values ​​and further improving the effect of run-length coding; Furthermore, when dividing the segmentation results into intervals, information such as information importance and value differences are taken into consideration, thereby improving the accuracy of the division of the intervals and providing a basis for subsequently improving the compression effect of run-length coding. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts.

[0022] Figure 1 It is a flow chart of a method in a cloud platform-based advertising data transmission method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0024] It should be understood that when the terms "first", "second", etc. are used in the claims, descriptions, and drawings of the present invention, they are only used to distinguish different objects, rather than to describe a specific order. The terms "include" and "comprise" used in the description and claims of the present invention indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their collections.

[0025] The embodiment of the present invention discloses a method for transmitting advertising data based on a cloud platform. Figure 1 , comprising steps S1 to S5: S1: Get the merchant's advertising video.

[0026] Specifically, obtain the merchant advertising video.

[0027] S2: Segment each frame of the merchant advertisement video to obtain foreground pixels and background pixels.

[0028] It should be noted that there are several moving objects in the merchant advertising video. The same moving object only changes its position in each frame, and its color value does not change much. Therefore, the pixel values ​​of the same moving object in consecutive frames are similar. The color of non-moving objects does not change much in consecutive frames. Therefore, in order to improve the compression effect, moving objects and non-moving objects need to be considered separately. First, the moving objects and non-moving objects in each frame of the merchant advertising video are separated. In this implementation, the foreground pixels reflect the moving objects, and the background pixels reflect the non-moving objects.

[0029] Preferably, as an example, segmenting each frame of the merchant advertisement video to obtain foreground pixels and background pixels includes: The merchant advertisement video is processed using background subtraction method to obtain the foreground area and background area of ​​each frame image; Obtain the bounding rectangle of the largest foreground area in all frame foreground areas as the reference rectangle; The geometric center of the foreground area in each frame image is taken as the center of the reference rectangle, the pixels within the reference rectangle are obtained and recorded as foreground pixels, and the pixels other than the foreground pixels in each frame image are taken as background pixels.

[0030] S3: Record the sequence of all background pixels at any position in all frame images as a background pixel sequence, divide the background pixel sequence into several background segments with different distributions, and construct a Gaussian distribution model of the background segment; calculate the number of intervals, divide the Gaussian distribution model into the number of intervals, use the mean of the interval to which the background pixel belongs as the update value of the background pixel, and use the run-length encoding algorithm to encode the update value of the background pixel in the background segment; encode the foreground pixel.

[0031] It should be noted that in order to reduce the diversity of values ​​of background pixels at a position in the frame sequence, different values ​​with smaller differences need to be differentiated, thereby increasing the continuation length of continuous identical data and further improving the compression effect.

[0032] S30: Record the sequence of all background pixels at any position in all frame images as a background pixel sequence, divide the background pixel sequence into several background segments with different distributions, and construct a Gaussian distribution model of the background segment; calculate the number of intervals, divide the Gaussian distribution model into S1 intervals, take the mean value of the interval to which the background pixel belongs as the update value of the background pixel, and use the run-length encoding algorithm to encode the update value of the background pixel in the background segment.

[0033] S300: Record a sequence consisting of all background pixels at any position in all frame images as a background pixel sequence.

[0034] S301: Segment the background pixel sequence into a plurality of background segments with different distributions, and construct a Gaussian distribution model of the background segments.

[0035] It should be noted that due to the phenomenon of video splicing in merchant advertising videos, the background pixels at one location may reflect different objects in different frames. Normally, the pixel values ​​of the same object generally have similar distribution characteristics, while the pixel values ​​of different objects have different distribution characteristics. Therefore, the pixel segments corresponding to different objects can be separated by distribution characteristics.

[0036] Preferably, as an example, the background pixel sequence is segmented into a plurality of background segments with different distributions, and a Gaussian distribution model of the background segments is constructed, including: Taking any background pixel in the background pixel sequence as the center, a preset number of pixels are obtained as the reference pixels of the background pixel, and a Gaussian distribution model is fitted using the reference pixels of the background pixel. The difference in the Gaussian distribution model between every two adjacent background pixels is used as the clustering difference. All background pixels are clustered to obtain several categories, and the pixel segments composed of background pixels in each category are used as background segments.

[0037] Fit the Gaussian distribution model of all pixels in each background segment. This embodiment takes the preset number of 11 as an example for explanation, and other embodiments may take other values, which are not limited in this embodiment.

[0038] It should be added that the difference between the two Gaussian distribution models can be obtained by multiplying the absolute value of the difference between the means of the two Gaussian distribution models by the absolute value of the difference between the variances of the two Gaussian distribution models.

[0039] S302: Calculate the number of intervals.

[0040] It should be noted that in order to reduce the diversity of pixel values ​​in the frame sequence, similar values ​​need to be dedifferentiated. Since the dedifferentiating process will inevitably damage the information in the video, in order to reduce the damage to important information in the video, the dedifferentiating process needs to be controlled.

[0041] Preferably, as an example, calculating the number of intervals includes:

[0042] in, Indicates the information recurrence rate within the preset area of ​​the background pixel at that position, Indicates the information content of the background pixel at that location within the preset area. represents the peak value of the Gaussian distribution model, represents the standard deviation of all background pixels in the background segment, Indicates the number of data values ​​in the background segment, norm() indicates the linear normalization method, S1 indicates the number of intervals, Indicates the round-up symbol.

[0043] Understandably, The larger it is, the information in the preset area of ​​the background pixel at that position not only has a large information content, but also appears repeatedly. This means that the information in the preset area of ​​the background pixel at that position is more likely to be the advertising theme information. Therefore, the information loss has a greater impact on the advertisement. Therefore, more intervals should be divided to make the values ​​in the intervals more similar, thereby reducing the information loss during de-differentiation. It reflects the concentration of pixel values ​​in the background segment. The larger the value, the smaller the difference in values ​​in the background segment. The number of interval divisions can be appropriately reduced to enhance the strength of dedifferentiation and provide data compression effect. It reflects the degree of difference of the data in the background segment. The greater the difference, the number of interval divisions should be appropriately reduced to enhance the intensity of de-differentiation and improve the compression effect.

[0044] It should be added that the method for obtaining the information recurrence rate includes: Taking the background pixel at the position in each frame image as the center, a preset area is obtained and recorded as the local area of ​​the background pixel at the position, and the similarity between the background pixel at the position and the local areas of each pixel at other positions is calculated, and the average of the similarities between the background pixel at the position and the local areas of all other positions is taken as the information recurrence rate of the background pixel at the position. This is described as an example, and other embodiments may take other values, and this embodiment does not make any specific limitation.

[0045] Methods for obtaining information content include: The information entropy in the local area of ​​the background pixel at that position is taken as the information content.

[0046] S303: Divide the Gaussian distribution model into S1 intervals, take the mean value of the interval to which the background pixel belongs as the update value of the background pixel, and use the run-length coding algorithm to encode the update value of the background pixel in the background segment.

[0047] Preferably, as an example, the mean value of the interval to which the background pixel belongs is used as the update value of the background pixel, and the update value of the background pixel in the background segment is encoded using a run-length encoding algorithm, including: The Gaussian distribution model is evenly divided into S1 regions of equal area, and the pixel value interval corresponding to each region is obtained.

[0048] The mean value of all background pixels in the interval to which the background pixel belongs is taken as the update value of the background pixel, and the update value of the background pixel in the background segment is encoded using the run-length variation algorithm to obtain the encoding sequence of the background segment.

[0049] It can be understood that dividing the intervals according to the area can take into account the influence of the number of pixels, so that the degree of de-differentiation of the values ​​with a large number of pixels is relatively small, effectively reducing information loss; using the mean to replace the value of each background pixel can effectively solve the problem of differentiation of background pixel values, thereby effectively extending the length of the same continuous value and improving the compression effect.

[0050] S31: Encode foreground pixels.

[0051] Preferably, as an example, encoding the foreground pixel includes: The area formed by the foreground pixels in each frame of the image is recorded as the analysis foreground area; the analysis foreground area with the closest distance in the adjacent frames is recorded as the corresponding analysis foreground area; Aligning the corresponding analysis foreground areas of all frames, and recording the sequence consisting of all foreground pixels at any position in the corresponding analysis foreground areas of all frames as a foreground pixel sequence; Divide the foreground pixel sequence into a number of foreground segments according to the method of dividing the background segments; The foreground segment is encoded according to the encoding method for the background segment to obtain the encoding sequence of each foreground segment.

[0052] It is understandable that the corresponding foreground area represents the area where the same moving object is located in different frames. Since the values ​​of the same moving object in the frame sequence are highly similar, the dedifferentiation process will not cause much loss of video information. However, the dedifferentiation process can greatly extend the continuation length of the same continuous value. Therefore, the dedifferentiation process can greatly improve the compression effect.

[0053] S4: To realize the transmission of merchant advertising videos.

[0054] Preferably, as an example, to realize the transmission of merchant advertisement video, the method includes: The coding sequences of all background segments of the background pixel sequence are spliced ​​together to obtain the coding sequence of the background pixel sequence, the coding sequences of all foreground segments of the foreground pixel sequence are spliced ​​together to obtain the coding sequence of the foreground pixel sequence, the geometric center coordinates of the analyzed foreground area are obtained, the geometric center coordinates of all analyzed foreground areas are spliced ​​together to obtain the trajectory sequence, the starting frame number of the analyzed foreground area is obtained, the starting frame number, the length and width of the reference rectangle are inserted before the trajectory sequence, the trajectory sequence with the inserted starting frame number is spliced ​​together with the coding sequences of all foreground pixel sequences, and then a preset demarcation mark value is inserted, and then the transmission sequence is spliced ​​together with the coding sequences of all background pixel sequences to obtain the transmission sequence, and the transmission sequence is transmitted. In this embodiment, the ASCALL code of the semicolon is used as the decomposition mark value, and other embodiments can take other values, which are not specifically limited in this embodiment.

[0055] S5: Decode the transmission sequence.

[0056] Preferably, as an example, decoding the transmission sequence includes: Using the demarcation mark value, the coding sequence of the background pixel sequence is separated from other sequences; The trajectory sequence, the starting frame number, the coding sequence of all foreground pixel sequences and the length and width of the reference rectangle in other sequences are separated; the coding sequence of all foreground pixel sequences is separated according to the number of continued frames, and the coding sequence of each foreground pixel sequence is decoded by a run-length coding algorithm to obtain each foreground pixel sequence, and the frame of each foreground pixel in the foreground pixel sequence and the coordinates in the frame are located by using the starting frame number, the coordinates of each geometric center in the trajectory sequence and the length and width of the reference rectangle.

[0057] For ease of explanation, an example is given below to explain how to locate the frame of each foreground pixel in the foreground pixel sequence and the coordinates in the frame using the starting frame number, the geometric center coordinates in the trajectory sequence, and the length and width of the reference rectangle: Taking the positioning method of the second foreground pixel in the second foreground pixel sequence as an example, assuming that the starting frame number is 2, the second foreground pixel in the second foreground pixel sequence is the pixel in the third frame image, and the geometric center coordinates of the foreground area corresponding to the second foreground pixel sequence are the second elements in the trajectory sequence. Assuming that the second element in the trajectory sequence is , the length and width of the reference rectangle are 11 and 11 respectively, then the coordinate position of the second foreground pixel is , so far the frame where the second foreground pixel in the second foreground pixel sequence is located and the coordinates in the frame where the second foreground pixel is located are located.

[0058] The run-length coding algorithm is used to decode the coding sequence of each background pixel sequence to obtain a background pixel sequence, and the frame where each background pixel in the background pixel sequence is located and the coordinates in the frame are located.

[0059] An embodiment of the present invention further discloses an advertising data transmission system based on a cloud platform, including a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, an advertising data transmission method based on a cloud platform according to the present invention is implemented.

[0060] The above system also includes other components well known to those skilled in the art, such as a communication bus and a communication interface, and their configuration and functions are known in the art, so they will not be described in detail here.

[0061] In the present invention, the aforementioned memory may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium may be any suitable magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory, a dynamic random access memory, a static random access memory, an enhanced dynamic random access memory, a high bandwidth memory, a hybrid storage cube, etc., or any other medium that can be used to store the required information and can be accessed by an application, a module, or both. Any such computer storage medium may be part of the device or accessible or connectable to the device.

[0062] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

[0063] The above are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A cloud platform-based advertising data transmission method, characterized in that: Includes steps: Get the merchant's advertising video; Segment each frame of the merchant advertisement video to obtain foreground pixels and background pixels; The sequence of all background pixels at any position in all frame images is recorded as the background pixel sequence; the background pixel sequence is divided into several background segments with different distributions; a Gaussian distribution model of the background segment is constructed, and the number of intervals is calculated: , Indicates the information recurrence rate within the preset area of ​​the background pixel at that position, Indicates the information content of the background pixel at that location within the preset area. represents the peak value of the Gaussian distribution model, represents the mean of the differences between all two adjacent pixels in the background segment, Indicates the number of data values ​​in the background segment, norm() indicates the linear normalization method, S1 indicates the number of intervals, Indicates the rounding up symbol, divides the Gaussian distribution model into S1 intervals, takes the mean value of the interval to which the background pixel belongs as the update value of the background pixel, and uses the run-length encoding algorithm to encode the update value of the background pixel in the background segment; Encode foreground pixels; To achieve merchant advertising video transmission.

2. The method for transmitting advertising data based on a cloud platform according to claim 1, characterized in that: The segmentation process of each frame of the merchant advertisement video to obtain foreground pixels and background pixels includes: The merchant advertisement video is processed using background subtraction method to obtain the foreground area and background area of ​​each frame image; Obtain the bounding rectangle of the largest foreground area in all frame foreground areas as the reference rectangle; The geometric center of the foreground area in each frame image is taken as the center of the reference rectangle, the pixels within the reference rectangle are obtained and recorded as foreground pixels, and the pixels other than the foreground pixels in each frame image are taken as background pixels.

3. The method for transmitting advertising data based on a cloud platform according to claim 1, characterized in that: The step of dividing the background pixel sequence into a plurality of background segments with different distributions includes: Taking any background pixel in the background pixel sequence as the center, a preset number of pixels are obtained as the reference pixels of the background pixel, and a Gaussian distribution model is fitted using the reference pixels of the background pixel. The difference in the Gaussian distribution model between every two adjacent background pixels is used as the clustering difference. All background pixels are clustered to obtain several categories, and the pixel segments composed of background pixels in each category are used as background segments.

4. The method for transmitting advertising data based on a cloud platform according to claim 3, characterized in that: The method for obtaining the difference of the Gaussian distribution model includes: The difference between the two Gaussian distribution models is obtained by multiplying the absolute value of the difference between the means of the two Gaussian distribution models by the absolute value of the difference between the variances of the two Gaussian distribution models.

5. The method for transmitting advertising data based on a cloud platform according to claim 1, characterized in that: The method for obtaining the information recurrence rate comprises: Taking the background pixel at that position in each frame image as the center, obtain a preset area, record it as the local area of ​​the background pixel at that position, calculate the similarity between the background pixel at that position and the local areas of pixels at other positions, and take the average of the similarities between the background pixel at that position and the local areas of all other positions as the information recurrence rate of the background pixel at that position.

6. The method for transmitting advertising data based on a cloud platform according to claim 5, characterized in that: The method for obtaining the information content comprises: The information entropy in the local area of ​​the background pixel at that position is taken as the information content.

7. The method for transmitting advertising data based on a cloud platform according to claim 1, characterized in that: The Gaussian distribution model is divided into S1 intervals, including: The Gaussian distribution model is evenly divided into S1 regions of equal area, and the pixel value interval corresponding to each region is obtained.

8. The method for transmitting advertising data based on a cloud platform according to claim 1, characterized in that: The encoding of the foreground pixels comprises: The area formed by the foreground pixels in each frame of the image is recorded as the analysis foreground area; Aligning the analyzed foreground areas of all frames, and recording a sequence consisting of all foreground pixels at any position in the analyzed foreground areas of all frames as a foreground pixel sequence; Divide the foreground pixel sequence into several foreground segments with different distributions; Encode the foreground segment.

9. The method for transmitting advertising data based on a cloud platform according to claim 8, characterized in that: The method of realizing the transmission of merchant advertisement video includes: The coding sequences of all background segments of the background pixel sequence are spliced ​​together to obtain the coding sequence of the background pixel sequence, the coding sequences of all foreground segments of the foreground pixel sequence are spliced ​​together to obtain the coding sequence of the foreground pixel sequence, the geometric center coordinates of the analyzed foreground area are obtained, the geometric center coordinates of all analyzed foreground areas are spliced ​​together to obtain a trajectory sequence, the starting frame number of the analyzed foreground area is obtained, the starting frame number, the length and width of the reference rectangle are inserted before the trajectory sequence, the trajectory sequence with the inserted starting frame number is spliced ​​together with the coding sequences of all foreground pixel sequences, and then a preset demarcation mark value is inserted, and then it is spliced ​​together with the coding sequences of all background pixel sequences to obtain a transmission sequence, and the transmission sequence is transmitted.

10. An advertising data transmission system based on a cloud platform, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a cloud platform-based advertising data transmission method according to any one of claims 1 to 9 is implemented.

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