Image reconstruction method and device, electronic equipment and storage medium

Abstract

The invention provides an image reconstruction method and apparatus, an electronic device and a storage medium. The image reconstruction method comprises the steps of obtaining a compressed image of a detection object for a projection plane; based on a conversion relation, processing at least one of two-dimensional position information, texture information and depth information included in the compressed image to obtain three-dimensional information, the conversion relation being determined according to limit position information of the two-dimensional position information relative to the projection plane or a projection angle of the two-dimensional position information relative to the projection plane; and according to the multiple pieces of three-dimensional information, generating point cloud data of the detection object.

Description

Technical Field

[0001] The present disclosure relates to the fields of image processing, point cloud processing and industrial technology, and more specifically, to an image reconstruction method, device, electronic device and storage medium. Background Art

[0002] With the development of industrial technology, 3D model data is increasingly used in various industrial fields. However, due to the limitations of graphics card processing power and network bandwidth, 3D model data is difficult to transmit in real time, making it difficult to effectively apply 3D model data in the industrial field.

[0003] In one example, the transmission capacity of the 3D model data can be improved by increasing the investment in hardware equipment. However, this method not only increases the cost of use but also fails to solve the problem that it is difficult to effectively apply the 3D model data in the industrial field.

[0004] In another example, it is possible to compress the 3D model data before transmitting it, and reconstruct the compressed image data when using it, so as to improve the application capability of the 3D model data in the industrial field. Image compression refers to the process of reducing the size of the 3D model data, and image reconstruction refers to the process of restoring the 3D model data from the compressed image data.

[0005] Therefore, how to achieve more effective reconstruction of compressed image data is an urgent problem to be solved. Summary of the invention

[0006] In view of this, the present disclosure provides an image reconstruction method, device, electronic device and storage medium.

[0007] According to one aspect of the present disclosure, there is provided an image reconstruction method, comprising: obtaining a compressed image of a detection object with respect to a projection plane; processing at least one of two-dimensional position information, texture information and depth information included in the compressed image based on a conversion relationship to obtain three-dimensional information, wherein the conversion relationship is determined based on the extreme position information of the two-dimensional position information relative to the projection plane, or the projection angle of the two-dimensional position information relative to the projection plane; and generating point cloud data of the detection object based on the multiple three-dimensional information.

[0008] According to another aspect of the present disclosure, an image reconstruction device is provided, including: a second acquisition module, used to acquire a compressed image of the detection object with respect to the projection plane; a second processing module, used to process at least one of the two-dimensional position information, texture information and depth information included in the above-mentioned compressed image based on a conversion relationship to obtain three-dimensional information, and the above-mentioned conversion relationship is determined according to the extreme position information of the above-mentioned two-dimensional position information relative to the above-mentioned projection plane, or the projection angle of the above-mentioned two-dimensional position information relative to the above-mentioned projection plane; and a second generation module, used to generate point cloud data of the above-mentioned detection object based on the above-mentioned multiple three-dimensional information.

[0009] According to another aspect of the present disclosure, an electronic device is provided, comprising: one or more processors; and a memory for storing one or more instructions, wherein when the one or more instructions are executed by the one or more processors, the one or more processors implement the method described in the present disclosure.

[0010] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which executable instructions are stored. When the executable instructions are executed by a processor, the processor implements the method described in the present disclosure.

[0011] According to another aspect of the present disclosure, a computer program product is provided. The computer program product includes computer executable instructions. When the computer executable instructions are executed, they are used to implement the method described in the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0013] Figure 1 The system architecture to which the image reconstruction method according to the embodiment of the present disclosure can be applied is schematically shown;

[0014] Figure 2 The flowchart of the image reconstruction method according to the embodiment of the present disclosure is schematically shown;

[0015] Figure 3 An example schematic diagram of an image reconstruction process according to an embodiment of the present disclosure is schematically shown;

[0016] Figure 4 An example schematic diagram schematically shows an image reconstruction process according to another embodiment of the present disclosure;

[0017] Figure 5 A block diagram schematically shows an image reconstruction device according to an embodiment of the present disclosure; and

[0018] Figure 6A block diagram of an electronic device suitable for implementing an image reconstruction method according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0019] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0020] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0021] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0022] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0023] In the technical solution of the present invention, the user information (including but not limited to user personal information, user image information, user device information, such as location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0024] To this end, the present disclosure provides an image reconstruction method, device, electronic device and storage medium, which can be applied to image processing, point cloud processing and industrial technology fields. The image reconstruction method includes: obtaining a compressed image of the detection object with respect to the projection plane; processing at least one of the two-dimensional position information, texture information and depth information included in the compressed image based on a conversion relationship to obtain three-dimensional information, and the conversion relationship is determined based on the extreme position information of the point cloud data relative to the projection plane, or the projection angle of the three-dimensional information relative to the projection plane; and generating point cloud data of the detection object based on multiple three-dimensional information.

[0025] Figure 1 The system architecture to which the image reconstruction method according to the embodiment of the present disclosure can be applied is schematically shown. It should be noted that: Figure 1 What is shown is merely an example of a system architecture to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0026] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104 and a server 105. The network 104 is a medium for providing a communication link between different devices.

[0027] It should be noted that the image reconstruction method provided in the embodiment of the present disclosure can generally be executed by the server 105 . Accordingly, the image reconstruction device provided in the embodiment of the present disclosure can generally be set in the server 105 .

[0028] Alternatively, the image reconstruction method provided in the embodiment of the present disclosure may also be executed by the first terminal device 101, the second terminal device 102 or the third terminal device 103. Accordingly, the image reconstruction apparatus provided in the embodiment of the present disclosure may also be arranged in the first terminal device 101, the second terminal device 102 or the third terminal device 103.

[0029] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0030] It should be noted that the sequence numbers of the operations in the following method are only used as representations of the operations for the purpose of description, and should not be regarded as representing the execution order of the operations. Unless explicitly stated, the method does not need to be executed completely in the order shown.

[0031] The above describes the system architecture to which the image reconstruction method provided by the present disclosure can be applied. Figure 2For example, the image reconstruction process of the present disclosure is further described.

[0032] Figure 2 The flowchart of the image reconstruction method according to the embodiment of the present disclosure is schematically shown.

[0033] like Figure 2 As shown, the image reconstruction method 200 includes operations S210 to S230.

[0034] In operation S210, a compressed image of the detection object with respect to a projection plane is acquired.

[0035] In operation S220, based on the conversion relationship, at least one of the two-dimensional position information, texture information and depth information included in the compressed image is processed to obtain three-dimensional information, and the conversion relationship is determined according to the extreme position information of the two-dimensional position information relative to the projection plane, or the projection angle of the two-dimensional position information relative to the projection plane.

[0036] In operation S230 , point cloud data of the detection object is generated according to the plurality of three-dimensional information.

[0037] The image reconstruction process may refer to the inverse process of the image compression process. The image reconstruction process may refer to the process of reconstructing point cloud data in a three-dimensional space based on a compressed image in a two-dimensional plane. The detection object may refer to a target or object that needs to be paid attention to in the image compression process.

[0038] A compressed image may refer to an image in a two-dimensional plane obtained by compressing the three-dimensional information used to represent the detection object in the three-dimensional space to reduce the file size of the three-dimensional information or speed up the transmission speed when projecting the three-dimensional information onto the two-dimensional plane. The file format of the compressed image may be Portable Network Graphics (PNG) and Bitmap (BMP) formats.

[0039] The two-dimensional position information can represent the position of each point of the detected object in the two-dimensional plane relative to a certain reference origin. For example, the two-dimensional position information can include an X coordinate and a Y coordinate, where the X coordinate is used to describe the position of the point in the horizontal direction and the Y coordinate is used to describe the position of the point in the vertical direction. The depth information can represent the distance between each point and the viewing angle or a certain reference plane.

[0040] In one example, the conversion relationship can be determined based on the extreme position information of the two-dimensional position information relative to the projection plane. The extreme position information can include the maximum coordinate value and the minimum coordinate value of the two-dimensional position information in the two coordinate axes of the projection plane, the positive direction and the negative direction perpendicular to the projection plane. In this case, at least one of the two-dimensional position information, the texture information and the depth information can be processed based on the extreme position information to convert the point in the two-dimensional plane to a point in the three-dimensional space to obtain the three-dimensional information.

[0041] In another example, the conversion relationship can be determined based on the projection angle of the two-dimensional position information relative to the projection plane. The projection angle may refer to the angle at which the two-dimensional position information is projected on the projection plane, that is, the angle between a certain point and the projection plane. The projection angle is obtained by projecting the two-dimensional position information onto the two-dimensional plane and calculating the angle between the projected vector and the normal vector of the projection plane. In this case, at least one of the two-dimensional position information, texture information, and depth information can be processed based on the projection angle to convert a point in the two-dimensional plane to a point in three-dimensional space to obtain three-dimensional information.

[0042] After obtaining multiple three-dimensional information, point cloud data of the detection object can be generated. The point cloud data of the detection object can refer to data composed of a series of three-dimensional information on the surface of the target or object. The point cloud data represents the external shape, structure and geometric information of the detection object. The point cloud data includes multiple points. The three-dimensional information can include three-dimensional position information and texture information. The three-dimensional position information can represent the position of each point in the three-dimensional space relative to a certain reference origin. For example, the three-dimensional position information can include X coordinates, Y coordinates and Z coordinates.

[0043] The shape of the detection object can be configured according to actual business needs and is not limited here. For example, the shape of the detection object may include at least one of the following: a sphere, a cube, a cylinder, a cone, a polyhedron, and an irregular shape. In one example, the spherical detection object may include a workpiece with a spherical or spherical shape, which may be a complete sphere or a partial sphere, such as a spherical surface and a hemispherical surface.

[0044] According to an embodiment of the present disclosure, by processing at least one of the two-dimensional position information, texture information and depth information of the detection object in the projection plane in combination with the conversion relationship, it is helpful to improve the accuracy of the three-dimensional information. In this process, since the conversion relationship is determined based on the extreme position information of the point cloud data relative to the projection plane, or the projection angle of the three-dimensional information relative to the projection plane, it can adapt to the needs of different scenes and improve the flexibility and applicability of the two-dimensional position information conversion. On this basis, by generating the point cloud data of the detection object based on the three-dimensional information, the reconstruction effect of the point cloud data can be improved.

[0045] In the embodiment of the present disclosure, the conversion relationship can be determined according to the extreme position information of the two-dimensional position information relative to the projection plane. Figure 3 The process of realizing image reconstruction based on a conversion relationship determined according to the extreme position information of the two-dimensional position information relative to the projection plane is further described.

[0046] Figure 3 An example schematic diagram of an image reconstruction process according to an embodiment of the present disclosure is schematically shown.

[0047] In 300 , the image reconstruction process is described by taking the detection object as a sphere, XOY as a projection plane, and the compressed image including a texture image and a depth image as an example.

[0048] like Figure 3 As shown, the point cloud data can be divided into two hemispheres based on the XOY projection plane, namely, a hemisphere 301 along the positive direction of the Z axis and a hemisphere 302 along the negative direction of the Z axis.

[0049] In the texture image 303 and the depth image 304 corresponding to the negative direction of the Z axis, in order to obtain the corresponding point D1 in the three-dimensional space of any point D0 in the texture image 303 and the depth image 304, the two-dimensional position information (ix4, iy4) of the point D0 can be mapped to the three-dimensional space to obtain x4 and y4 in the three-dimensional position information of the point D1; z4 in the three-dimensional position information of D1 is obtained according to the pixel value of the point D0 in the depth image 304, thereby obtaining the three-dimensional position information (x4, y4, z4) of the point D1. The method of determining the three-dimensional position information based on the two-dimensional position information can be configured according to the actual business needs and is not limited here. For example, the determination method may include at least one of the following: a depth sensor method, a multi-view geometry method, and a deep learning method.

[0050] The depth sensor method refers to the use of depth sensors such as laser scanners, stereo cameras or time-of-flight cameras to measure the distance from the surface of the detection object to the depth sensor, thereby obtaining three-dimensional position information. The multi-view geometry method refers to taking multiple images of the same detection object from different angles and using triangulation to analyze the two-dimensional position information of each image to determine the three-dimensional position information. The deep learning method refers to processing the two-dimensional position information using a depth information model to mine the depth clues in the captured image to obtain three-dimensional position information.

[0051] For example, in an application scenario where the detection object is a sphere, the texture image 303 and the depth image 304 may include a two-dimensional position information set of a circle, and correspondingly, the point cloud data may include a three-dimensional position information set of the sphere obtained using a point cloud acquisition device.

[0052] In one example, the limit position information may include the maximum coordinate value and the minimum coordinate value of the point cloud data in the two coordinate axes of the projection plane and the maximum coordinate value and the minimum coordinate value of the point cloud data in the positive direction and the negative direction perpendicular to the projection plane. For the positive direction of the two coordinate axes of the projection plane and the positive direction perpendicular to the projection plane, the maximum coordinate value indicates the farthest point position of the point cloud data in the positive direction of the coordinate axis, and the minimum coordinate value indicates the closest point position of the point cloud data in the positive direction of the coordinate axis. For the negative direction of the two coordinate axes of the projection plane and the negative direction perpendicular to the projection plane, the maximum coordinate value indicates the closest point position of the point cloud data in the negative direction of the coordinate axis, and the minimum coordinate value indicates the farthest point position of the point cloud data in the negative direction of the coordinate axis.

[0053] For example, in an application scenario where the detection object is a sphere, the coordinate value corresponding to the projection plane may refer to the coordinate value of the point corresponding to the diameter of a circle or a semicircle obtained by projecting the point cloud data onto the projection plane.

[0054] On this basis, the fourth ratio can be determined based on the two-dimensional position information, the maximum coordinate value and the minimum coordinate value corresponding to the projection plane. The fifth ratio is determined based on the depth information, the maximum coordinate value and the minimum coordinate value perpendicular to the projection plane. The three-dimensional position information is determined based on the target image resolution, the fourth ratio and the fifth ratio.

[0055] It should be noted that the reconstruction level can be adjusted by adjusting the target image resolution. For example, if high-precision details need to be retained, the reconstruction level is high and the target image resolution can be set to a higher resolution. Alternatively, if point cloud data needs to be displayed in real time, the reconstruction level is low and the target image resolution can be set to a lower resolution.

[0056] In a specific example, the process of processing the two-dimensional position information according to the extreme position information to obtain the three-dimensional position information can be shown in the following formulas (1) and (2).

[0057] #timg# （1） #timg# （2）

[0058] in, and Represents the coordinate value corresponding to the projection plane in the two-dimensional position information, Represents the minimum coordinate value of the point cloud data on the X-axis. Represents the maximum coordinate value of the point cloud data on the X-axis. Represents the minimum coordinate value of the point cloud data on the Y coordinate axis. Represents the maximum coordinate value of the point cloud data on the Y coordinate axis. Characterizes the width information in the target image resolution, Characterize the height information in the target image resolution, and Represents two-dimensional position information.

[0059] In another example, the process of processing the depth information according to the extreme position information to obtain the three-dimensional position information can be shown in the following equations (3) and (4).

[0060] #timg# （3） #timg# （4）

[0061] in, Represents the pixel value corresponding to the two-dimensional position information, Represents the minimum coordinate value of the point cloud data in the negative direction perpendicular to the projection plane. Represents the maximum coordinate value of the point cloud data in the negative direction perpendicular to the projection plane. Represents the three-dimensional position information in the negative direction perpendicular to the projection plane, Represents the minimum coordinate value of the point cloud data in the positive direction perpendicular to the projection plane. Represents the maximum coordinate value of the point cloud data in the positive direction perpendicular to the projection plane. Represents the three-dimensional position information in the positive direction perpendicular to the projection plane.

[0062] In another specific example, the two-dimensional position information may be processed according to the projection angle of the three-dimensional position information relative to the projection plane to obtain the three-dimensional position information. This process may be shown in the following equations (5) to (9).

[0063] #timg# （5） #timg# （6） #timg# （7） #timg# （8） #timg# （9）

[0064] in, Characterize the first pitch angle, Characterize the first azimuth. It should be noted that some formulas provided in the present disclosure are given with the detection object being a sphere as an example, but the shape of the detection object to which the image reconstruction method of the present disclosure is applicable can be configured according to actual business needs and is not limited here.

[0065] According to an embodiment of the present disclosure, the fourth ratio is determined by using the two-dimensional position information and the maximum and minimum coordinate values ​​corresponding to the projection plane, and the fifth ratio is determined based on the depth information and the maximum and minimum coordinate values ​​perpendicular to the projection plane, so that the three-dimensional position information can be accurately determined at different spatial positions. On this basis, the three-dimensional position information is determined based on the target image resolution, the fourth ratio and the fifth ratio. Since the target image resolution can be flexibly adjusted according to actual needs, the detection object can be made clearer and more accurate at the required resolution, thereby helping to improve the reconstruction effect of the point cloud data.

[0066] In the embodiment of the present disclosure, the conversion relationship can be determined according to the projection angle of the two-dimensional position information relative to the projection plane. Figure 4 The process of realizing image reconstruction based on a conversion relationship determined according to the projection angle of the two-dimensional position information relative to the projection plane is further described.

[0067] Figure 4 An example schematic diagram of an image reconstruction process according to another embodiment of the present disclosure is schematically shown.

[0068] In 400 , the image reconstruction process is described by taking the detection object as a sphere and XOY as a projection plane as an example.

[0069] like Figure 4 As shown, for the two-dimensional position information (ix5, iy5) of any point E0 in the compressed image 401, the two-dimensional position information can be three-dimensionally reconstructed to obtain the three-dimensional position information (x5, y5, z5) of the corresponding point E1.

[0070] On this basis, the sixth ratio can be determined according to the two-dimensional position information and the preset angle range. The three-dimensional position information is determined according to the target image resolution and the projection angle determined based on the sixth ratio. The preset angle range can represent the viewing angle of the acquisition device used for point cloud data, that is, the observation angle or field of view of the acquisition device when acquiring point cloud data. The projection angle can include a second pitch angle and the second azimuth .

[0071] In one example, the projection angle may include a second pitch angle and the second azimuth . Second pitch angle It can refer to the angle between the positive direction of the Z axis and the position of the three-dimensional position information in the three-dimensional space and the XOY plane, which usually varies between -π / 2 and π / 2. The second pitch angle It can be used to describe the height or depth of three-dimensional position information relative to the XOY plane. It can refer to the angle between the positive direction of the Z axis and the projection of the three-dimensional position information on the XOY plane and the positive direction of the Z axis, usually ranging from 0 to 2π. The second azimuth angle It can be used to describe the position of three-dimensional position information on the horizontal plane.

[0072] For example, in an application scenario where the detection object is a sphere, the compressed image 401 may include a set of two-dimensional position information of a circle, and correspondingly, the point cloud data may include a set of three-dimensional position information of a sphere obtained by using a point cloud acquisition device. In a specific example, the process of processing the two-dimensional position information according to the projection angle of the three-dimensional position information relative to the projection plane to obtain the three-dimensional position information can be shown in the following formulas (10) to (14).

[0073] #timg# （10） #timg# （11） #timg# （12） #timg# （13） #timg# （14）

[0074] in, Characterize the second pitch angle, Characterize the second azimuth, and Represents two-dimensional position information, Characterizes the width information in the target image resolution, Characterizing the height information in the target image resolution, the preset angle range corresponding to the second pitch angle is , the preset angle range corresponding to the second azimuth is .

[0075] According to the embodiments of the present disclosure, by combining the two-dimensional position information, the projection angle and the preset angle range, the two-dimensional to three-dimensional position information conversion can be performed more accurately, thereby improving the accuracy of the three-dimensional position information obtained subsequently. In addition, since the target image resolution can be flexibly adjusted according to actual needs, the detection object can be made clearer and more accurate at the required resolution, thereby helping to improve the reconstruction effect of the point cloud data.

[0076] Figure 5 The block diagram of an image reconstruction device according to an embodiment of the present disclosure is schematically shown.

[0077] like Figure 5 As shown, the image reconstruction device 500 may include a second acquisition module 510 , a second processing module 520 and a second generation module 530 .

[0078] The second acquisition module 510 is used to acquire a compressed image of the detection object on the projection plane.

[0079] The second processing module 520 is used to process at least one of the two-dimensional position information, texture information and depth information included in the compressed image based on a conversion relationship to obtain three-dimensional information. The conversion relationship is determined based on the extreme position information of the two-dimensional position information relative to the projection plane, or the projection angle of the two-dimensional position information relative to the projection plane.

[0080] The second generating module 530 is used to generate point cloud data of the detection object according to multiple three-dimensional information.

[0081] According to the embodiments of the present invention, any one or more of the modules, or at least part of the functions of any one of them, can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging the circuit, or in any one of the three implementation methods of software, hardware and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be executed.

[0082] It should be noted that the image reconstruction device part in the embodiment of the present disclosure corresponds to the image reconstruction method part in the embodiment of the present disclosure. The description of the image reconstruction device part specifically refers to the image reconstruction method part, which will not be repeated here.

[0083] Figure 6 A block diagram of an electronic device suitable for implementing an image reconstruction method according to an embodiment of the present disclosure is schematically shown. Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0084] like Figure 6 As shown, the computer electronic device 600 according to the embodiment of the present disclosure includes a processor 601, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage part 608 to the random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include an on-board memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiment of the present disclosure.

[0085] In the RAM 603, various programs and data necessary for the operation of the electronic device 600 are stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604.

[0086] According to an embodiment of the present disclosure, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 may further include one or more of the following components connected to the input / output (I / O) interface 605: an input portion 606 including a keyboard, a mouse, etc.; an output portion 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 608 including a hard disk, etc.; and a communication portion 609 including a network interface card such as a LAN card, a modem, etc. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the input / output (I / O) interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage portion 608 as needed.

[0087] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the image reconstruction method according to the embodiment of the present disclosure is implemented.

[0088] In the present disclosure, a computer readable storage medium may be any tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0089] An embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method provided by the embodiment of the present disclosure. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the image reconstruction method provided by the embodiment of the present disclosure.

[0090] When the computer program is executed by the processor 601, the above functions defined in the system / device of the embodiment of the present disclosure are executed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0091] According to the embodiments of the present disclosure, program codes for executing the computer programs provided by the embodiments of the present disclosure may be written in any combination of one or more programming languages.

[0092] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. It should also be noted that in some alternative implementations, the functions marked in the blocks may also occur in an order different from that marked in the accompanying drawings.

[0093] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. An image reconstruction method, comprising: Obtaining a compressed image of the detection object with respect to the projection plane; Based on a conversion relationship, at least one of the two-dimensional position information, texture information, and depth information included in the compressed image is processed to obtain three-dimensional information, wherein the conversion relationship is determined according to the extreme position information of the two-dimensional position information relative to the projection plane, or the projection angle of the two-dimensional position information relative to the projection plane; as well as Point cloud data of the detection object is generated according to the multiple three-dimensional information.

2. The method according to claim 1, wherein: The three-dimensional information includes three-dimensional position information and texture information; The three-dimensional information obtained by processing at least one of the two-dimensional position information, texture information and depth information included in the compressed image based on the conversion relationship includes: Based on the extreme position information, processing the two-dimensional position information or the depth information to obtain the three-dimensional position information; and The texture information of the three-dimensional position information is determined according to the texture information of the two-dimensional position information.

3. The method according to claim 2, wherein: The limit position information includes the maximum coordinate value and the minimum coordinate value of the two-dimensional position information in the two coordinate axes of the projection plane and the maximum coordinate value and the minimum coordinate value of the two-dimensional position information in the positive direction and the negative direction perpendicular to the projection plane; The processing of the two-dimensional position information or the depth information based on the limit position information to obtain the three-dimensional position information includes: For each of the two-dimensional position information, determining a fourth ratio according to the two-dimensional position information, a maximum coordinate value and a minimum coordinate value corresponding to the projection plane; determining a fifth ratio based on the depth information, a maximum coordinate value and a minimum coordinate value perpendicular to the projection plane; and The three-dimensional position information is determined based on the target image resolution, the fourth ratio, and the fifth ratio.

4. The method according to claim 1, wherein: The three-dimensional information includes three-dimensional position information and texture information; The three-dimensional information obtained by processing at least one of the two-dimensional position information, texture information and depth information included in the compressed image based on the conversion relationship includes: Based on the projection angle, processing the two-dimensional position information or the depth information to obtain the three-dimensional position information; and The texture information of the three-dimensional position information is determined according to the texture information of the two-dimensional position information.

5. The method according to claim 4, wherein: The processing of the two-dimensional position information or the depth information based on the projection angle to obtain the three-dimensional position information includes: For each of the two-dimensional position information, determining a sixth ratio according to the two-dimensional position information and a preset angle range, wherein the preset angle range represents a viewing angle of a device for collecting the point cloud data; and The three-dimensional position information is determined according to the target image resolution and the projection angle determined based on the sixth ratio.

6. The method according to claim 1, wherein: The detection object is a sphere.

7. An image reconstruction device, comprising: A second acquisition module is used to acquire a compressed image of the detection object with respect to the projection plane; a second processing module, configured to process at least one of the two-dimensional position information, the texture information and the depth information included in the compressed image based on a conversion relationship to obtain three-dimensional information, wherein the conversion relationship is determined according to the extreme position information of the two-dimensional position information relative to the projection plane, or the projection angle of the two-dimensional position information relative to the projection plane; as well as The second generating module is used to generate point cloud data of the detection object according to the multiple three-dimensional information.

8. An electronic device comprising: one or more processors; a memory for storing one or more computer programs, It is characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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