Preset bit deployment method, device, storage medium and system

Abstract

The invention provides a preset position deployment method and device, a storage medium and a system, the preset position deployment method and device are applied to a collection device management device in the preset position deployment system, the collection device management device is connected with a panoramic image collection device and a local image collection device, and the panoramic image collection device is used for collecting a panoramic image of a space; the method comprises the steps that a first local image set is acquired, the first local image set comprises a plurality of local images, and the plurality of local images in the first local image set are local images acquired by a local image acquisition device at a plurality of attitude positions in a first attitude position set; splicing all local images in the first local image set to obtain a first spliced image; and comparing the first spliced image with the panoramic image, and deploying a preset position for the local image acquisition device according to a comparison result of the first spliced image and the panoramic image, the preset position being a posture position required by the local image acquisition device for fixed-point image acquisition. According to the technical scheme, automatic deployment of the preset position is realized.

Description

Technical Field

[0001] The present application relates to the field of intelligent deployment, and in particular to a pre-positioned deployment method, device, storage medium, and system. Background Art

[0002] Contactless attendance in education uses contactless technology to automatically record student attendance. It aims to improve attendance efficiency, reduce manual effort, and ensure the accuracy and security of attendance data. Contactless attendance is typically implemented using technologies such as radio frequency identification (RFID) and biometrics.

[0003] Facial recognition is a common biometric technology used to achieve seamless attendance. This technology uses a camera installed near the podium to capture the student area, capturing their facial features. These features are then compared with facial data in a database to obtain attendance results. To ensure that the faces captured by the camera meet facial recognition requirements, a combination of panoramic and close-up lenses is typically used. The panoramic camera is a wide-angle lens used to capture images of the entire classroom, providing the faces of students in the front row for facial recognition. The close-up lens is a telephoto lens used for panning, capturing the faces of students in the back row for facial recognition. Panning means that the close-up camera is in different preset positions at different times to capture different areas. Therefore, different preset positions need to be set for the close-up camera in advance. Summary of the Invention

[0004] The present application provides a preset position deployment method, device, storage medium and system, aiming to deploy preset positions for close-up shots.

[0005] In a first aspect, a pre-positioned position deployment method is provided, which is applied to a collection device management device in a pre-positioned position deployment system, wherein the pre-positioned position deployment system includes the collection device management device, a panoramic image collection device, and a local image collection device, wherein the collection device management device is connected to the panoramic image collection device and the local image collection device, respectively, wherein the panoramic image collection device is used to collect a panoramic image of a space, and the local image collection device is used to collect a local image of the space; the method includes:

[0006] Acquire a first partial image set, where the first partial image set includes a plurality of partial images, wherein the plurality of partial images in the first partial image set are partial images acquired by the partial image acquisition device at a plurality of posture positions in a first posture position set, and different posture positions in the first posture position set correspond to different yaw angles;

[0007] stitching all the partial images in the first partial image set to obtain a first stitched image;

[0008] The first stitched image is compared with the panoramic image, and according to the comparison result of the first stitched image and the panoramic image, a preset position is deployed for the local image acquisition device, where the preset position is a posture position required for the local image acquisition device to capture images at a fixed point.

[0009] In this technical solution, a first local image set is obtained, wherein the multiple images in the first local image set are local images acquired by the local image acquisition device in the preset position deployment system at multiple posture positions in the first posture position set, and different posture positions in the first posture position set correspond to different yaw angles. All local images in the first local image set are spliced to obtain a first spliced image, and the first spliced image is compared with the panoramic image acquired by the panoramic image acquisition device in the preset position deployment system. According to the comparison result of the first spliced image and the panoramic image, the preset position is deployed for the local image acquisition device to realize automatic deployment of the preset position. Since the image content in the local image acquired by the local image acquisition device will be included in the image content of the panoramic image acquired by the panoramic image acquisition device, the local images acquired by the local image acquisition device at different posture positions are spliced and then compared with the panoramic image to deploy the preset position, so that the preset position can cover all spatial areas in the horizontal viewing direction, thereby ensuring the rationality of the preset position.

[0010] In combination with the first aspect, in a possible implementation, the comparing the first stitched image with the panoramic image and deploying a preset position for the local image acquisition device based on the comparison result of the first stitched image and the panoramic image includes: determining the image similarity between the first stitched image and the panoramic image; and determining the preset position corresponding to the local image acquisition device in combination with the image similarity and multiple posture positions in the first posture position set.

[0011] Since image similarity reflects the degree of visual similarity of images, determining the preset position corresponding to the local image acquisition device according to the image similarity of the stitched image panoramic image and multiple posture positions in the posture position set is conducive to the rationality of the preset position deployment.

[0012] In combination with the first aspect, in a possible implementation, the multiple posture positions in the first posture position set are obtained by the local image acquisition device sequentially adjusting the posture position of the local image acquisition device according to a yaw angle step, the yaw angle step is the difference between the first yaw angle and the second yaw angle, the first yaw angle is the yaw angle corresponding to the local image acquisition device after adjusting the posture position, and the second yaw angle is the yaw angle corresponding to the local image acquisition device before adjusting the posture position; the number of the first stitched images is multiple, each first stitched image is obtained by stitching all the local images in the first local image set corresponding to a first posture position set, the multiple first stitched images correspond to the multiple first posture position sets, and different first stitched images may correspond to different first posture position sets. The posture position sets correspond to different yaw angle step sizes; the combination of the image similarity and the multiple posture positions in the first posture position set to determine the preset position corresponding to the local image acquisition device includes: determining a qualified first stitched image among the multiple first stitched images, wherein the image similarity between the qualified first stitched image and the panoramic image is greater than a preset threshold; determining a first posture position set with the largest yaw angle step size in the qualified first posture position set, wherein the qualified first posture position set is the first posture position set corresponding to the qualified first stitched image; and determining the multiple posture positions in the first posture position set with the largest yaw angle step size as the preset positions corresponding to the local image acquisition device.

[0013] By determining a plurality of attitude positions that meet the conditions and have the largest yaw angle as preset positions corresponding to the local image acquisition device, the number of preset positions can be reduced, thereby extending the service life of the local image acquisition device.

[0014] In combination with the first aspect, in a possible implementation, the multiple posture positions in the first posture position set are obtained by the local image acquisition device sequentially adjusting the posture position of the local image acquisition device according to a yaw angle step, the yaw angle step being the difference between a first yaw angle and a second yaw angle, the first yaw angle being the yaw angle corresponding to the local image acquisition device after adjusting the posture position, and the second yaw angle being the yaw angle corresponding to the local image acquisition device before adjusting the posture position; determining the preset position corresponding to the local image acquisition device by combining the image similarity and the multiple posture positions in the first posture position set includes: when the image similarity is less than or equal to a preset threshold, reducing the yaw angle step and performing the step of acquiring the first partial image set until the image similarity is greater than the preset threshold; and when the image similarity is greater than the preset threshold, determining the multiple posture positions in the first posture position set as the preset positions corresponding to the local image acquisition device.

[0015] When the image similarity is less than or equal to a preset threshold, the yaw angle step size is gradually reduced, and when the image similarity is greater than the preset threshold, multiple posture positions in the posture position concentration are determined as preset positions corresponding to the local image acquisition device, which helps to quickly deploy the preset positions while ensuring that the preset positions are reasonable.

[0016] In combination with the first aspect, in a possible implementation, determining the image similarity between the first stitched image and the panoramic image includes: determining multiple groups of matching feature points based on the first stitched image and the panoramic image, each group of matching feature points including stitching feature points and panoramic feature points matching the stitching feature points, the stitching feature points being feature points in the first stitched image, and the panoramic feature points being feature points in the panoramic image; and determining the image similarity between the first stitched image and the panoramic image based on the multiple groups of matching feature points.

[0017] By determining multiple sets of matching feature points in the stitched image and the panoramic image, and determining the image similarity between the stitched image and the panoramic image based on the multiple sets of matching feature points, it is helpful to accurately compare the stitched image and the panoramic image.

[0018] In combination with the first aspect, in a possible implementation, determining the image similarity between the first stitched image and the panoramic image based on the multiple groups of matching feature points includes: determining four target stitching feature points and four target panoramic feature points from the multiple groups of matching feature points, the four target stitching feature points being the stitching feature points closest to the four image boundaries of the first stitched image, and the four target panoramic feature points being the panoramic feature points that match the four target stitching feature points; in the first stitched image, intercepting the image area corresponding to the four target stitching feature points as a first sub-image; in the panoramic image, intercepting the image area corresponding to the four target panoramic feature points as a second sub-image; adjusting the size of the second sub-image to the same size as the first sub-image to obtain a comparison image of the first sub-image; and calculating the similarity between the comparison image and the first sub-image as the image similarity between the first stitched image and the panoramic image.

[0019] The image similarity between the stitched image and the panoramic image is determined by selecting the feature points closest to the image boundary from the feature points of the stitched image and the panoramic image, and then cropping the images corresponding to the feature points. After adjusting the cropped images to have the same size, the image similarity of the cropped images is calculated. This helps to accurately determine the image similarity between the stitched image and the panoramic image.

[0020] In combination with the first aspect, in a possible implementation, the multiple posture positions in the first posture position set all correspond to a first pitch angle; the method also includes: obtaining a second local image set, the second local image set includes multiple local images, the multiple local images in the second local image set are local images acquired by the local image acquisition device at multiple posture positions in the second posture position set, different posture positions in the second posture position set correspond to different yaw angles, the multiple posture positions in the second posture position set all correspond to a second pitch angle, and the second pitch angle is different from the first pitch angle; stitching all the local images in the second local image set to obtain a second stitched image; comparing the second stitched image with the panoramic image, and deploying a preset position for the local image acquisition device according to the comparison result of the second stitched image and the panoramic image.

[0021] By changing the pitch angle of the local image acquisition device, reacquiring the local image set, stitching the images in the local image set, and comparing the stitched image with the panoramic image, multiple rows of preset positions in the visual depth direction can be deployed one by one, thereby deploying the preset positions in the entire spatial range.

[0022] In combination with the first aspect, in a possible implementation, the space contains a preset object to be detected, and the preset object to be detected is located at the position farthest from the local image acquisition device in the space; before acquiring the first local image set, it also includes: acquiring a sample local image, the sample local image being a local image obtained by the local image acquisition device acquiring the object to be detected at a sample magnification; when the object to be detected in the sample local image does not meet the detection requirements, increasing the sample magnification and executing the step of acquiring the sample local image until the object to be detected in the sample local image meets the detection requirements; setting the sample magnification when the object to be detected in the sample local image meets the detection requirements as the maximum magnification of the local image acquisition device during the local image acquisition process.

[0023] Before acquiring the local image set, the magnification of the local image acquisition device is adjusted, and the magnification of the object to be detected located at the farthest position from the local image acquisition device in space when it meets the detection requirements in the local image is determined as the maximum magnification of the local image acquisition device during the local image acquisition process, to ensure that the local image acquired by the local image acquisition device meets the detection requirements.

[0024] In a second aspect, a pre-positioned position deployment device is provided, which is applied to a collection device management device in a pre-positioned position deployment system. The pre-positioned position deployment system includes the collection device management device, a panoramic image collection device, and a local image collection device. The collection device management device is connected to the panoramic image collection device and the local image collection device, respectively. The panoramic image collection device is used to collect a panoramic image of a space, and the local image collection device is used to collect a local image of the space. The device includes:

[0025] an image set acquisition module, configured to acquire a first partial image set, wherein the first partial image set includes a plurality of partial images, the plurality of partial images in the first partial image set being partial images acquired by the partial image acquisition device at a plurality of posture positions in a first posture position set, wherein different posture positions in the first posture position set correspond to different yaw angles;

[0026] an image stitching module, configured to stitch all the partial images in the first partial image set to obtain a first stitched image;

[0027] The preset position deployment module is used to compare the first stitched image with the panoramic image, and deploy a preset position for the local image acquisition device based on the comparison result of the first stitched image and the panoramic image, wherein the preset position is the posture position required for the local image acquisition device to capture the image at a fixed point.

[0028] In a third aspect, a computer device is provided, comprising a memory and a processor, wherein the memory is connected to the processor, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the computer device executes the preset position deployment method of the first aspect.

[0029] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the preset position deployment method of the first aspect.

[0030] The present application can achieve the following technical effects: automatic deployment of preset positions; since the image content in the local image captured by the local image acquisition device will be included in the image content of the panoramic image captured by the panoramic image acquisition device, the local images captured by the local image acquisition device at different posture positions are spliced and then compared with the panoramic image to deploy the preset positions, so that the preset positions can cover all spatial areas in the horizontal viewing direction, ensuring the rationality of the preset positions. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0032] Figure 1 A schematic diagram of the system composition of a pre-positioned deployment system provided in an embodiment of the present application;

[0033] Figure 2 A flowchart of a pre-positioning method provided in an embodiment of the present application;

[0034] Figure 3 A schematic diagram of a partial image set and a stitched image provided in an embodiment of the present application;

[0035] Figure 4 A flowchart of another pre-positioning method provided in an embodiment of the present application;

[0036] Figure 5 A schematic diagram of splicing feature points provided in an embodiment of the present application;

[0037] Figure 6 A flowchart of another pre-positioning method provided in an embodiment of the present application;

[0038] Figure 7 A flowchart of another pre-positioning method provided in an embodiment of the present application;

[0039] Figure 8 A schematic diagram of a process for determining the maximum magnification in a local image acquisition process according to an embodiment of the present application;

[0040] Figure 9 This is a structural diagram of a pre-position deployment device provided in an embodiment of the present application;

[0041] Figure 10 It is a structural diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solutions and advantages of this application more clear, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0043] It should be noted that, if there is no conflict, the various features in the embodiments of the present application can be combined with each other and are all within the scope of protection of the present application. In addition, although the functional modules are divided in the device schematic and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order than the module division in the device or the order in the flow chart. Furthermore, the words "first", "second", "third", etc. used in this application do not limit the data and execution order, but only distinguish between the same items or similar items with basically the same functions and effects.

[0044] The technical solution of the present application is applicable to the pre-position deployment scenario. The pre-position refers to a specific position or state that is pre-set and stored in some adjustable or positionable devices; the pre-position deployment refers to pre-setting the adjustable or positionable device to a specific position or state according to actual needs and planning. In the present application, the pre-position deployment refers to pre-setting the posture position of a camera with adjustable posture position (hereinafter referred to as the adjustable camera) so that the adjustable camera can subsequently capture images at a fixed point according to the pre-set posture position. Capturing images at a fixed point refers to capturing images at a specific position. In the present application, the adjustable camera captures images at a deployed preset position.

[0045] Currently, adjustable cameras are usually deployed manually with preset positions based on industry experience. Deployers need to go to the actual site to deploy the cameras at fixed locations. The accuracy of the deployment depends entirely on the deployment personnel's debugging, which is time-consuming and labor-intensive. In addition, the accuracy of the deployment is uncontrollable.

[0046] In view of this, the present application proposes a preset position deployment scheme, which enables a close-up camera with adjustable posture and position to capture multiple local images from left to right, stitches the multiple local images captured by the close-up camera, and compares the stitched image with the panoramic image captured by the panoramic lens. According to the comparison result of the stitched image and the panoramic image, the preset position is deployed for the close-up camera, thereby realizing automatic deployment of the preset position, saving manpower and deployment time; the image content in the local image captured by the close-up camera will be included in the image content of the panoramic image captured by the panoramic lens, and the multiple local images are stitched and then compared with the panoramic image to deploy the preset position, so that the preset position can cover all spatial areas in the horizontal viewing angle direction, thereby ensuring the rationality of the preset position, that is, ensuring the accuracy of the preset position deployment, and making the deployment accuracy controllable.

[0047] The technical solution of the present application is applied to a pre-positioned position deployment system. For ease of understanding, the pre-positioned position deployment system of the present application is first introduced.

[0048] See also Figure 1 , Figure 1 A schematic diagram of the system composition of a pre-positioned deployment system provided in an embodiment of the present application is shown as follows: Figure 1 As shown, the pre-position deployment system includes a collection device management device 101, a panoramic image collection device 102, and a local image collection device 103. The collection device management device 101 is a device for managing the collection devices. The collection device management device 101 is connected to the panoramic image collection device 102 and the local image collection device 103. The connection between the collection device management device 101 and the panoramic image collection device 102 and the local image collection device 103 can be a wired connection, or the connection between the collection device management device 101 and the panoramic image collection device 102 and the local image collection device 103 can be a wireless connection.

[0049] The panoramic image acquisition device 102 is used to capture a panoramic image of a space. A panoramic image refers to an image that reflects the entire space. A panoramic image can fully display the content in the space and generally has a large field of view. In the present application, the panoramic image acquisition device 102 can be a wide-angle lens, and the horizontal viewing angle of the wide-angle lens exceeds a preset field of view angle, such as 120°. In this way, the panoramic image captured by the panoramic image acquisition device 102 can accommodate the content in the space in a first horizontal direction. The first horizontal direction is used to reflect the direction of the field of view angle on the horizontal plane. The horizontal plane refers to a plane perpendicular to the direction of gravity.

[0050] The local image acquisition device 103 is used to capture a local image of a space. A local image refers to an image reflecting a specific local area in the space. A local image can also be called a close-up image, which displays a portion of the content in the space. The local image acquisition device 103 may be a telephoto lens, which can capture distant objects and magnify them, so that distant objects occupy more pixels in the image. The focal length of the telephoto lens is greater than a preset focal length, such as 85 mm, and the maximum focal length can reach hundreds of millimeters. In this way, the local image acquisition device 103 can capture close-up content from a distance, ensuring that the distant content meets the detection requirements in the local image. In this application, the posture and position of the local image acquisition device 103 are adjustable. By adjusting the posture and position, the local image acquisition device 103 can capture images of any area in the space. For example, the local image acquisition device 103 can be mounted on a pan-tilt platform, a support device used to stabilize the image acquisition device and allowing the local image acquisition device 103 to rotate freely in any direction, thereby enabling multi-directional adjustment.

[0051] In some specific embodiments, the panoramic image acquisition device 102 and the local image acquisition device 103 are located at the same position in space. The term "same position" means that the distance between the panoramic image acquisition device 102 and the local image acquisition device 103 is less than a preset distance, for example, the distance between the panoramic image acquisition device 102 and the local image acquisition device 103 is less than 0.05 meters. The panoramic image acquisition device 102 and the local image acquisition device 103 are located at the same position in space, ensuring that the local image captured by the local image acquisition device 103 is part of the panoramic image captured by the panoramic image acquisition device 102.

[0052] The acquisition device management device 101 and the panoramic image acquisition device 102 and the local image acquisition device 103 can be independent devices; for example, the panoramic image acquisition device 102 and the local image acquisition device 103 are integrated into one image acquisition device, and the acquisition device management device 101 is connected to the image acquisition device integrated with the panoramic image acquisition device 102 and the local image acquisition device 103 via wireless or wired communication. The acquisition device management device 101 is, for example, a teaching terminal host, a personal computer, etc. The acquisition device management device 101 and the panoramic image acquisition device 102 and the local image acquisition device 103 can also be integrated into one device. For example, the acquisition device management device 101 and the panoramic image acquisition device 102 and the local image acquisition device 103 are integrated into a computer device that can perform both acquisition and recognition, such as an interactive tablet device. This application does not limit the connection method and integration method between the acquisition device management device 101 and the panoramic image acquisition device 102 and the local image acquisition device 103.

[0053] based on Figure 1 The pre-positioned deployment system 10 shown can implement the technical solution of the present application, which is specifically applied to the collection device management apparatus 101 in the pre-positioned deployment system 10. The technical solution of the present application is described in detail below.

[0054] See also Figure 2 , Figure 2 A flow chart of a pre-position deployment method provided in an embodiment of the present application is provided. The method is applied to a collection device management device in a pre-position deployment system. The pre-position deployment system is as follows: Figure 1 As shown; Figure 2 As shown, the method includes the following steps:

[0055] S201: Acquire a first partial image set.

[0056] Here, the first local image set includes multiple local images, and the multiple local images in the first local image set are local images acquired by the local image acquisition device at multiple posture positions in the first posture position set; different posture positions in the first posture position set correspond to different yaw angles, and a local image in the first local image set is acquired by the local image acquisition device at a posture position in the first posture position set; different local images in the first local image set correspond to different yaw angles, that is, different local images in the first local image set are local images acquired by the local image acquisition device at different yaw angles; the yaw angle refers to the angle of horizontal rotation along the vertical axis, and the vertical axis is parallel to the direction of gravity. The posture position of the local image acquisition device can be expressed in the form of Euler angles, quaternions, rotation matrices or axis angles. For the definition of local images, please refer to the aforementioned Figure 1 The corresponding description.

[0057] The local image acquisition device is controlled to change the yaw angle multiple times in succession to adjust the posture position of the local image acquisition device multiple times, and the local images acquired by the local image acquisition device at each adjusted posture position are obtained as the first local image set. Figure 3 , the first local image set is as follows Figure 3 As shown in J1 in , different local images correspond to different posture positions, and different posture positions correspond to different yaw angles.

[0058] S202 : Stitching all partial images in the first partial image set to obtain a first stitched image.

[0059] Here, stitching all partial images in the first partial image set to obtain the first stitched image means arranging the plurality of partial images in the first partial image set in order of yaw angle from small to large or from large to small, and then stitching the plurality of arranged partial images one by one along the image width direction so that the height of the stitched image remains unchanged and the width increases, thereby obtaining the first stitched image. The image width reflects the length of the image or the number of pixels in the first horizontal direction described above, the image width direction refers to the direction reflecting the width of the image, and the image height reflects the length of the image or the number of pixels in the vertical direction, where the vertical direction is parallel to the direction of gravity.

[0060] For example, the first local image set includes n local images, and the resolution of each local image is 540*480. Assuming that the n local images are arranged in order of yaw angle from small to large or from large to small, the n local images obtained are local image 1 to local image n, then local image 1 is spliced with local image 2 to obtain spliced image 1, and the resolution of spliced image 1 is w1*480, 540<w1≤1080; then spliced image 1 is spliced with local image 3 to obtain spliced image 2, and the resolution of spliced image 2 is w2*480, 1080<w2≤1620; ...; finally, spliced image (n-1) is spliced with local image n to obtain spliced image n, and spliced image n is wn*480, (n-1)*540<w2≤n*540; spliced image n is the first spliced image. For example, the first spliced image is as follows Figure 3 As shown in P1.

[0061] The images can be stitched together using the following principles: first, feature matching is performed on the images to be stitched, and geometric transformation parameters (such as perspective transformation and affine transformation parameters) between the images to be stitched are determined. The geometric transformation parameters are then used to perform image registration on the images to align the images to be stitched together; the registered images are then fused to obtain a stitched image. It is understood that all partial images in the first partial image set can be stitched together using any image stitching algorithm, and this application does not limit this.

[0062] S203 : Compare the first stitched image with the panoramic image, and deploy a preset position for the local image acquisition device according to the comparison result between the first stitched image and the panoramic image.

[0063] Here, the preset position is the posture position required by the local image acquisition device to capture images at a fixed point. For the meaning of capturing images at a fixed point, please refer to the above description.

[0064] The panoramic image is an image captured by the panoramic image acquisition device in the pre-positioned deployment system. For the definition of the panoramic image acquisition device, please refer to the above Figure 1 The corresponding description.

[0065] In some embodiments, comparing the first stitched image with the panoramic image, and deploying a preset position for the local image acquisition device based on the comparison result of the first stitched image and the panoramic image includes: determining the image similarity between the first stitched image and the panoramic image; and determining the preset position corresponding to the local image acquisition device based on the image similarity between the first stitched image and the panoramic image and the plurality of posture positions in the first posture position set. For a specific implementation method of determining the image similarity between the first stitched image and the panoramic image, please refer to the following. Figure 4 The corresponding description.

[0066] In some feasible embodiments, when the image similarity between the first stitched image and the panoramic image exceeds a preset threshold, the multiple posture positions in the first posture position set are determined as preset positions corresponding to the local image acquisition device. The image similarity between the first stitched image and the panoramic image exceeds the preset threshold, indicating that the first stitched image is close to the actual scene in space, and that the overlap between the multiple posture positions in the first posture position set is reasonable and effective, thereby ensuring that the image captured by the local image acquisition device meets the detection requirements.

[0067] Alternatively, the following Figure 4 or Figure 5 The implementation method described in the above is to determine the preset position corresponding to the local image acquisition device by combining the image similarity between the first stitched image and the panoramic image and the multiple posture positions in the first posture position set. Please refer to the following text Figure 4 and Figure 5 The corresponding description.

[0068] In other embodiments, the first stitched image and the panoramic image may be compared based on statistical comparison to obtain a comparison result between the first stitched image and the panoramic image, and then, based on the comparison result between the first stitched image and the panoramic image, a preset position may be deployed for the local image acquisition device. For example, the first stitched image and the panoramic image may be compared by comparing their color histograms, feature point histograms, etc. to obtain a comparison result between the first stitched image and the panoramic image. This application is not limited to this.

[0069] In the above Figure 2 In the corresponding technical solution, a first local image set is obtained, and multiple images in the first local image set are local images acquired by the local image acquisition device in the preset position deployment system at multiple posture positions in the first posture position set. Different posture positions in the first posture position set correspond to different yaw angles. All local images in the first local image set are spliced to obtain a first spliced image. The first spliced image is compared with the panoramic image acquired by the panoramic image acquisition device in the preset position deployment system. According to the comparison result of the first spliced image and the panoramic image, the preset position is deployed for the local image acquisition device to realize automatic deployment of the preset position. Since the image content in the local image acquired by the local image acquisition device will be included in the image content of the panoramic image acquired by the panoramic image acquisition device, the local images acquired by the local image acquisition device at different posture positions are spliced and then compared with the panoramic image to deploy the preset position, so that the preset position can cover all spatial areas in the horizontal viewing direction, thereby ensuring the rationality of the preset position.

[0070] In some embodiments, the plurality of posture positions in the first posture position set are obtained by the local image acquisition device sequentially adjusting the posture position of the local image acquisition device according to the yaw angle step length, the yaw angle step length being the difference between the first yaw angle and the second yaw angle, the first yaw angle being the yaw angle corresponding to the posture position after the local image acquisition device adjusts the posture position, and the second yaw angle being the yaw angle corresponding to the posture position before the local image acquisition device adjusts the posture position; that is, the difference between the yaw angles corresponding to two adjacent posture positions in the first posture position set is the yaw angle step length. The first posture position set includes Figure 3 Taking the posture positions 1, 2, 3, ..., and n shown as an example, assuming a yaw angle step length of Δyaw, the posture positions 1, 2, 3, ..., and n are obtained by the local image acquisition device sequentially adjusting the posture position of the local image acquisition device according to the yaw angle step length. Then, the difference between yaw angle 2 and yaw angle 1 is Δyaw, the difference between yaw angle 3 and yaw angle 2 is Δyaw, ..., and the difference between yaw angle n and yaw angle (n-1) is Δyaw. In the process of controlling the local image acquisition device to sequentially change the yaw angle multiple times to adjust the posture position of the local image acquisition device multiple times, the yaw angle step length is sent to the local image acquisition device, causing the local image acquisition device to sequentially change the yaw angle multiple times according to the yaw angle step length to adjust the posture position of the local image acquisition device multiple times. Alternatively, multiple yaw angles are calculated based on the yaw angle step length, and one of the multiple yaw angles is sent to the local image acquisition device each time, causing the local image acquisition device to change the yaw angle based on the received yaw angle to adjust the posture position of the local image acquisition device.

[0071] In the case where the plurality of posture positions in the first posture position set are obtained by sequentially adjusting the posture positions of the local image acquisition device according to the yaw angle step, the posture positions of the local image acquisition device can be obtained by Figure 4 or Figure 5 The corresponding method embodiment is to deploy a preset position of the local image acquisition device.

[0072] See also Figure 4 , Figure 4 A flow chart of another pre-position deployment method provided in an embodiment of the present application is provided. The method is applied to a collection device management device in a pre-position deployment system. The pre-position deployment system is as follows: Figure 1 As shown; Figure 4 As shown, the method includes the following steps:

[0073] S301: Acquire a first partial image set.

[0074] S302 : Stitching all partial images in the first partial image set to obtain a first stitched image.

[0075] Here, the specific implementation principles of steps S301 to S302 can refer to the description of steps S201 to S202 above, which will not be repeated here.

[0076] S303: Determine the image similarity between the first stitched image and the panoramic image.

[0077] In one embodiment, the image similarity between the first stitched image and the panoramic image is determined through the following steps A1-A2:

[0078] A1. Determine multiple groups of matching feature points based on the first stitched image and the panoramic image.

[0079] Here, each set of matching feature points in the multiple sets of matching features includes stitching feature points and panoramic feature points matching the stitching feature points. The stitching feature points are feature points in the first stitched image, and the panoramic feature points are feature points in the panoramic image.

[0080] Among them, feature point extraction can be performed on the first stitched image to obtain feature points in the first stitched image, and feature point extraction can be performed on the panoramic image to obtain feature points in the panoramic image; feature point matching is performed on the feature points in the first stitched image and the feature points in the panoramic image to obtain stitching feature points and panoramic feature points matching the stitching feature points, thereby obtaining multiple groups of matching feature points.

[0081] Feature points are extracted from the first stitched image and the panoramic image using any one or more feature point extraction algorithms to obtain feature points in the first stitched image and feature points in the panoramic image. Feature point extraction algorithms include, but are not limited to, a scale-invariant feature transform (SIFT) algorithm, an oriented fast and rotated brief (ORB) algorithm, and the like.

[0082] Based on any feature point matching algorithm, feature points in the first stitched image are matched with feature points in the panoramic image to obtain stitching feature points and panoramic feature points that match the stitching feature points.

[0083] In one specific implementation, for any feature point extracted from the first stitched image (hereinafter referred to as a to-be-matched feature point), a feature descriptor for the to-be-matched feature point can be obtained. The feature descriptor is an attribute parameter used to describe the feature point, typically presented as a multidimensional position vector, and is extracted using a feature point extraction algorithm. The Euclidean distance between the feature descriptor of the to-be-matched feature point and the feature descriptor of a feature point in the panoramic image is calculated. If the Euclidean distance between the feature descriptor of the to-be-matched feature point and the feature descriptor of a target feature point in the panoramic image is less than a preset distance threshold, the to-be-matched feature point is determined to be a stitching feature point, and the target feature point is determined to be a panoramic feature point that matches the stitching feature point. If the Euclidean distance between the feature descriptor of the to-be-matched feature point and the feature descriptor of each feature point in the panoramic image is greater than or equal to the preset distance threshold, it is determined that there is no feature point in the panoramic image that matches the to-be-matched feature point. For each feature point in the first stitched image, feature point matching is performed with feature points in the panoramic image in the same manner. All stitching feature points and panoramic feature points that match the stitching feature points can be determined, thereby obtaining multiple sets of matched feature points.

[0084] A2. Determine the image similarity between the first stitched image and the panoramic image based on the multiple sets of matching feature points.

[0085] In a feasible implementation, the image similarity between the first stitched image and the panoramic image is determined through the following steps a1-a5:

[0086] a1. Determine four target stitching feature points and four target panoramic feature points from multiple sets of matching feature points.

[0087] Here, the four target stitching feature points are the stitching feature points closest to the four image boundaries of the first stitching image. The position coordinates of the four target stitching feature points are respectively expressed as (x min1 ,y1),(x max1 ,y2),(x3,y min1 ), (x4, y max1 ), x min1 and x max1 represents the minimum and maximum values of all the stitching feature points in the first stitching image in the x-axis direction of the first stitching image, and y min1 and y max1 Indicates the minimum and maximum values of all stitching feature points in the first stitching image in the y-axis direction of the first stitching image.

[0088] Take the first stitched image as Figure 3 As shown in P1 in the figure, assume that the stitching feature points in the first stitching image are as follows Figure 5 As shown by the white dots in Figure 5The white dots z1, z2, z3, and z4 in the figure are the four target stitching feature points, among which the white dot z1 is the stitching feature point with the smallest x-axis coordinate, the white dot z4 is the stitching feature point with the largest x-axis coordinate, the white dot z3 is the stitching feature point with the smallest y-axis coordinate, and the white dot z2 is the stitching feature point with the largest y-axis coordinate.

[0089] The four target panoramic feature points are panoramic feature points that match the four target stitching feature points.

[0090] a2. In the first stitched image, image regions corresponding to the four target stitching feature points are intercepted as the first sub-image.

[0091] Here, the image area corresponding to the four target stitching feature points is the image area corresponding to the first bounding rectangle determined based on the four target stitching feature points. The first bounding rectangle includes the four target stitching feature points in the first stitching image. For example, the first stitching image and the four target stitching feature points are as follows: Figure 5 As shown, the first circumscribed rectangle is Figure 5 As shown in c1.

[0092] The coordinates of the four vertices of the first circumscribed rectangle are expressed as (x min1 ,y min1 ), (x min1 ,y max1 ), (x max1 ,y min1 ), (x max1 ,y max1 ).

[0093] a3. In the panoramic image, the image area corresponding to the four target panoramic feature points is intercepted as the second sub-image.

[0094] Here, the image area corresponding to the four target panoramic feature points is the image area corresponding to the second circumscribed rectangle determined based on the four target panoramic feature points. The second circumscribed rectangle includes the four panoramic feature points in the panoramic image. The four vertex coordinates of the second circumscribed rectangle are expressed as (x min2 ,y min2 ), (x min2 ,y max2 ), (x max2 ,y min2 ), (x max2 ,y max2 ), x min2 and x max2 Indicates the minimum and maximum values of the four target stitching feature points in the x-axis direction of the panoramic image, and y min2 and y max2 Indicates the minimum and maximum values of the four target stitching feature points in the y-axis direction of the panoramic image.

[0095] a4. Adjust the size of the second sub-image to be the same as the size of the first sub-image, and obtain a comparison image of the first sub-image.

[0096] a5. Calculate the similarity between the comparison image and the first sub-image as the image similarity between the first stitched image and the panoramic image.

[0097] In one specific implementation, a structural similarity index (SSIM) is calculated between the comparison image and the first sub-image as the similarity between the first stitched image and the panoramic image. The SSIM measures the similarity between two images in terms of structure, brightness, and contrast, and can more comprehensively evaluate the similarity between the comparison image and the first sub-image.

[0098] Alternatively, the similarity between the comparison image and the first sub-image may be calculated based on a pixel-based method. For example, the mean squared error (MSE) or peak signal-to-noise ratio (PSNR) between the comparison image and the first sub-image may be calculated as the similarity between the comparison image and the first sub-image. This application is not limited to this.

[0099] In the above steps a1-a5, the feature points closest to the image boundaries of the images are selected from the feature points of the stitched image and the panoramic image, and the images corresponding to the feature points are cut out. After the sizes of the cut out images are adjusted to be the same, the image similarity of the cut out images is calculated, which helps to accurately determine the image similarity between the stitched image and the panoramic image.

[0100] In an optional embodiment, after determining the multiple sets of matching feature points, the image similarity between the first stitched image and the panoramic image may be determined based on the number of matching feature points, the geometric consistency of the matching feature points, etc. For example, the image similarity between the first stitched image and the panoramic image may be determined based on the total number of the multiple sets of matching feature points; a greater total number indicates a higher image similarity between the first stitched image and the panoramic image. For another example, m groups of matching feature points are randomly sampled from multiple groups of matching feature points, where m ≥ 4. A homography matrix between the first stitched image and the panoramic image is calculated based on the m groups of matching feature points. It is determined whether each matching feature point in the multiple groups of matching feature points conforms to the homography matrix. Matching feature points in the multiple groups of matching feature points that conform to the homography matrix are determined as inliers, and the number of inliers is counted to obtain a number of inliers. If a feature point obtained by calculating the stitched feature point and the homography matrix is a panoramic feature point that matches the stitched feature point, it means that the matching feature point conforms to the homography matrix. The above steps of random sampling, calculating the homography matrix, and determining the inliers and the number of inliers are then repeated until the number of repetitions reaches a preset number, thereby obtaining multiple numbers of inliers. The image similarity between the first stitched image and the panoramic image is determined based on the maximum number of inliers among the multiple numbers of inliers. A greater maximum number of inliers indicates a higher image similarity between the first stitched image and the panoramic image. This application does not limit the specific implementation method of determining the image similarity between the first stitched image and the panoramic image based on the multiple groups of matching feature points.

[0101] In the above steps A1-A2, by determining multiple sets of matching feature points in the stitched image and the panoramic image, and determining the image similarity between the stitched image and the panoramic image based on the multiple sets of matching feature points, it is helpful to accurately compare the stitched image and the panoramic image.

[0102] Optionally, the image similarity between the first stitched image and the panoramic image may also be determined based on a deep learning method.

[0103] S304: Determine whether the image similarity between the first stitched image and the panoramic image is greater than a preset threshold.

[0104] If the image similarity between the first stitched image and the panoramic image is less than or equal to a preset threshold, it indicates that the first stitched image is significantly different from the real scene in space, and the settings of the multiple posture positions in the first posture position set are not reasonable, and step S305 is executed. If the image similarity between the first stitched image and the panoramic image is greater than the preset threshold, it indicates that the first stitched image is close to the real scene in space, and the settings of the multiple posture positions in the first posture position set are reasonable, and step S306 is executed.

[0105] S305: Reduce the yaw angle step size and execute step S301.

[0106] S306: Determine the multiple posture positions in the first posture position set as preset positions corresponding to the local image acquisition device.

[0107] In the above Figure 4 In the corresponding technical solution, after acquiring the first local image set and stitching all the local images in the first local image set to obtain the first stitched image, the image similarity between the first stitched image and the panoramic image is determined. When the image similarity is less than or equal to a preset threshold, the yaw angle step size is gradually reduced. When the image similarity is greater than the preset threshold, the multiple posture positions in the first posture position set corresponding to the first local image set are determined as the preset positions corresponding to the local image acquisition device. This helps to quickly deploy the preset positions while ensuring that the preset positions are reasonable.

[0108] See also Figure 6 , Figure 6 A flow chart of a pre-position deployment method provided in an embodiment of the present application is shown as follows: Figure 6 As shown, the method includes the following steps:

[0109] S401: Acquire multiple first partial image sets.

[0110] Here, the multiple first partial image sets are first partial image sets corresponding to multiple first posture and position sets. Each first posture and position set corresponds to one first partial image set, and different first posture and position sets correspond to different yaw angle step sizes. The multiple first partial image sets are obtained by repeatedly varying the yaw angle step size and executing step S201. For the definitions of the first partial image set, first posture and position set, and yaw angle step size, please refer to the previous description and will not be repeated here.

[0111] S402: Acquire a plurality of first stitched images.

[0112] Here, the multiple first stitched images are first stitched images corresponding to multiple first pose and position sets. One first stitched image corresponds to one first pose and position set, and one first stitched image is obtained by stitching together all the partial images in the first partial image set corresponding to one first pose and position set. Each of the multiple first stitched images is obtained by executing step S202 above. For details on how to stitch together the first stitched images, please refer to the description of step S202 above and will not be repeated here.

[0113] S403 : Determine an image similarity between each of the plurality of first stitched images and the panoramic image.

[0114] For each of the multiple first stitched images, the image similarity between the first stitched image and the panoramic image is determined in the same manner. Regarding the specific implementation method of determining the image similarity between the first stitched image and the panoramic image, please refer to the description of the aforementioned step S303, which will not be repeated here.

[0115] S404: Determine a first stitched image that meets a condition among a plurality of first stitched images.

[0116] Here, the image similarity between the first stitched image that meets the conditions and the panoramic image is greater than a preset threshold.

[0117] For example, there are five first stitched images, namely stitched image 1 to stitched image 5, and the preset threshold is 0.9. Assuming that the image similarity between stitched image 1 and the panoramic image is 0.85, the image similarity between stitched image 2 and the panoramic image is 0.95, the image similarity between stitched image 3 and the panoramic image is 0.9, the image similarity between stitched image 4 and the panoramic image is 0.87, and the image similarity between stitched image 5 and the panoramic image is 0.92, then stitched image 2 and stitched image 5 are the first stitched images that meet the conditions.

[0118] S405 : Determine a first attitude and position set with a maximum yaw angle step length among the first attitude and position sets that meet the conditions.

[0119] Here, the first posture and position set that meets the conditions is the first posture and position set corresponding to the first stitched image that meets the conditions.

[0120] Still taking the example of the first stitched images having five images, namely stitched image 1 to stitched image 5, assuming that stitched image 2 and stitched image 5 are the first stitched images that meet the conditions, then the first posture position set corresponding to stitched image 2 and the first posture position set corresponding to stitched image 5 are the first posture position sets that meet the conditions. Assuming that the yaw angle step size corresponding to stitched image 2 is yaw2, and the yaw angle step size corresponding to stitched image 5 is yaw5, yaw5>yaw2, then the first posture position set corresponding to stitched image 5 is the first posture position set with the largest yaw angle step size.

[0121] S406 , determining a plurality of posture positions in the first posture position set with the largest yaw angle step as preset positions corresponding to the local image acquisition device.

[0122] In the above Figure 6In the corresponding technical solution, by obtaining multiple first local image sets, different first local image sets correspond to different yaw angle step sizes, and obtaining multiple first stitched images, then determining the image similarity between each first stitched image in the multiple first stitched images and the panoramic image, the first stitched image with an image similarity greater than a preset threshold is determined as a qualified first stitched image, the first posture position set corresponding to the qualified first stitched image is determined as a qualified first posture position set, and in the qualified first posture position set, the first posture position set with the largest yaw angle step size is determined, and the multiple posture positions in the first posture position set with the largest yaw angle step size are determined as the preset positions corresponding to the local image acquisition device. This can reduce the number of preset positions and thus extend the life of the local image acquisition device.

[0123] In some embodiments, multiple posture positions in the first posture position set correspond to the same pitch angle, where the pitch angle refers to an angle of rotation up and down along a vertical axis, and the first posture position set corresponds to the first pitch angle. After the partial image acquisition device is deployed to obtain preset positions at one pitch angle, i.e., a row of preset positions, the pitch angle can be changed to obtain preset positions of the partial image acquisition device at another pitch angle, i.e., another row of preset positions.

[0124] See also Figure 7 , Figure 7 A flow chart of another pre-position deployment method provided in an embodiment of the present application is shown as follows: Figure 7 As shown, the method includes the following steps:

[0125] S501: Acquire a first partial image set.

[0126] S502 : Stitching all partial images in the first partial image set to obtain a first stitched image.

[0127] S503 : Compare the first stitched image with the panoramic image, and deploy a preset position for the local image acquisition device according to the comparison result between the first stitched image and the panoramic image.

[0128] Here, for the specific implementation of steps S501 to S503, please refer to the description of steps S201 to S203 above, which will not be repeated here.

[0129] S504: Acquire a second partial image set.

[0130] Here, the second local image set includes multiple local images, and the multiple local images in the second local image set are local images acquired by the local image acquisition device at multiple posture positions in the second posture position set; different posture positions in the second posture position set correspond to different yaw angles, and a local image in the second local image set is acquired by the local image acquisition device at a posture position in the second posture position set; different local images in the second local image set correspond to different yaw angles, that is, different local images in the second local image set are local images acquired by the local image acquisition device at different yaw angles; multiple posture positions in the second posture position set all correspond to the same pitch angle, and the multiple posture positions in the second posture position set have a second pitch angle, and the second pitch angle is different from the first pitch angle corresponding to the first posture position set.

[0131] Among them, by controlling the local image acquisition device to change the pitch angle, and controlling the local image acquisition device to adjust the yaw angle multiple times in succession, the posture position of the local image acquisition device is adjusted multiple times, and the local images acquired by the local image acquisition device at each adjusted posture position are obtained to obtain the second local image set.

[0132] S505 , stitching all the partial images in the second partial image set to obtain a second stitched image.

[0133] Here, all the partial images in the second partial image set are stitched together to obtain the second stitched image. The specific implementation principle is the same as that of stitching all the partial images in the first partial image set in the aforementioned step S202 to obtain the first stitched image. Please refer to the relevant description of the aforementioned step S202, which will not be repeated here.

[0134] S506 : Compare the second stitched image with the panoramic image, and deploy a preset position for the local image acquisition device according to the comparison result between the second stitched image and the panoramic image.

[0135] Here, the second stitched image is compared with the panoramic image, and a preset position is deployed for the local image acquisition device based on the comparison result of the second stitched image and the panoramic image. This is the same as the implementation principle of comparing the first stitched image with the panoramic image in the aforementioned step S203, and deploying the preset position for the local image acquisition device based on the comparison result of the first stitched image and the panoramic image. Please refer to the relevant description of the aforementioned step S203, which will not be repeated here.

[0136] In the above Figure 7 In the corresponding technical solution, by changing the pitch angle of the local image acquisition device, re-acquiring the local image set, stitching the images in the local image set, and comparing the stitched image with the panoramic image, multiple rows of preset positions in the visual depth direction can be deployed one by one, thereby deploying the preset positions in the entire spatial range.

[0137] In some embodiments, before acquiring the first partial image set, the maximum magnification of the partial image acquisition device during the partial image acquisition process can also be set. Figure 8 The process steps shown in the figure set the maximum magnification of the local image acquisition device during the local image acquisition process, including the following steps B1-B4:

[0138] B1. Obtain a local image of the sample.

[0139] Here, the sample partial image is a partial image obtained by capturing a predetermined object to be detected by the partial image acquisition device at a sample magnification. The predetermined object to be detected is located at a position farthest from the partial image acquisition device in space. The initial value of the sample magnification may be the minimum magnification of the partial image acquisition device.

[0140] The object to be detected is the object that needs to be captured by the panoramic image acquisition device and the local image acquisition device. The object to be detected is determined by the specific image detection task. Different image detection tasks have different definitions of the object to be detected. For example, if the image detection task is face recognition, the default object to be detected is the face.

[0141] B2. Determine whether the object to be detected in the local image of the sample meets the detection requirements.

[0142] In a feasible implementation, the image area where the object to be detected is located can be cut out from the sample image as the image to be detected, and it is determined whether the clarity of the image to be detected is greater than the preset clarity. If the clarity of the image to be detected is greater than the preset clarity, it is determined that the object to be detected in the sample local image meets the detection requirements; if the clarity of the image to be detected is less than or equal to the preset clarity, it is determined that the object to be detected in the sample local image does not meet the detection requirements. Among them, it can be determined whether the image size of the image to be detected is greater than the preset size. If the image size of the image to be detected is greater than the preset size, it is determined that the clarity of the image to be detected is greater than the preset clarity; if the image size of the image to be detected is less than or equal to the preset size, it is determined that the clarity of the image to be detected is less than the preset clarity. The preset size is the size set to measure whether the image meets the recognition requirements, and the preset size is set based on the object to be detected and the detection requirements. Taking the object to be detected as a student's face as an example, assuming that a 30*30 face image is required to recognize the student's identity in the image, the preset size is 30*30.

[0143] If the object to be detected in the sample partial image meets the detection requirements, step B4 is executed; if the object to be detected in the sample partial image does not meet the detection requirements, step B3 is executed.

[0144] B3. Increase the sample magnification and execute step B1.

[0145] B4. The sample magnification when the object to be detected in the sample partial image meets the detection requirements is set as the maximum magnification of the partial image acquisition device during the partial image acquisition process.

[0146] Among them, the local image acquisition process can refer to the process in which the local image acquisition device acquires local images in the above-mentioned first local image set or the above-mentioned second local image set, or it can refer to the process in which the local image acquisition device acquires images at fixed points according to the preset positions after the preset positions are deployed for the local image acquisition device. This application does not impose any restrictions on this.

[0147] During the partial image acquisition process, the partial image acquisition device acquires the partial image at a magnification less than or equal to the maximum magnification determined in step B4.

[0148] In the above steps B1-B4, before obtaining the local image set, the magnification of the local image acquisition device is adjusted, and the magnification of the object to be detected located at the farthest position from the local image acquisition device in space when it meets the detection requirements in the local image is determined as the maximum magnification of the local image acquisition device during the local image acquisition process, to ensure that the local image acquired by the local image acquisition device meets the detection requirements.

[0149] The method of the present application is introduced above, and the device of the present application is introduced below.

[0150] See also Figure 9 , Figure 9 This is a schematic diagram of the structure of a pre-positioned deployment device provided in an embodiment of the present application, which is applied to a collection device management device in a pre-positioned deployment system. Figure 1 As shown; Figure 9 As shown, the pre-position deployment device 60 includes:

[0151] An image set acquisition module 601 is configured to acquire a first partial image set, where the first partial image set includes a plurality of partial images. The plurality of partial images in the first partial image set are partial images acquired by the partial image acquisition device at a plurality of posture positions in a first posture position set, where different posture positions in the first posture position set correspond to different yaw angles.

[0152] An image stitching module 602 is configured to stitch all the partial images in the first partial image set to obtain a first stitched image;

[0153] The preset position deployment module 603 is used to compare the first stitched image with the panoramic image, and deploy preset positions for the local image acquisition device based on the comparison result of the first stitched image and the panoramic image. The preset positions are the posture positions required for the local image acquisition device to capture images at a fixed point.

[0154] It should be noted that the above-mentioned pre-position deployment device 60 can execute the above-mentioned pre-position deployment method provided in the embodiment of this application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not fully described in the embodiment, please refer to the above-mentioned pre-position deployment method provided in the embodiment of this application.

[0155] See also Figure 10 , Figure 10 7 is a schematic diagram of the structure of a computer device provided in an embodiment of the present application, wherein the computer device 70 includes a processor 701 and a memory 702. The memory 702 is connected to the processor 701, for example, via a bus.

[0156] The processor 701 is configured to support the computer device 70 in executing the corresponding functions of the method in the above method embodiment. The processor 701 can be a central processing unit (CPU), a network processor (NP), a hardware chip, or any combination thereof. The above hardware chip can be an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The above PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0157] Memory 702 is used to store program code, etc. Memory 702 may include volatile memory (VM), such as random access memory (RAM); non-volatile memory (NVM), such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); or a combination of the aforementioned types of memory.

[0158] The memory 702 is used to store non-volatile software programs, non-volatile computer executable programs, and modules, such as the program instructions / modules corresponding to the pre-positioned position deployment method in the embodiments of the present application. The processor executes the non-volatile software programs, instructions, and modules stored in the memory to perform various functional applications and data processing of the pre-positioned position deployment method, thereby implementing the functions of the pre-positioned position deployment method provided in the above-mentioned method embodiments.

[0159] The memory 702 may include a program storage area and a data storage area. The program storage area may store an operating system and application programs required for at least one function. The data storage area may store data generated based on the use of the pre-positioned device. In some embodiments, the memory may include a memory remote from the processor, and such remote memory may be connected to the pre-positioned device via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0160] The one or more modules are stored in the memory, and when executed by the one or more processors, execute the preset position deployment method in any of the above method embodiments, for example, execute the method steps described in the above method embodiments, and realize the functions of the modules described in the above device embodiments.

[0161] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the method as described in the above embodiment.

[0162] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware through a computer program. The program can be stored in a computer-readable storage medium, and when executed, the program can include the processes in the above-described method embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0163] The above disclosure is only a preferred embodiment of the present application, and certainly cannot be used to limit the scope of rights of the present application. Therefore, equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A pre-position deployment method, characterized in that: A collection device management device used in a pre-positioned deployment system, the pre-positioned deployment system comprising the collection device management device, a panoramic image collection device, and a local image collection device, the collection device management device being connected to the panoramic image collection device and the local image collection device, respectively; the panoramic image collection device being used to collect panoramic images of a space, and the local image collection device being used to collect local images of the space; The method comprises: Acquire a first partial image set, where the first partial image set includes a plurality of partial images, wherein the plurality of partial images in the first partial image set are partial images acquired by the partial image acquisition device at a plurality of posture positions in a first posture position set, and different posture positions in the first posture position set correspond to different yaw angles; stitching all the partial images in the first partial image set to obtain a first stitched image; The first stitched image is compared with the panoramic image, and according to the comparison result of the first stitched image and the panoramic image, a preset position is deployed for the local image acquisition device, where the preset position is a posture position required for the local image acquisition device to capture images at a fixed point.

2. The method according to claim 1, characterized in that The comparing the first stitched image with the panoramic image, and deploying a preset position for the local image acquisition device according to a comparison result of the first stitched image with the panoramic image, includes: determining an image similarity between the first stitched image and the panoramic image; The preset position corresponding to the local image acquisition device is determined by combining the image similarity and a plurality of posture positions in the first posture position set.

3. The method according to claim 2, characterized in that The multiple posture positions in the first posture position set are obtained by the local image acquisition device sequentially adjusting the posture positions of the local image acquisition device according to a yaw angle step size, wherein the yaw angle step size is the difference between the first yaw angle and the second yaw angle, the first yaw angle is the yaw angle corresponding to the posture position after the local image acquisition device adjusts the posture position, and the second yaw angle is the yaw angle corresponding to the posture position before the local image acquisition device adjusts the posture position; there are multiple first stitched images, each first stitched image is obtained by stitching together all the local images in the first local image set corresponding to a first posture position set, the multiple first stitched images correspond to multiple first posture position sets, and different first posture position sets correspond to different yaw angle step sizes; The determining of the preset position corresponding to the local image acquisition device by combining the image similarity and the plurality of posture positions in the first posture position set includes: Determining a first stitched image that meets a condition among the plurality of first stitched images, wherein an image similarity between the first stitched image that meets the condition and the panoramic image is greater than a preset threshold; Determine, in the first posture position set that meets the conditions, a first posture position set with the largest yaw angle step length, wherein the first posture position set that meets the conditions is the first posture position set corresponding to the first stitched image that meets the conditions; A plurality of posture positions in the first posture position set with the largest yaw angle step length are determined as preset positions corresponding to the local image acquisition device.

4. The method according to claim 2, characterized in that The multiple posture positions in the first posture position set are obtained by the local image acquisition device sequentially adjusting the posture positions of the local image acquisition device according to a yaw angle step size, wherein the yaw angle step size is a difference between a first yaw angle and a second yaw angle, the first yaw angle being the yaw angle corresponding to the posture position after the local image acquisition device adjusts the posture position, and the second yaw angle being the yaw angle corresponding to the posture position before the local image acquisition device adjusts the posture position; The determining of the preset position corresponding to the local image acquisition device by combining the image similarity and the plurality of posture positions in the first posture position set includes: When the image similarity is less than or equal to a preset threshold, reducing the yaw angle step size, and performing the step of acquiring the first partial image set until the image similarity is greater than the preset threshold; When the image similarity is greater than the preset threshold, a plurality of posture positions in the first posture position set are determined as preset positions corresponding to the local image acquisition device.

5. The method according to claim 2, characterized in that The determining the image similarity between the first stitched image and the panoramic image includes: determining, based on the first stitched image and the panoramic image, a plurality of groups of matching feature points, each group of matching feature points including a stitching feature point and a panoramic feature point matching the stitching feature point, the stitching feature point being a feature point in the first stitched image, and the panoramic feature point being a feature point in the panoramic image; An image similarity between the first stitched image and the panoramic image is determined based on the multiple groups of matching feature points.

6. The method according to claim 5, characterized in that The determining, based on the multiple groups of matching feature points, the image similarity between the first stitched image and the panoramic image includes: Determining, from the multiple groups of matching feature points, four target stitching feature points and four target panoramic feature points, the four target stitching feature points being stitching feature points closest to four image boundaries of the first stitched image, and the four target panoramic feature points being panoramic feature points that match the four target stitching feature points; In the first stitched image, intercepting the image area corresponding to the four target stitching feature points as a first sub-image; In the panoramic image, intercepting the image area corresponding to the four target panoramic feature points as a second sub-image; adjusting the size of the second sub-image to be the same as the size of the first sub-image, to obtain a comparison image of the first sub-image; A similarity between the comparison image and the first sub-image is calculated as an image similarity between the first stitched image and the panoramic image.

7. The method according to any one of claims 1 to 6, characterized in that The plurality of posture positions in the first posture position set all correspond to a first pitch angle; The method further comprises: Acquire a second partial image set, the second partial image set including a plurality of partial images, the plurality of partial images in the second partial image set being partial images acquired by the partial image acquisition device at a plurality of posture positions in a second posture position set, different posture positions in the second posture position set corresponding to different yaw angles, the plurality of posture positions in the second posture position set all corresponding to a second pitch angle, and the second pitch angle being different from the first pitch angle; stitching all the partial images in the second partial image set to obtain a second stitched image; The second stitched image is compared with the panoramic image, and a preset position is arranged for the local image acquisition device according to a comparison result between the second stitched image and the panoramic image.

8. The method according to any one of claims 1 to 6, characterized in that The space contains a preset object to be detected, and the preset object to be detected is located at a position in the space farthest from the local image acquisition device; Before acquiring the first partial image set, the method further includes: Acquire a sample local image, where the sample local image is a local image of the object to be detected acquired by the local image acquisition device at a sample magnification; In the case that the object to be detected in the sample partial image does not meet the detection requirements, increasing the sample magnification, and performing the step of acquiring the sample partial image until the object to be detected in the sample partial image meets the detection requirements; The sample magnification when the object to be detected in the sample partial image meets the detection requirement is set as the maximum magnification of the partial image acquisition device during the partial image acquisition process.

9. A computer device, characterized in that: The computer device comprises a memory and a processor, wherein the memory is connected to the processor, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the computer device executes the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions. When the program instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 8.

11. A pre-position deployment system, characterized in that: The system comprises an acquisition device management device, a panoramic image acquisition device, and a local image acquisition device, wherein the acquisition device management device is connected to the panoramic image acquisition device and the local image acquisition device respectively, the panoramic image acquisition device is used to acquire a panoramic image of a space, and the local image acquisition device is used to acquire a local image of the space; The collection device management equipment is used to execute the method according to any one of claims 1-8.

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