Parameter determination methods, image correction, apparatus, media, and projection equipment

Abstract

This disclosure relates to a parameter determination method, a correction image, an apparatus, a medium, and a projection device. The method involves acquiring a captured image of the projection area when the projection device projects a correction image onto the projection area. The correction image includes multiple feature images, each feature image including a first sub-feature image and a second sub-feature image. The first image and the second image are extracted from the captured image. Then, based on the first image and the second image, a perspective transformation matrix between the projected image and the modulation plane of the projection device is obtained. The perspective transformation matrix between the captured image and the modulation plane of the projection device can be accurately obtained by using first sub-feature images and second sub-feature images with different effects.

Description

Technical Field

[0001] This disclosure relates to the field of projection technology, and more specifically, to a parameter determination method, a correction image, an apparatus, a medium, and a projection device. Background Technology

[0002] In projection equipment, the perspective transformation matrix between the projection area and the modulation plane of the projection equipment can be used for keystone correction of the projected image, camera calibration on the projection equipment, and focus optimization, among other things. Therefore, determining an accurate perspective transformation matrix is ​​extremely important. However, existing methods for determining parameters are easily affected by the projection environment, especially in complex projection environments, where it is impossible to determine an accurate perspective transformation matrix. Summary of the Invention

[0003] This disclosure provides a parameter determination method, a correction image, an apparatus, a medium, and a projection device, which can accurately determine the perspective transformation matrix between the projected image and the modulation plane of the projection device.

[0004] Firstly, this disclosure relates to a parameter determination method, including:

[0005] The captured image is obtained by taking a picture of the projection area when the projection device projects the correction image onto the projection area. The correction image includes multiple feature images, including a first sub-feature image and a second sub-feature image, and the first sub-feature image overlaps with the second sub-feature image.

[0006] A first image and a second image are extracted from the captured image. The first image includes a first sub-feature image extracted from the captured image, and the second image includes a second sub-feature image extracted from the captured image.

[0007] Based on the first image and / or the second image, obtain the perspective transformation matrix between the projected image and the modulation plane of the projection device.

[0008] Secondly, this disclosure relates to a corrected image, including multiple feature images, wherein the feature images include a first sub-feature image and a second sub-feature image, and the first sub-feature image overlaps with the second sub-feature image.

[0009] Thirdly, this disclosure relates to a parameter determining device, comprising:

[0010] The acquisition module is configured to acquire captured images. The captured images are obtained by capturing images of the projection area when the projection device projects the correction image onto the projection area. The correction image includes multiple feature images, including a first sub-feature image and a second sub-feature image, and the first sub-feature image overlaps with the second sub-feature image.

[0011] The extraction module is configured to extract a first image and a second image from the captured image, wherein the first image includes a first sub-feature image extracted from the captured image, and the second image includes a second sub-feature image extracted from the captured image;

[0012] The acquisition module is configured to obtain a perspective transformation matrix between the captured image and the modulation plane of the projection device based on the first image and / or the second image.

[0013] Fourthly, this disclosure relates to a computer storage medium having a computer program stored thereon, which, when executed by a processing device, implements the steps of the method described in the first aspect.

[0014] Fifthly, this disclosure relates to a projection device, comprising:

[0015] A storage device on which computer programs are stored;

[0016] A processing device for executing the computer program in the storage device to implement the steps of the method described in the first aspect.

[0017] This disclosure relates to a parameter determination method, a correction image, an apparatus, a medium, and a projection device. The method involves acquiring a captured image of the projection area when the correction image is projected onto the projection area by the projection device. This correction image includes multiple feature images, each comprising a first sub-feature image and a second sub-feature image. The first and second images are extracted from the captured image. Then, based on the first and second images, a perspective transformation matrix between the projected image and the modulation plane of the projection device is obtained. The perspective transformation matrix between the captured image and the modulation plane of the projection device can be accurately calculated using first and second sub-feature images with different effects. Even when the projection angle of the projection device relative to the projection area is large and / or the projected image is obstructed, the perspective transformation matrix between the captured image and the modulation plane of the projection device can still be accurately determined. Attached Figure Description

[0018] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale. In the drawings:

[0019] Figure 1 This is a flowchart illustrating a parameter determination method according to some embodiments.

[0020] Figure 2This is a schematic diagram of a feature image shown according to some embodiments.

[0021] Figure 3 This is a schematic diagram of a corrected image shown according to some embodiments.

[0022] Figure 4 These are schematic diagrams of the first and second images shown according to some embodiments.

[0023] Figure 5 yes Figure 1 The detailed flowchart of step 130 is shown.

[0024] Figure 6 yes Figure 5 The detailed flowchart of step 132 is shown.

[0025] Figure 7 This is a flowchart illustrating a parameter determination method according to other embodiments.

[0026] Figure 8 This is a schematic diagram of the module connections of a parameter determining device according to some embodiments.

[0027] Figure 9 This is a schematic diagram of the structure of a projection device 200 in one embodiment. Detailed Implementation

[0028] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0029] It should be understood that the various steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0030] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0031] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0032] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0033] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0034] Figure 1 This is a flowchart illustrating a parameter determination method according to some embodiments. For example... Figure 1 As shown, this disclosure provides a parameter determination method, which can be executed by a projection device, specifically by a parameter determination device. This device can be implemented in software and / or hardware and configured within the projection device. Figure 1 As shown, the method may include the following steps.

[0035] In step 110, an image is acquired, wherein the image is captured by taking a picture of the projection area when the projection device projects the correction image onto the projection area. The correction image includes multiple feature images, including a first sub-feature image and a second sub-feature image, and the first sub-feature image overlaps with the second sub-feature image.

[0036] Here, the projection area refers to the area used to support the projected image. The projection area can be a wall, a screen, etc. The calibration image is an image used to detect the perspective transformation matrix of the projected image projected onto the projection area and the corresponding image on the modulation plane of the projection device. This calibration image includes multiple feature images.

[0037] Figure 2 This is a schematic diagram of feature images shown according to some embodiments. For example... Figure 2 As shown, feature image 20 includes a first sub-feature image 21 and a second sub-feature image 22. Figure 2 As shown, the bottom layer of feature image 20 is the first sub-feature image 21, and the second sub-feature image 22 is set within the image range of the first sub-feature image 21, and the second sub-feature image 22 is superimposed on the first sub-feature image 21. For example, the center point of the second sub-feature image 22 may coincide with the center point of the first sub-feature image 21.

[0038] It should be understood that the second sub-feature image 22 may have a white box 23 to clearly distinguish the second sub-feature image 22 from the first sub-feature image 21 in the feature image 20. The size of the white box 23 can be set according to the actual use. Of course, the second sub-feature image 22 and the first sub-feature image 21 in the feature image 20 can also be distinguished by different colors, in which case the aforementioned white box 23 does not need to be set in the second sub-feature image 22.

[0039] like Figure 2 As shown, the first sub-feature image 21 can be a dot image, and the second sub-feature image 22 can be an identifier code that serves as a unique identifier. For example, the identifier code can be an Aruco identifier code (a type of tag used in augmented reality). Of course, in other embodiments, the first sub-feature image 21 can also be a square image, and the second sub-feature image 22 can also be an AprilTags code (a two-dimensional barcode used for reference marking).

[0040] It should be understood that in the embodiments of this disclosure, both the first sub-feature image and the second sub-feature image can be used to calculate the perspective transformation matrix, but the accuracy provided by the first sub-feature image and the second sub-feature image differs under different usage conditions. For example, when the first sub-feature image is a dot image and the second sub-feature image is an Aruco identifier, the dot image can provide accurate projection image positioning capability when the projection angle of the projection device relative to the projection area is too large. The Aruco identifier can provide information such as the direction and attitude of the projection image, but when the projection angle of the projection device is too large, part of the Aruco identifier will be lost, resulting in projection image positioning failure. Therefore, the feature image including the first sub-feature image and the second sub-feature image provided in the embodiments of this disclosure is actually an image with image positioning capabilities of at least two types of images. For example, when the first sub-feature image is a dot image and the second sub-feature image is an Aruco identifier, the feature image simultaneously has the anti-occlusion capability and anti-tilt angle capability of the dot image, and has the ability of the Aruco identifier to provide more information (attitude and direction).

[0041] For example, when the second sub-feature image is an Aruco identifier, this Aruco identifier can use a 6x6 dictionary, meaning the irregular square area in the middle of the Aruco identifier occupies a total of 36 pixels (6x6). Of course, the Aruco identifier can also use a 4x4 or 5x5 dictionary. The difference between using different dictionaries is that the fewer pixels an Aruco identifier has, the less data it carries, but the stronger its resistance to interference. Therefore, the Aruco identifier can be designed according to actual usage.

[0042] Figure 3 This is a schematic diagram of a corrected image shown according to some embodiments. For example... Figure 3 As shown, the corrected image 300 includes multiple feature images 20, which are arranged in an array within the corrected image 300. Of course, in other embodiments, the corrected image 300 may also include dot images, with the multiple feature images 20 and the dot images arranged in a rectangular array within the corrected image 300. It should be understood that the multiple feature images 20 and the dot images can be arranged in other array forms besides rectangular arrays, such as circular arrays, ring arrays, etc.

[0043] When a corrected image, which includes multiple feature images, is projected onto a projection area by a projection device, an image of that projection area is captured.

[0044] For example, the image can be obtained by taking a picture of the projection area using a camera device mounted on the projection device.

[0045] In step 120, a first image and a second image are extracted from the captured image, wherein the first image includes a first sub-feature image extracted from the captured image, and the second image includes a second sub-feature image extracted from the captured image.

[0046] Here, the captured image includes the projected image of the corrected image onto the projection area. Therefore, a first image and a second image can be extracted from the captured image. The first image includes all the first sub-feature images extracted from the captured image, and the second image includes all the second sub-feature images extracted from the captured image.

[0047] For example, morphological processing can be performed on the captured image to remove the second sub-feature image from the captured image, obtaining a first image that only includes the first sub-feature image, and then the captured image and the first image can be subtracted to obtain a second image that only includes the second sub-feature image.

[0048] It should be understood that by separating the first and second sub-feature images in the captured image, all first and second sub-feature images can be prevented from interfering with each other, ensuring that all first and second sub-feature images can be detected. For example, if the first sub-feature image is a dot image and the second sub-feature image is an Aruco identifier, failing to separate the dot image from the Aruco identifier image would result in the hollow dot image being undetectable, while the Aruco identifier would be interfered with by the dot image.

[0049] Figure 4These are schematic diagrams of the first and second images shown according to some embodiments. For example... Figure 4 As shown, a first image 401 and a second image 402 are extracted from the captured image 400. It should be understood that the image size, shape, and other image attributes of the first image 401 and the second image 402 remain unchanged relative to the captured image 400. However, when the projection device projects at an angle relative to the projection area, the shapes of the first sub-feature image in the first image 401 and the second sub-feature image in the second image 402 may be distorted.

[0050] In step 130, a perspective transformation matrix between the captured image and the modulation plane of the projection device is obtained based on the first image and / or the second image.

[0051] Here, after obtaining the first image and the second image, the perspective transformation matrix between the captured image and the modulation plane of the projection device can be determined based on the first image and / or the second image.

[0052] For example, taking a dot image as the first sub-feature image and an Aruco identifier as the second sub-feature image, since the Aruco identifier has strong anti-occlusion capabilities, when part of the dot image is obscured due to partial obstruction of the projected image, the perspective transformation matrix can be determined based on the second image. Conversely, since the dot image has strong anti-tilt capabilities, when part of the Aruco identifier cannot be detected due to a large projection angle between the projector and the projection area, the perspective transformation matrix can be determined based on the first image. Alternatively, a first perspective transformation matrix can be determined based on the first image, and a second perspective transformation matrix can be determined based on the second image. Then, the perspective transformation matrix between the projected image and the modulation plane of the projector can be determined based on the comparison between the first and second perspective transformation matrices.

[0053] It is worth noting that the principle of how to determine the perspective transformation matrix based on the first image and / or the second image will be explained in detail in subsequent embodiments.

[0054] In this context, the modulation plane refers to the plane on which the light modulator (chip) of the projection device generates the image. Chips corresponding to the modulation plane include reflective image modulation chips and transmissive image modulation chips. Reflective image modulation chips include DMD chips (Digital Micromirror Device) or LCOS chips (Liquid Crystal on Silicon), while transmissive image modulation chips include LCD chips (Liquid Crystal Display).

[0055] The perspective transformation matrix between the projected image and the modulation plane of the projection device reflects the positional changes of the pixels in the modulation plane mapped onto the captured image. It should be understood that this perspective transformation matrix can also be called the homography matrix.

[0056] In some embodiments, the perspective transformation matrix determined by the present disclosure can be used for trapezoidal correction of the projected image. For example, trapezoidal correction is performed on the image projected by the projection device according to the perspective transformation matrix so that the projected image on the projection area appears as a rectangle in the user's vision. In other embodiments, the perspective transformation matrix determined by the present disclosure can be used to calibrate the shooting device installed on the projection device. For example, the camera matrix and distortion coefficient of the shooting device are determined according to the perspective transformation matrix. In still other embodiments, the perspective transformation matrix determined by the present disclosure can also be used to calculate the sharpness of the projected image. In summary, the perspective transformation matrix calculated by the embodiments of the present disclosure can be used as needed in all scenarios where a perspective transformation matrix needs to be calculated, including but not limited to scenarios such as trapezoidal correction of the projected image, focusing of the projection device, alignment of the projected image with the screen, camera parameter correction, and automatic obstacle avoidance by the projection device.

[0057] Therefore, by acquiring a captured image of the projection area when the projection device projects a corrected image onto the projection area, and this corrected image includes multiple feature images, each of which includes a first sub-feature image and a second sub-feature image, and by extracting the first and second images from the captured image, and then obtaining the perspective transformation matrix between the projected image and the modulation plane of the projection device based on the first and second images, the perspective transformation matrix between the captured image and the modulation plane of the projection device can be accurately calculated using first and second sub-feature images with different effects. Even when the projection angle of the projection device relative to the projection area is large and / or the projected image is obstructed, the perspective transformation matrix between the captured image and the modulation plane of the projection device can still be accurately determined.

[0058] Figure 5 yes Figure 1 The detailed flowchart for step 130 is shown below. Figure 5 As shown, in some possible implementations, step 130 may include the following steps.

[0059] In step 131, the projection scene type corresponding to the projection device is determined based on the first image and / or the second image.

[0060] Here, the projection scene type corresponding to the projection device can refer to the type of projection environment in which the projection device is located. For example, the projection scene type can be used to indicate the projection angle of the projection device relative to the projection area, and / or to indicate whether there is any obstruction in the projected image.

[0061] In some embodiments, the projection angle of the projection device relative to the projection area and / or the occlusion of the projected image projected by the projection device can be determined based on the first image and / or the second image, and the projection scene type can be determined based on the projection angle and / or the occlusion.

[0062] The projection angle between the projection device and the projection area refers to the angle between the optical axis of the projection device and the projection area. For example, when the projection device projects onto the projection area in orthographic projection mode, the optical axis of the projection device is perpendicular to the projection area, and the projection angle is 90°. The occlusion of the projected image refers to whether there is any obstruction in the projected image.

[0063] For example, if the second image is an Aruco identifier, and a portion of the Aruco identifier in the second image is not detected, it indicates that the portion of the Aruco identifier is obscured, or that the projection angle of the projection device relative to the projection area is too large, causing that portion of the Aruco identifier to be undetectable. If the first image is a dot image, the projection angle can be determined based on the distortion of the dot image in the first image. Furthermore, if a portion of the dot image in the second image is undetectable, it indicates that the projected image is obstructed, thus causing that portion of the dot image to be undetectable.

[0064] Therefore, based on the projection angle and / or occlusion, the projection scene type corresponding to the projection device can be accurately determined, and different strategies can be used to calculate the perspective transformation matrix for different projection scene types.

[0065] It is worth noting that determining the projection angle and / or occlusion based on the first image and / or the second image can be achieved through image recognition of the first image and / or the second image. For example, the first image and / or the second image can be input into a trained neural network model to obtain the corresponding projection scene type.

[0066] In step 132, the perspective transformation matrix is ​​determined according to the projection scene type.

[0067] Here, for different projection scene types, different strategies can be used to determine the perspective transformation matrix between the projected image and the modulation plane of the projection device. It should be understood that the specific implementation methods for calculating the perspective transformation matrix for different projection scene types will be described in detail in subsequent embodiments.

[0068] Therefore, by using a strategy that matches the projection scene type to determine the perspective transformation matrix for different projection scene types, different strategies can be used to calculate the perspective transformation matrix for different usage scenarios. Even when the projection angle of the projection device relative to the projection area is large and / or the projection image is obstructed, the perspective transformation matrix between the captured image and the modulation plane of the projection device can still be accurately determined.

[0069] For example, the projection scene types corresponding to the projection device include a first scene type, a second scene type, and a third scene type.

[0070] The first scene type indicates that the projection angle of the projector relative to the projection area is greater than or equal to a preset angle threshold, and the projected image is obstructed; for example, the projector projects at a large angle and there are obstacles in the projection light path. The second scene type indicates that the projection angle of the projector relative to the projection area is less than the preset angle threshold. The third scene type indicates that the projection angle of the projector relative to the projection area is greater than or equal to the preset angle threshold, and the projected image is not obstructed.

[0071] In some feasible implementations, feature images are provided for multiple target regions of the corrected image. These multiple target regions may be the four diagonal regions of the corrected image. For example... Figure 3 As shown, each of the four diagonal regions of the corrected image 300 contains six feature images 20.

[0072] Accordingly, in some embodiments, if at least one target region in the multiple target regions of the second image does not include the second sub-feature image, and the number of targets in the first sub-feature image determined according to the first image is less than a preset number threshold, the projection scene type of the projection device is determined to be the first scene type.

[0073] Here, the multiple target regions of the second image correspond one-to-one with the multiple target regions of the corrected image. Taking the Aruco identifier as the second sub-feature image as an example, if at least one target region in the second image does not include the second sub-feature image, it indicates that the projection angle of the projection device relative to the projection area is greater than or equal to a preset angle threshold. At this time, it can be further determined whether there is occlusion in the projected image based on the first image. If the number of targets belonging to the first sub-feature image determined based on the first image is less than a preset number threshold, it indicates that there is occlusion in the projected image. Accordingly, the projection scene type of the projection device can be determined as the first scene type.

[0074] It should be understood that the number of targets in the first sub-feature image can refer to the number of outer contours corresponding to the first sub-feature image. The outer contours corresponding to the first sub-feature image can be the original shape of the first sub-feature image. Of course, due to possible distortion in the projected image, the outer contours corresponding to the first sub-feature image can also be deformed. For example, taking a dotted image as the first sub-feature image, the outer contours corresponding to the first sub-feature image can be circular or elliptical.

[0075] For example, the circumscribed contour of the first sub-feature image in the first image can be extracted to obtain the target number of the outer contour corresponding to the first sub-feature image. It should be understood that the preset number threshold can refer to the number of the first sub-feature images included in the corrected image. Figure 3 As shown, the corrected image 300 includes 24 first sub-feature images, which are the first sub-feature images in the 24 feature images 20, so the number of targets is 24.

[0076] In other embodiments, when multiple target regions of the second image include the second sub-feature image, the projection scene type of the projection device is determined to be the second scene type.

[0077] Here, multiple target regions of the second image all include the second sub-feature image, indicating that the projection angle of the projection device relative to the projection region is less than a preset angle threshold, so that the second sub-feature image can be detected in each target region.

[0078] Therefore, when multiple target regions of the second image include the second sub-feature image, it can be determined that the projection angle of the projection device relative to the projection region is less than a preset angle threshold, thereby determining that the projection scene type corresponding to the projection device is the second scene type.

[0079] In some other embodiments, if at least one target region in the second image does not include the second sub-feature image, and the number of targets in the first sub-feature image determined from the first image is equal to a preset number threshold, the projection scene type corresponding to the projection device is determined to be the third scene type.

[0080] Here, if at least one target region in the second image does not include the second sub-feature image, it indicates that the projection angle of the projection device relative to the projection area is greater than or equal to a preset angle threshold. In this case, the presence of occlusion in the projected image can be further determined based on the first image. If the number of targets in the first sub-feature image equals a preset number threshold, it indicates that there is no occlusion in the projected image. Accordingly, the projection scene type corresponding to the projection device can be determined to be the third scene type.

[0081] It is worth noting that the number of targets in the first sub-feature image can refer to the number of targets in the outer contour corresponding to the first sub-feature image. The definitions of the number of targets in the outer contour corresponding to the first sub-feature image and the preset number threshold can be found in the relevant descriptions of the above implementation methods, and will not be repeated here.

[0082] Figure 6 yes Figure 5 The detailed flowchart for step 132 is shown below. Figure 6 As shown, in some possible implementations, step 132 may include the following steps.

[0083] In step 1321, when the projection scene type is the first scene type, image transformation parameters are obtained based on the first image, wherein the image transformation parameters are used to make the contour shape of each first sub-feature image in the first image after adjustment by the image transformation parameters consistent with the contour shape of the first sub-feature image in the corrected image.

[0084] Here, if the projection scene type is the first scene type, it indicates that the projected image is occluded, causing some of the first sub-feature images to be undetectable. In this case, it is necessary to determine the perspective transformation matrix based on the second image. However, since some of the second sub-feature images in the second image are also undetectable, the image transformation parameters can be obtained from the first image to correct the second image.

[0085] It is worth noting that the image transformation parameters are used to ensure that the contour shape of each first sub-feature image in the first image after adjustment matches the contour shape of the first sub-feature image in the corrected image. In other words, the image transformation parameters are used to restore the distorted first sub-feature image in the first image to its original shape in the corrected image. Taking a dotted image as an example, the dotted image in the first image can be stretched along its major or minor axis, restoring the contour shape of the stretched dotted image to a circle. The parameters of this stretching transformation are the image transformation parameters.

[0086] In step 1322, the second image is adjusted based on the image transformation parameters to obtain the adjusted second image.

[0087] Here, in obtaining image transformation parameters, the second image can be adjusted using the image transformation parameters to obtain the adjusted second image.

[0088] It should be understood that the second image after image transformation parameter adjustment has eliminated the influence of projection angle on the projected image, and the shape of each second sub-feature image in the adjusted second image is consistent with the shape of the second sub-feature image in the corrected image.

[0089] In step 1323, the perspective transformation matrix is ​​determined based on the adjusted second image and the image transformation parameters.

[0090] Here, the initial perspective transformation matrix can be determined based on the adjusted second image, and then the perspective transformation matrix between the captured image and the modulation plane of the projection device can be obtained based on the initial perspective transformation matrix and the image transformation parameters.

[0091] It should be understood that since the adjusted second image is obtained by adjusting the original second image using image transformation parameters, the calculated initial perspective transformation matrix will also be affected by the image transformation parameters. Therefore, by obtaining the perspective transformation matrix between the captured image and the modulation plane of the projection device based on the initial perspective transformation matrix and the image transformation parameters, the final obtained perspective transformation matrix can accurately reflect the spatial variation relationship between the captured image and the modulation plane of the projection device.

[0092] For example, taking the Aruco identifier as an example, the initial perspective transformation matrix is ​​determined based on the adjusted second image. This can be achieved by determining the first coordinate information of the corner points of each Aruco identifier in the second image in the image coordinate system of the captured image, and then obtaining the initial perspective transformation matrix based on the first coordinate information of the corner points of each Aruco identifier and the second coordinate information of the corner points of each Aruco identifier in the calibration image corresponding to the second image in the coordinate system of the modulation plane.

[0093] Therefore, through the above steps 1321 to 1323, when the projection scene type corresponding to the projection device is the first projection scene type (the projection angle is too large and / or the projection screen is obstructed), the second image can be used to determine the perspective transformation matrix, so that the calculated perspective transformation matrix can eliminate environmental interference and make the perspective transformation matrix more accurate.

[0094] In some feasible implementations, when the projection scene type is the second scene type, the perspective transformation matrix can be determined based on the second image.

[0095] Here, when the projection scene type is the second scene type, it means that the projection angle of the projection device relative to the projection area is less than a preset angle threshold, so that the second sub-feature image can be detected in each target area. Accordingly, the perspective transformation matrix can be determined based on the second image.

[0096] In some embodiments, for each second sub-feature image in the second image, the coordinate information corresponding to the corner point of the second sub-feature image can be determined, and the target corner point can be determined based on the coordinate information corresponding to all the obtained corner points. Then, the perspective transformation matrix can be determined based on the coordinate information corresponding to the target corner point.

[0097] The coordinate information corresponding to the corner point refers to the coordinates of the corner point in the image coordinate system corresponding to the second image. It should be understood that since the second image is extracted from the captured image, the coordinate information corresponding to the corner point in the second sub-feature image can also be understood as the coordinates of the corner point in the image coordinate system of the captured image.

[0098] Taking the Aruco identifier as an example, each Aruco identifier can have four corner points. These corner points can be extracted using a detection algorithm provided by OpenCV (an open-source algorithm library for Aruco identifiers). The algorithm returns data including the four corner points of the Aruco identifier and its corresponding identifier number. This identifier number is used to determine the position of the Aruco identifier corresponding to that number on the projected image.

[0099] After calculating the coordinates of the corner points in each of the second sub-feature images, corner points that meet preset conditions can be deleted from all the obtained corner points to obtain the target corner point. These preset conditions may include the area of ​​the second sub-feature image formed by the corner point being greater than a preset area threshold, and the edge containing the corner point not being parallel to the edges of other corresponding second sub-feature images. This preset area threshold can be set according to actual conditions.

[0100] For example, all corner points can be fitted to determine whether a corner point meets a preset condition.

[0101] It should be understood that the corner points of the second sub-feature image are easily affected by the unevenness of the projection area, leading to errors in the coordinate information of the corner points. For example, when the projection area is a screen, the unevenness of the screen can easily cause errors in the coordinate information of the corner points of the second sub-feature image. Therefore, by deleting corner points that meet the preset conditions from all the determined corner points of the second sub-feature image, erroneous corner points caused by the unevenness of the projection area can be eliminated, thereby making the perspective transformation matrix calculated based on the target corner points more accurate.

[0102] It is worth noting that the principle of determining the perspective transformation matrix based on the target corner point can be found in the description of determining the initial perspective transformation matrix based on the adjusted second image in the above embodiment. The principle is the same and will not be repeated here.

[0103] Therefore, when the scene type corresponding to the projection device is the second scene type, the perspective transformation matrix between the captured image and the modulation plane of the projection device can be accurately determined through the second image.

[0104] It should be noted that during the process of determining the initial perspective transformation matrix based on the adjusted second image, corner points that meet the preset conditions can also be deleted from the determined corner points to obtain the target corner point, and then the initial perspective transformation matrix can be determined based on the target corner point.

[0105] In some feasible implementations, when the projection scene type is a third scene type, the perspective transformation matrix can be determined based on the first image.

[0106] Here, the third scene type represents that among the multiple target regions of the second image, at least one target region does not include the second sub-feature image, and the number of targets in the first sub-feature image determined according to the first image is equal to a preset number threshold.

[0107] For example, taking the first sub-feature image as a dot image, the perspective transformation matrix is ​​determined based on the first image. This can be done by determining the coordinate information of the center point of each dot image in the first image in the image coordinate system of the first image, and then obtaining the perspective transformation matrix based on the coordinate information of each center point and the coordinate information of the center point of each dot image in the calibration image corresponding to the first image in the coordinate system of the modulation plane.

[0108] It should be understood that since the first image is extracted from the captured image, the coordinate information of the center point of each dot in the first image in the image coordinate system of the first image is equivalent to the coordinate information of the center point in the image coordinate system of the captured image.

[0109] Therefore, when the projection scene type corresponding to the projection device is the third scene type, the perspective transformation matrix can be determined based on the first image. When the projection angle is greater than or equal to the preset angle threshold, the perspective transformation matrix between the captured image and the modulation plane of the projection device can be accurately determined based on the first image.

[0110] In some feasible implementations, if the number of targets in the first sub-feature image determined based on the first image is greater than a preset number threshold, the first sub-feature image is clustered to obtain a clustering result, and the number of targets is corrected based on the clustering result to obtain a corrected number of targets.

[0111] Here, the definitions of the target number of the first sub-feature image and the preset number threshold can be found in the relevant descriptions of the above implementation methods, and will not be repeated here.

[0112] If the number of targets in the first sub-feature image exceeds a preset threshold, it indicates that there are objects in the projected image that do not belong to the first sub-feature image but have a similar outer contour to the one corresponding to the first sub-feature image. For example, if the first sub-feature image is a dot image, the outer contour corresponding to the first sub-feature image is a circle or an ellipse. The projection of indoor lights onto the projected image will also appear as a circle or an ellipse, thus causing the number of targets corresponding to the outer contour of the detected first sub-feature image to exceed the preset threshold.

[0113] If the number of targets in the first sub-feature image exceeds a preset threshold, it is necessary to exclude outer contours that do not belong to the first sub-feature image from the first image. To do this, the outer contours corresponding to the first sub-feature image are clustered to obtain clustering results. The target number is then corrected based on these clustering results to obtain a corrected target number. The corrected target number is the number of outer contours in the first image that truly belong to the first sub-feature image.

[0114] For example, based on the target parameters corresponding to the outer contour, a clustering algorithm can be used to cluster the outer contour of the first sub-feature image extracted from the first image to obtain the clustering result. The target parameters can be the major axis length, minor axis length, center point coordinates, and the average pixel value of the first sub-feature image in the first image, etc.

[0115] It should be understood that, taking clustering by major axis length as an example, if the clustering result includes multiple clusters with different major axis length ranges, then the outer contours corresponding to the clusters that meet the conditions can be deleted to obtain the corrected target number. These clusters that meet the conditions can be clusters that are not within the preset major axis length range.

[0116] Therefore, by correcting the number of targets, the influence of the projection environment on the first image can be eliminated to obtain an accurate first image, thereby obtaining an accurate perspective transformation matrix between the captured image and the modulation plane of the projection device.

[0117] It is worth noting that the corrected target number can be further used to determine the projection scene type corresponding to the projection device. That is, the corrected target number is compared with a preset number threshold.

[0118] In some feasible implementations, if at least one target region in the multiple target regions of the adjusted second image does not include the second sub-feature image, an action for adjusting the placement of the projection device is performed.

[0119] Here, after obtaining the adjusted second image, the adjusted second image is detected. If at least one target region in the multiple target regions of the adjusted second image does not include the second sub-feature image, then an action to adjust the placement of the projection device is performed.

[0120] The action of adjusting the placement of the projection device can involve outputting a first prompt message to the user, prompting them to adjust the device's position. The projection device or a mobile terminal associated with it can be controlled to output this first prompt message to alert the user that there is an obstruction in front of the projection device, allowing the user to adjust the device's placement accordingly and avoid the obstacle. It is worth noting that the first prompt message can be output in various forms, such as text, voice, or images.

[0121] Of course, the action used to adjust the placement of the projection equipment can also be to control the pan-tilt unit used to mount the projection equipment to move.

[0122] It should be understood that the adjusted second image has effectively eliminated the influence of the projection angle on the captured image. If at least one target region in the adjusted second image does not include the second sub-feature image, it indicates that the projected image is obstructed, resulting in a missing portion of the second sub-feature image in the captured image. In this case, it is necessary to adjust the placement of the projection device to prevent obstruction of the projected image. Therefore, the projection device can be controlled to perform actions to adjust its placement.

[0123] Therefore, by performing actions to adjust the placement of the projection device, its position can be adjusted in a timely manner, thus improving the user experience.

[0124] In some feasible implementations, if the corrected target number is greater than a preset number threshold, an action is performed to adjust the projection angle of the projection device.

[0125] Here, after obtaining the corrected target number, the corrected target number is compared with the preset number threshold again. If the corrected target number is greater than the preset number threshold, an action to adjust the projection angle of the projection device is executed.

[0126] The corrected number of targets has actually eliminated the outer contours that do not belong to the first sub-feature image. If the corrected number of targets is greater than the preset number threshold, it means that the tilt angle of the projection device relative to the projection area is too large, causing the first sub-feature image to stick together. At this time, an action to adjust the projection angle of the projection device can be performed.

[0127] The action of adjusting the projection angle of the projection device can be performed by outputting a second prompt message to the user, prompting them to adjust the projection angle. For example, the projection device or a mobile terminal associated with the projection device can be controlled to output the second prompt message to indicate to the user that the tilt angle of the projection device is too large, so that the user can adjust the placement angle of the projection device according to the second prompt message. It is worth noting that the second prompt message can be output in various forms such as text, voice, and images.

[0128] Of course, performing actions to adjust the projection angle of the projection device can also control the pan-tilt unit used to mount the projection device to rotate, thereby adjusting the projection angle of the projection device.

[0129] Therefore, by performing actions to adjust the projection angle of the projection device, the placement angle of the projection device can be adjusted in a timely manner, thus improving the user experience of the projection device.

[0130] It should be understood that if the corrected number of targets equals the preset threshold, the perspective transformation matrix can be calculated based on the first image. If the corrected number of targets is less than the preset threshold, the image transformation parameters are obtained based on the first image.

[0131] Figure 7 This is a flowchart illustrating a parameter determination method according to other embodiments. For example... Figure 7 As shown in the embodiments of this disclosure, a parameter determination method is provided, which includes the following steps:

[0132] S701, acquire captured images;

[0133] S702, extracts the first image and the second image from the captured image;

[0134] S703, Does each target region of the second image have a second sub-feature image? If each target region of the second image has a second sub-feature image, then proceed to step S708. If at least one target region of the second image does not have a second sub-feature image, then proceed to step S704.

[0135] S704, whether the number of targets on the outer contour corresponding to the first sub-feature image is less than a preset number threshold; if the number of targets is less than the preset number threshold, then proceed to step S705; if the number of targets is greater than the preset number threshold, then proceed to step S710; if the number of targets is equal to the preset number threshold, then proceed to step S709.

[0136] S705, Obtain image transformation parameters based on the first image;

[0137] S706, Adjust the second image based on the image transformation parameters to obtain the adjusted second image;

[0138] S707, Determine the perspective transformation matrix based on the adjusted second image and the image transformation parameters;

[0139] S708, Determine the perspective transformation matrix based on the second image;

[0140] S709, the target quantity is equal to the preset quantity threshold, and the perspective transformation matrix is ​​determined based on the first image;

[0141] S710 If the number of targets is greater than the preset number threshold, then cluster the outer contour corresponding to the first sub-feature image to obtain the clustering result;

[0142] S711, adjust the target quantity based on the clustering results to obtain the adjusted target quantity.

[0143] It is worth noting that for a detailed explanation of steps S701 to S711 above, please refer to the relevant descriptions in the above embodiments, and will not be repeated here.

[0144] According to an embodiment of this disclosure, a correction image is provided, which includes a plurality of feature images, the feature images including a first sub-feature image and a second sub-feature image, and the first sub-feature image and the second sub-feature image overlap.

[0145] Optionally, the first sub-feature image is a dot image, and the second sub-feature image is an identifier code.

[0146] It is worth noting that for a detailed description of the correction image, please refer to the relevant description of the correction image in the above embodiments, which will not be repeated here.

[0147] Figure 8 This is a schematic diagram illustrating the module connections of a parameter determining device according to some embodiments. For example... Figure 8 As shown, this disclosure provides a parameter determination device 800, which includes:

[0148] The acquisition module 801 is configured to acquire a captured image. The captured image is obtained by capturing the projection area when the projection device projects the correction image onto the projection area. The correction image includes multiple feature images, including a first sub-feature image and a second sub-feature image, and the first sub-feature image overlaps with the second sub-feature image.

[0149] The extraction module 802 is configured to extract a first image and a second image from the captured image, wherein the first image includes a first sub-feature image extracted from the captured image, and the second image includes a second sub-feature image extracted from the captured image;

[0150] The acquisition module 803 is configured to obtain a perspective transformation matrix between the captured image and the modulation plane of the projection device based on the first image and / or the second image.

[0151] Optionally, obtaining module 803 includes:

[0152] The first determining unit is configured to determine the projection scene type corresponding to the projection device based on the first image and / or the second image;

[0153] The second determining unit is configured to determine the perspective transformation matrix based on the projection scene type.

[0154] Optionally, the first determining unit is specifically configured as follows:

[0155] Based on the first image and / or the second image, determine the projection angle of the projection device relative to the projection area and / or the occlusion of the projected image projected by the projection device;

[0156] Determine the projection scene type based on the projection angle and / or occlusion.

[0157] Optionally, the second determining unit is specifically configured as follows:

[0158] When the projection scene type is the first scene type, image transformation parameters are obtained based on the first image, wherein the image transformation parameters are used to make the contour shape of each first sub-feature image in the first image after adjustment by the image transformation parameters consistent with the contour shape of the first sub-feature image in the corrected image.

[0159] The second image is adjusted based on the image transformation parameters to obtain the adjusted second image;

[0160] Determine the perspective transformation matrix based on the adjusted second image and the image transformation parameters;

[0161] The first scene type is characterized by a projection angle of the projection device relative to the projection area that is greater than or equal to a preset angle threshold, and the projected image projected by the projection device is obstructed.

[0162] Optionally, multiple target regions of the corrected image are provided with feature images, and the first determining unit is specifically configured as follows:

[0163] If at least one target region in the second image does not include the second sub-feature image, and the number of targets in the first sub-feature image determined from the first image is less than a preset number threshold, the projection scene type of the projection device is determined to be the first scene type.

[0164] Optionally, the second determining unit is specifically configured as follows:

[0165] When the projection scene type is the second scene type, the perspective transformation matrix is ​​determined based on the second image, where the second scene type indicates that the projection angle of the projection device relative to the projection area is less than a preset angle threshold.

[0166] Optionally, the second determining unit is specifically configured as follows:

[0167] For each second sub-feature image in the second image, determine the coordinate information corresponding to the corner points of the second sub-feature image;

[0168] Based on the coordinate information of all obtained corner points, determine the target corner point;

[0169] Determine the perspective transformation matrix based on the coordinate information corresponding to the target corner point.

[0170] Optionally, the second determining unit is specifically configured as follows:

[0171] When the projection scene type is the third scene type, the perspective transformation matrix is ​​determined based on the first image, wherein the third scene type indicates that the projection angle of the projection device relative to the projection area is greater than or equal to a preset angle threshold, and the projected image projected by the projection device is not obstructed.

[0172] Optionally, the device 800 further includes:

[0173] The clustering module is configured to cluster the first sub-feature image if the number of targets in the first sub-feature image determined based on the first image is greater than a preset number threshold, and obtain the clustering result.

[0174] The correction module is configured to correct the target quantity based on the clustering results to obtain the corrected target quantity.

[0175] Optionally, the first sub-feature image is a dot image, and the second sub-feature image is an identifier code.

[0176] The methods for executing each functional module in the aforementioned device 800 have been described in detail in the section on methods, and will not be repeated here.

[0177] According to an embodiment of this disclosure, a computer storage medium is provided, on which a computer program is stored, which, when executed by a processing device, implements the steps of the parameter determination method provided in the above embodiments.

[0178] The aforementioned computer storage medium may be included in the aforementioned projection device; or it may exist independently and not be assembled into the projection device.

[0179] The aforementioned computer storage medium carries one or more programs. When the aforementioned one or more programs are executed by the projection device, the projection device causes the projection device to: acquire a captured image, wherein the captured image is obtained by capturing a picture of the projection area when the projection device projects a correction image onto the projection area, the correction image includes multiple feature images, the feature images include a first sub-feature image and a second sub-feature image, and the first sub-feature image overlaps with the second sub-feature image; extract a first image and a second image from the captured image, the first image including the first sub-feature image extracted from the captured image, and the second image including the second sub-feature image extracted from the captured image; and obtain a perspective transformation matrix between the projected image and the modulation plane of the projection device based on the first image and / or the second image.

[0180] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the projection device or user's computer, partially on the projection device or user's computer, as a standalone software package, partially on the projection device or user's computer or partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0181] According to embodiments of this disclosure, a projection device is also provided, comprising:

[0182] A storage device on which computer programs are stored;

[0183] A processing device is configured to execute the computer program in the storage device to implement the steps of the method described in any of the above embodiments.

[0184] Figure 9 This is a schematic diagram of the structure of a projection device 200 in one embodiment. For example... Figure 9 As shown, the projection device 200 includes a projection unit 210 and a drive unit 220 for driving the projection unit 210. The projection unit 210 can form an optical image and project the optical image onto the imaging medium SC.

[0185] The projection unit 210 includes a light source unit 211, a light modulator 212, and an optical system 213. The driving unit 220 includes a light source driving unit 221 and a light modulator driving unit 222.

[0186] The light source unit 211 may include solid-state light sources such as light-emitting diodes (LEDs), lasers, and pump lamps. The light source unit 211 may include optical elements such as lenses and polarizers for improving the optical characteristics of the projected light, as well as dimming elements for adjusting the luminous flux.

[0187] The light source driving unit 221 can control the operation of the light source in the light source unit 211, including turning it on and off, according to the instructions of the control unit 250.

[0188] The light modulator 212 includes a display panel 215, which can be a transmissive liquid crystal display (LCD), a reflective liquid crystal on silicon (LCOS), or a digital micromirror device (DMD).

[0189] The optical modulator 212 is driven by the optical modulator driver unit 222, which is connected to the image processing unit 245.

[0190] The image processing unit 245 inputs image data to the light modulator driving unit 222. The light modulator driving unit 222 converts the input image data into a data signal suitable for the operation of the display panel 215. Based on the converted data signal, the light modulator driving unit 222 applies voltage to each pixel of each display panel 215 and draws an image on the display panel 215.

[0191] The optical system 213 includes a lens or mirror that causes the incident image light PLA to form an image on the imaging medium SC. The optical system 213 may also include a zoom mechanism that magnifies or reduces the image projected onto the imaging medium SC and a focus adjustment mechanism that performs focus adjustment.

[0192] The projection device 200 also includes an operation unit 231, a signal receiving unit 233, an input interface 235, a storage unit 237, a data interface 241, an interface unit 242, a frame memory 243, an image processing unit 245, and a control unit 250. The input interface 235, storage unit 237, data interface 241, interface unit 242, image processing unit 245, and control unit 250 can communicate with each other via an internal bus 207.

[0193] The operation unit 231 can generate corresponding operation signals based on the operation of various buttons and switches on the surface of the projection device 200 housing, and output them to the input interface 235. The input interface 235 includes circuitry that outputs the operation signals input from the operation unit 231 to the control unit 250.

[0194] After receiving signals (such as infrared signals or Bluetooth signals) sent from the control device 5 (such as a remote control), the signal receiving unit 233 can decode the received signals to generate corresponding operation signals. The signal receiving unit 233 outputs the generated operation signals to the input interface 235. The input interface 235 outputs the received operation signals to the control unit 250.

[0195] Storage unit 237 may be a magnetic recording device such as a hard disk drive (HDD), or a storage device using semiconductor storage elements such as flash memory. Storage unit 237 stores programs executed by control unit 250, data processed by control unit 250, image data, etc.

[0196] Data interface 241 includes a connector and interface circuitry, enabling wired connection with other electronic devices 100. Data interface 241 can also be a communication interface for communicating with other electronic devices 100. Data interface 241 receives image data, sound data, etc., from other electronic devices 100. In this embodiment, the image data can be content images.

[0197] Interface unit 242 is a communication interface for communicating with other electronic devices 100 according to the Ethernet standard. Interface unit 242 includes a connector and interface circuitry for processing signals transmitted by the connector. Interface unit 242 is an interface substrate including the connector and interface circuitry and is connected to the main substrate of control unit 250, which is a substrate on which processor 253 and other components are mounted. The connector and interface circuitry constituting interface unit 242 are mounted on the main substrate of control unit 250. Interface unit 242 can receive setting information or instruction information transmitted by other electronic devices 100.

[0198] The control unit 250 includes a memory 251 and a processor 253.

[0199] Memory 251 is a storage device that non-volatilely stores programs and data executed by processor 253. Memory 251 is composed of semiconductor storage elements such as magnetic storage devices, flash read-only memory (ROM), or other types of non-volatile storage devices. Memory 251 may also include random access memory (RAM) that constitutes the working area of ​​processor 253. Memory 251 stores data processed by control unit 250 and control programs executed by processor 253.

[0200] The processor 253 can be a single processor or a combination of multiple processor groups. The processor 253 executes control programs to control various parts of the projection device 200. For example, the processor 253 performs corresponding image processing based on operation signals generated by the operation unit 231, and outputs the parameters used in the image processing (such as parameters for keystone correction of the image) to the image processing unit 245. Furthermore, the processor 253 can control the light source in the light source unit 211 to turn on, off, or adjust its brightness by controlling the light source drive unit 221.

[0201] The image processing unit 245 and the frame memory 243 can be constructed from integrated circuits. Integrated circuits include large-scale integrated circuits (LSI), application-specific integrated circuits (ASIC), and programmable logic devices (PLD), where PLD may include field-programmable gate arrays (FPGA). Integrated circuits may also include a portion of analog circuitry, or a combination of a processor and integrated circuits. Combinations of processors and integrated circuits are referred to as microcontroller units (MCU), system-on-chips (SoC), system LSIs, chipsets, etc.

[0202] The image processing unit 245 can store the image data received from the data interface 241 in the frame memory 243. The frame memory 243 includes multiple memory banks, each containing storage capacity for writing one frame of image data. The frame memory 243 can be constructed from synchronous dynamic random access memory (SDRAM) or dynamic random access memory (DRAM).

[0203] The image processing unit 245 can perform image processing on the image data stored in the frame memory 243, including resolution conversion, size adjustment, distortion correction, shape correction, digital zoom, image tone adjustment, and image brightness adjustment.

[0204] The image processing unit 245 can also convert the input frame frequency of the vertical synchronization signal into a drawing frequency and generate a vertical synchronization signal with a drawing frequency. The generated vertical synchronization signal is called the output synchronization signal. The image processing unit 245 then outputs the above-mentioned output synchronization signal to the optical modulator driver unit 222.

[0205] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0206] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0207] Although the subject matter has been described using language specific to the method's logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims. Regarding the apparatus in the above embodiments, the specific manner in which the various modules perform their operations has been described in detail in the embodiments relating to the method, and will not be elaborated upon here.

Claims

1. A method for determining parameters, characterized in that, include: The image is captured by taking a picture of the projection area when the projection device projects the correction image onto the projection area. The correction image includes multiple feature images, including a first sub-feature image and a second sub-feature image. The second sub-feature image is within the image range of the first sub-feature image and is superimposed on the first sub-feature image. Both the first and second sub-feature images are used to calculate the perspective transformation matrix. The first sub-feature image is used to provide anti-occlusion and anti-tilt capabilities, and the second sub-feature image is used to provide the direction and orientation of the projected image. A first image and a second image are extracted from the captured image. The first image includes a first sub-feature image extracted from the captured image, and the second image includes a second sub-feature image extracted from the captured image. Based on the first image and / or the second image, obtain the perspective transformation matrix between the captured image and the modulation plane of the projection device.

2. The method according to claim 1, characterized in that, The step of obtaining the perspective transformation matrix between the captured image and the modulation plane of the projection device based on the first image and / or the second image includes: Based on the first image and / or the second image, determine the projection scene type corresponding to the projection device; The perspective transformation matrix is ​​determined based on the projection scene type.

3. The method according to claim 2, characterized in that, The step of determining the projection scene type corresponding to the projection device based on the first image and / or the second image includes: Based on the first image and / or the second image, determine the projection angle of the projection device relative to the projection area and / or the occlusion of the projected image projected by the projection device; The projection scene type is determined based on the projection angle and / or the occlusion situation.

4. The method according to claim 2, characterized in that, Determining the perspective transformation matrix based on the projection scene type includes: When the projection scene type is a first scene type, image transformation parameters are obtained based on the first image, wherein the image transformation parameters are used to make the contour shape of each first sub-feature image in the first image after adjustment by the image transformation parameters consistent with the contour shape of the first sub-feature image in the corrected image. The second image is adjusted based on the image transformation parameters to obtain the adjusted second image; The perspective transformation matrix is ​​determined based on the adjusted second image and the image transformation parameters; The first scene type indicates that the projection angle of the projection device relative to the projection area is greater than or equal to a preset angle threshold, and the projected image projected by the projection device is obstructed.

5. The method according to claim 4, characterized in that, The feature image is set in multiple target regions of the corrected image. Based on the first image and / or the second image, the projection scene type of the projection device is determined, including: If at least one of the target regions in the second image does not include the second sub-feature image, and the number of targets in the first sub-feature image determined from the first image is less than a preset number threshold, then the projection scene type of the projection device is determined to be the first scene type.

6. The method according to claim 2, characterized in that, Obtaining the perspective transformation matrix based on the projection scene type includes: When the projection scene type is the second scene type, the perspective transformation matrix is ​​determined based on the second image, wherein the second scene type indicates that the projection angle of the projection device relative to the projection area is less than a preset angle threshold.

7. The method according to claim 6, characterized in that, Determining the perspective transformation matrix based on the second image includes: For each of the second sub-feature images in the second image, determine the coordinate information corresponding to the corner points of the second sub-feature images; The target corner point is determined based on the coordinate information corresponding to all the obtained corner points; The perspective transformation matrix is ​​determined based on the coordinate information corresponding to the target corner point.

8. The method according to claim 2, characterized in that, Obtaining the perspective transformation matrix based on the projection scene type includes: When the projection scene type is the third scene type, the perspective transformation matrix is ​​determined based on the first image, wherein the third scene type indicates that the projection angle of the projection device relative to the projection area is greater than or equal to a preset angle threshold, and the projected image projected by the projection device is not obstructed.

9. The method according to claim 5, characterized in that, The method further includes: If the number of targets in the first sub-feature image determined based on the first image is greater than the preset number threshold, then the first sub-feature image is clustered to obtain the clustering result; The target quantity is corrected based on the clustering results to obtain the corrected target quantity.

10. The method according to claim 1, characterized in that, The first sub-feature image is a dot image, and the second sub-feature image is an identification code.

11. A parameter determining device, characterized in that, include: The acquisition module is configured to acquire captured images. The captured images are obtained by capturing images of the projection area when the projection device projects a correction image onto the projection area. The correction image includes multiple feature images, including a first sub-feature image and a second sub-feature image. The second sub-feature image is within the image range of the first sub-feature image and is superimposed on the first sub-feature image. Both the first sub-feature image and the second sub-feature image are used to calculate the perspective transformation matrix. The first sub-feature image is used to provide anti-occlusion and anti-tilt capabilities, and the second sub-feature image is used to provide the direction and orientation of the projected image. The extraction module is configured to extract a first image and a second image from the captured image, wherein the first image includes a first sub-feature image extracted from the captured image, and the second image includes a second sub-feature image extracted from the captured image; The acquisition module is configured to obtain a perspective transformation matrix between the captured image and the modulation plane of the projection device based on the first image and / or the second image.

12. A computer storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processing device, it implements the steps of the method described in any one of claims 1-10.

13. A projection device, characterized in that, include: A storage device on which computer programs are stored; A processing device for executing the computer program in the storage device to implement the steps of the method according to any one of claims 1-10.

Images