A positioning method, apparatus and system

Abstract

The embodiment of the application discloses a positioning method, device and system, which realizes small operation amount when positioning a target object in real time, reduces resource consumption and improves positioning efficiency. The method comprises the following steps: determining the corresponding relationship between an image pixel and a physical space by covering the pixel set of a camera imaging plane with a physical space grid area; determining the positioning pixel of the target object in the image, wherein the geographical position information of the physical space grid corresponding to the positioning pixel of the target object is the geographical position information of the positioning pixel of the target object, and the positioning of the target object can be realized.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the field of communication, and in particular to a positioning method, device and system. BACKGROUND

[0002] Cameras play an important role in the acquisition of dynamic information in cities, and through visual positioning technology, the cameras extract the position information of targets such as pedestrians and vehicles from video images. The position information of targets in cities is the basis for constructing a dynamic information database of cities. Cameras can be widely used in intelligent transportation, safe city, smart park and other scenarios. At present, the positioning method for positioning targets in cities using cameras can adopt the following two ways:

[0003] First, the Make3D positioning method. The Make3D method uses a clustering algorithm to segment parts with similar attributes (such as color and texture) in an image, divides the image into many extremely small regions, and the region becomes a superpixel block. Then, according to the depth information of each superpixel block and the connection between superpixel blocks, the plane where each superpixel block is located constitutes the basic unit of the 3D model, and an image model reflecting the real scene is obtained. By inputting the image into the image model, the position information of the target in the image is output, thereby realizing positioning.

[0004] Second, pixel-by-pixel intersection positioning. This positioning method obtains two images of a target in a physical space from different positions, finds the target on the two images by feature extraction and comparison of the two images, and then performs spatial positioning of the target according to the parameters of the camera and the linear theory of camera imaging.

[0005] However, the first positioning method needs to obtain a large amount of sample data in advance, and the sample data is difficult to obtain. In addition, the first positioning method uses pixel-by-pixel estimation, which has a large amount of calculation. The second positioning method needs to extract and match the features of the image in real time, which has a large amount of calculation. Therefore, the existing positioning methods consume a lot of resources for real-time positioning. SUMMARY

[0006] Embodiments of the present application provide a positioning method, device and system to realize less amount of calculation for real-time positioning of targets, reduce resource consumption, and improve positioning efficiency.

[0007] To achieve the above purpose, embodiments of the present application adopt the following technical solutions.

[0008] In a first aspect, the present application provides a positioning method, which comprises: determining a positioning pixel of a target object in an image, the positioning pixel being used to represent a position of the target object in the image; determining a grid of a physical space corresponding to the positioning pixel according to a target pixel set corresponding to the positioning pixel and a mapping relationship between the target pixel set and the grid of the physical space; and determining geographical position information of the positioning pixel according to geographical position information corresponding to the grid of the physical space corresponding to the positioning pixel. The target pixel set is obtained by dividing the image according to the grid of the physical space and parameter information of a camera used to collect the image. The mapping relationship is determined according to a grid of the physical space to which a pixel in the target pixel set belongs. In the present application, the corresponding relationship between the image pixel and the physical space is determined by covering the pixel set in the imaging plane of the camera with the grid of the physical space. Then, the positioning pixel of the target object in the image is determined, and the geographical position information represented by the grid of the physical space corresponding to the positioning pixel is the geographical position information of the positioning pixel of the target object. Thus, the positioning of the target object can be realized, and the operation amount is small when the target object is positioned in real time, the resource consumption is reduced, and the positioning efficiency is improved.

[0009] In the method of the first aspect, each pixel set in the image is determined according to the grid of the physical space and the parameter information of the camera, specifically: the pixel coordinates in the image corresponding to each of the plurality of corner points in the grid of the physical space are determined according to the geographical position coordinates of the plurality of corner points in the grid of the physical space, a projection matrix, the focal length of the camera and the geographical position coordinates of the center of the view point, the projection matrix being used to represent the conversion relationship between the pixel coordinates of the pixels in the image and the geographical position coordinates of the corner points on the grid of the physical space; a target polygon surrounded by each pixel in the image is determined according to the pixel coordinates of each pixel in the image and the correlation relationship between the plurality of corner points; and the pixels surrounded by the target polygon or the pixels surrounded by the target polygon and the pixels on the edges of the target polygon are used to construct the pixel set.

[0010] In the method of the first aspect, if the image collected by the camera is distorted, after the pixel coordinates of each pixel in the image are determined according to the geographical position coordinates of the plurality of corner points in the grid of the physical space, the projection matrix, the focal length of the camera and the geographical position coordinates of the center of the view point, specifically: the corrected pixel coordinates of each pixel in the image are determined according to the pixel coordinates of each pixel in the image and the radial distortion coefficient and / or the tangential distortion coefficient, the corrected pixel coordinates being used to determine the pixel set to which each pixel in the image belongs. In the present application, the pixel coordinates of each pixel in the image collected by the camera are corrected, which can effectively prevent the positioning pixel of the target object in the distorted image from being used to position the target object, and improve the accuracy of the positioning of the target object.

[0011] In the method, the pixel coordinates of each pixel in the image are determined according to the geographical position coordinates of the at least one sampling point and the plurality of corner points on the edges of the grid in the physical space, the projection matrix, the focal length of the camera and the geographical position coordinates of the center of the viewpoint. In the embodiment of the application, at least one sampling point is added to the edges of the grid in the physical space, and the pixel coordinates of each pixel in the image are determined according to the at least one sampling point and the corner points of the grid, so that the area of the grid in the physical space mapped on the image is closer to itself, thereby realizing more accurate projection expression of the grid in the physical space on the image. In addition, the mapping relationship between the corner points and / or sampling points of the grid in the physical space and the pixels of the image is established, the projection expression of the grid in the physical space is effectively and accurately, the influence of the terrain on the positioning accuracy is reduced, and the large-scale grid positioning accuracy is improved.

[0012] In a possible design, the parameter information of the camera is determined according to the feature points in the sample image and the corresponding geographical position coordinates.

[0013] In a possible design, the parameter information of the camera includes a focal length, a principal point position, a video CCD size and a pose parameter, the pose parameter includes geographical position coordinates of the camera, a pitch angle, a roll angle and a side view angle of the camera.

[0014] In a possible design, the geographical position information includes a global position code or geographical position coordinates.

[0015] In the method, the pixel coordinates of the first positioning pixel of the target object in the first image are determined, and specifically, the pixel coordinates of the reference pixel of the target object in the first image are determined according to the type of the target object, and the reference pixel is used to determine the pixel coordinates of the first positioning pixel of the target object in the first image. It should be noted that the determination manner of the first positioning pixel of the target object in the first image is different based on the type of the target object.

[0016] In the method, the pixel coordinates of the first positioning pixel of the target object in the first image are determined, and specifically, if the type of the target object is a vehicle, the pixel coordinates of the reference pixel of the vehicle in the first image, the height value and the width value of the vehicle are determined. The pixel coordinates of the first positioning pixel of the vehicle in the first image are determined according to the pixel coordinates of the reference pixel, the height value and the width value of the vehicle.

[0017] In the method of the first aspect, the pixel coordinates of the first positioning pixel of the target object in the first image are determined, and specifically, if the type of the target object is a pedestrian, the pixels corresponding to the feet of the pedestrian in the first image are determined as the reference pixels. The pixel coordinates of the first positioning pixel of the pedestrian in the first image are determined according to the pixel coordinates of the two reference pixels.

[0018] In the method of the first aspect, the pixel coordinates of the first positioning pixel of the target object in the first image are determined, and specifically, if the type of the target object is a pedestrian, the pixel corresponding to the center of gravity of the pedestrian in the first image is determined as the first positioning pixel.

[0019] In the second aspect of the embodiments of the present application, a positioning device is provided, which includes: a positioning pixel determination unit configured to determine a positioning pixel of a target object in an image, the positioning pixel being used to represent the position of the target object in the image; a grid determination unit configured to determine a grid of a physical space corresponding to the positioning pixel according to a target pixel set corresponding to the positioning pixel and a mapping relationship between the target pixel set and the grid of the physical space; and a geographic position information determination unit configured to determine geographic position information of the positioning pixel according to geographic position information corresponding to the grid of the physical space corresponding to the positioning pixel. The target pixel set is obtained by dividing the image according to the grid of the physical space and parameter information of a camera used to collect the image. The mapping relationship is determined according to the grid of the physical space to which the pixels in the target pixel set belong.

[0020] In the positioning device of the second aspect, the device includes: a first pixel coordinate determination unit configured to determine pixel coordinates of each of a plurality of corner points of a grid in a physical space in an image according to geographic position coordinates of the plurality of corner points, a projection matrix, a focal length of a camera, and geographic position coordinates of a viewpoint center, the projection matrix being used to represent a conversion relationship between pixel coordinates of the image and geographic position coordinates of the corner points on the grid in the physical space; and a target polygon determination unit configured to determine a target polygon formed by each pixel in the image according to the pixel coordinates of each pixel in the image and an association relationship between the plurality of corner points, the pixels enclosed by the target polygon, or the pixels enclosed by the target polygon and the pixels on the edges of the target polygon being used to construct a pixel set.

[0021] The positioning device based on the second aspect comprises a second pixel coordinate determination unit configured to determine, according to the pixel coordinates of each pixel in the image and the radial distortion coefficient and / or the tangential distortion coefficient, the corrected pixel coordinates of each pixel in the image, and the corrected pixel coordinates are used to determine the pixel set to which each pixel in the image belongs. The embodiments of the present application can effectively prevent the positioning pixels of the target object in the distorted image from being used to position the target object, thereby improving the accuracy of target object positioning.

[0022] The first pixel coordinate determination unit of the positioning device based on the second aspect comprises a first pixel coordinate determination sub-unit configured to determine, according to the geographical position coordinates of at least one sampling point and a plurality of corner points on the edges of the grid in the physical space, the projection matrix, the focal length of the camera, and the geographical position coordinates of the center of the viewpoint, the pixel coordinates of each pixel in the image. The embodiments of the present application add at least one sampling point to the edges of the grid in the physical space, and then determine each pixel in the image through the at least one sampling point and the corner points of the grid, so that the area of the grid in the physical space mapped on the image is closer to itself, thereby realizing more fine projection expression of the grid in the physical space on the image. In addition, the mapping relationship between the corner points and / or sampling points of the grid in the physical space and the pixels of the image is established, which effectively and accurately projects the grid in the physical space, reduces the influence of the terrain on the positioning accuracy, and is beneficial to improving the positioning accuracy of the large-scale grid.

[0023] In a possible design, the parameter information of the camera is determined according to the feature points in the sample image and the corresponding geographical position coordinates.

[0024] In a possible design, the parameter information of the camera comprises a focal length, a principal point position, a video CCD size, and a pose parameter, the pose parameter comprises geographical position coordinates of the camera, a pitch angle, a roll angle, and a side view angle of the camera.

[0025] In a possible design, the geographical position information comprises a global position code or geographical position coordinates.

[0026] The first positioning pixel determination unit of the positioning device based on the second aspect comprises a first determination sub-unit configured to, if the type of the target object is a vehicle, determine the pixel coordinates, the height value, and the width value of the reference pixel of the vehicle in the first image. A second determination sub-unit configured to determine, according to the pixel coordinates, the height value, and the width value of the reference pixel, the pixel coordinates of the first positioning pixel of the vehicle in the first image.

[0027] The positioning device of the second aspect determines the pixel coordinates of the first positioning pixel of the target object in the first image, and specifically, if the type of the target object is a pedestrian, the pixel corresponding to the feet of the pedestrian in the first image is determined as the reference pixel. The pixel coordinates of the first positioning pixel of the pedestrian in the first image are determined according to the pixel coordinates of the two reference pixels.

[0028] The positioning device of the second aspect determines the pixel coordinates of the first positioning pixel of the target object in the first image, and specifically, if the type of the target object is a pedestrian, the pixel corresponding to the center of gravity of the pedestrian in the first image is determined as the first positioning pixel.

[0029] In a third aspect of the embodiments of the present application, a positioning system is provided, including at least one camera and a positioning device. The camera is configured to capture images and send the images to the positioning device. The positioning device is configured to receive the images captured by the camera and perform the positioning method of the first aspect or any possible design of the first aspect.

[0030] In a fourth aspect of the embodiments of the present application, an electronic device is provided, including a processor and a memory. The memory is coupled to the processor and is configured to store computer program codes. The computer program codes include computer instructions. When the processor reads the computer instructions from the memory, the electronic device performs the positioning method of the first aspect or any possible design of the first aspect.

[0031] In a fifth aspect of the embodiments of the present application, a computer program product is provided. The computer program product includes computer instructions. When the computer instructions are run on a computer, the computer performs the positioning method of the first aspect or any possible design of the first aspect.

[0032] In a sixth aspect of the embodiments of the present application, a computer readable storage medium is provided. The computer readable storage medium includes computer instructions. When the computer instructions are run on a computer, the computer performs the positioning method of the first aspect or any possible design of the first aspect.

[0033] In a seventh aspect of the embodiments of the present application, a chip system is provided. The chip system includes one or more processors. When the one or more processors execute instructions, the one or more processors perform the positioning method of the first aspect or any possible design of the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative effort based on these drawings.

[0035] Figure 1 An architecture schematic diagram of an electronic device provided by an embodiment of the present application;

[0036] Figure 2 An architecture schematic diagram of another positioning system provided by an embodiment of the present application;

[0037] Figure 3 An architecture schematic diagram of another positioning system provided by an embodiment of the present application;

[0038] Figure 4 A flowchart of a positioning method provided by an embodiment of the present application;

[0039] Figure 5 An application scenario schematic diagram of a positioning method provided by an embodiment of the present application Figure 1 ;

[0040] Figure 6 An application scenario schematic diagram of a positioning method provided by an embodiment of the present application Figure 2 ;

[0041] Figure 7 An application scenario schematic diagram of a positioning method provided by an embodiment of the present application Figure 3 ;

[0042] Figure 8 An application scenario schematic diagram of a positioning method provided by an embodiment of the present application Figure 4 ;

[0043] Figure 9 An application scenario schematic diagram of a positioning method provided by an embodiment of the present application Figure 5 ;

[0044] Figure 10 A schematic diagram of a world map provided by an embodiment of the present application;

[0045] Figure 11 An application scenario schematic diagram of a positioning method provided by an embodiment of the present application Figure 6 ;

[0046] Figure 12 An application scenario schematic diagram of a positioning method provided by an embodiment of the present application Figure 7 ;

[0047] Figure 13An application scenario of a positioning method provided by an embodiment of the present application is shown in the figure Figure 8 ;

[0048] Figure 14 An assembly diagram of a positioning device provided by an embodiment of the present application is shown in the figure

[0049] Figure 15 An assembly diagram of a positioning system provided by an embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0050] Cameras play an important role in the acquisition of dynamic information in cities, and they extract the position information of targets such as pedestrians and vehicles from video images through visual positioning technology. The position information of targets in cities is the basis for constructing a dynamic information database of cities. Cameras can be widely used in intelligent transportation, safe cities, and smart parks. At present, the positioning method for positioning targets in cities using cameras can adopt the following two ways:

[0051] First, the Make3D positioning method. This method uses a clustering algorithm to segment parts with similar attributes (such as color and texture) in an image, divides the image into many extremely small regions, and calls these regions super-pixel blocks. Then, according to the depth information of each super-pixel block and the relationship between super-pixel blocks, the plane where each super-pixel block is located constitutes the basic unit of a 3D model, and an image model reflecting the real scene is obtained. By inputting the image into the image model, the position information of the target in the image is output, thereby realizing positioning.

[0052] Second, pixel-by-pixel intersection positioning. This positioning method acquires two images of a target in a physical space from different positions, finds the target on the two images by feature extraction and comparison of the two images, and then performs spatial positioning of the target according to the parameters of the camera and the linear theory of camera imaging.

[0053] However, the first positioning method requires a large amount of sample data to be obtained in advance, and it is difficult to obtain sample data. In addition, it uses pixel-by-pixel estimation, which has a large amount of calculation. The second positioning method requires real-time extraction and matching of image features, which has a large amount of computation. Therefore, the existing positioning methods consume a lot of resources for real-time positioning.

[0054] To solve the technical problem, the embodiment of the present application provides a positioning method, which comprises the following steps: determining a positioning pixel of a target object in an image, and determining a target pixel set corresponding to the positioning pixel of the target object; and according to a mapping relationship between the target pixel set and a grid of a physical space, a grid of the physical space corresponding to the positioning pixel can be found, and geographical position information represented by the grid is geographical position information of the positioning pixel of the target object, so that the positioning of the target object can be realized, the table positioning is used to replace the pixel-by-pixel intersection positioning, the calculation amount is effectively reduced, the resource consumption is reduced, and the positioning efficiency is improved.

[0055] The positioning method provided by the embodiment of the present application will be described below in combination with the drawings in the embodiment of the present application.

[0056] The positioning method provided by the embodiment of the present application can be applied to Figure 1 The electronic device shown in the figure (which can include a camera) can also be applied to Figure 2 The positioning system composed of the electronic device shown in the figure (which can not include a camera) and the camera, and can also be applied to Figure 3 The positioning system composed of the server, the camera and the electronic device (which can include a display screen) shown in the figure.

[0057] As Figure 1 The electronic device 100 can include a processor 110, a camera 120, a universal serial bus (USB) interface 130, a memory 140, a sensor module 150, a display screen 160 and the like. The sensor module 150 can include a pressure sensor 150A and a touch sensor 150B.

[0058] It can be understood that the structure shown in the embodiment of the present application does not constitute a specific limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 can include more or fewer components than the figure, or combine certain components, or split certain components, or different component arrangements. The components shown in the figure can be implemented in hardware, software or a combination of software and hardware.

[0059] The processor 110 can include one or more processing units, for example: the processor 110 can include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Different processing units can be independent devices or integrated in one or more processors.

[0060] The controller can generate operation control signals according to the instruction operation code and the timing signal, complete the control of fetching and executing instructions.

[0061] The processor 110 can also be provided with a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory can save instructions or data that the processor 110 has just used or repeatedly uses. If the processor 110 needs to use the instructions or data again, it can directly call from the memory. This avoids repeated access and reduces the waiting time of the processor 110, thereby improving the efficiency of the system.

[0062] In some embodiments, the processor 110 can include one or more interfaces. The interface can include an inter-integrated circuit (I2C) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, etc. The I2C interface is a bidirectional synchronous serial bus, including a serial data line (SDA) and a serial clock line (SCL). In some embodiments, the processor 110 can include multiple groups of I2C buses. The processor 110 can be coupled to the camera 120, etc. through the I2C bus interface.

[0063] The MIPI interface can be used to connect the processor 110 and peripheral devices such as the camera 120. The MIPI interface includes a camera serial interface (CSI), a display serial interface (DSI), and the like. In some embodiments, the processor 110 and the camera 120 communicate through the CSI interface to implement the photographing function of the electronic device 100.

[0064] The GPIO interface can be configured by software. The GPIO interface can be configured as a control signal or as a data signal. In some embodiments, the GPIO interface can be used to connect the processor 110 and the camera 120, and the like. The GPIO interface can also be configured as an I2C interface, a MIPI interface, and the like.

[0065] The USB interface 130 is an interface that complies with the USB standard specification, and can be a Mini USB interface, a Micro USB interface, a USB Type C interface, and the like. The USB interface 130 can be used to connect a charger to charge the electronic device 100, or to transmit data between the electronic device 100 and a peripheral device.

[0066] It can be understood that the interface connection relationship between the modules shown in the embodiments of the present application is only illustrative and does not constitute a structural limitation of the electronic device 100. In some other embodiments of the present application, the electronic device 100 can also use different interface connection methods or combinations of multiple interface connection methods as described in the above embodiments.

[0067] The electronic device 100 can implement the function of locating an object through an ISP, a camera 120, a pressure sensor 150A, a touch sensor 150B, a video codec, a GPU, a display 160, and an application processor, and the like.

[0068] The ISP is used to process data fed back by the camera 120. For example, when taking a picture, the shutter is opened, the light is transmitted to the camera photosensitive element through the lens, the light signal is converted into an electrical signal, and the camera photosensitive element transmits the electrical signal to the ISP for processing to convert it into an image visible to the naked eye. The ISP can also optimize the algorithm for noise, brightness, and skin color of the image. The ISP can also optimize the exposure, color temperature, and other parameters of the shooting scene. In some embodiments, the ISP can be provided in the camera 120.

[0069] The camera 120 is configured to capture still images or videos of the collection area and the target object in the collection area. The object projects an optical image through the lens to the photosensitive element. The photosensitive element can be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal, which is then transmitted to the ISP to be converted into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into a standard image signal in RGB, YUV, or the like. In some embodiments, the electronic device 100 can include one or N cameras 120, where N is a positive integer greater than 1.

[0070] In some embodiments of the present application, the camera 120 is configured to collect an image in which the locating pixels of the target object represent the position of the target object in the physical space.

[0071] The processor 110 is configured to determine the locating pixels of the target object in the image collected by the camera 120, and determine a target pixel set corresponding to the pixel coordinate of the locating pixels. Then, according to the mapping relationship between the target pixel set and the grid of the physical space, the geographical location information of the grid of the physical space corresponding to the locating pixels is determined, and the geographical location information corresponding to the locating pixels is sent to the display screen 160 for display, so as to realize the positioning of the target object.

[0072] The video codec is configured to compress or decompress digital videos. The electronic device 100 can support one or more video codecs. In this way, the electronic device 100 can play or record videos in multiple encoding formats, such as moving picture experts group (MPEG) 1, MPEG 2, MPEG 3, MPEG 4, and the like.

[0073] The NPU is a neural-network (NN) computing processor that can quickly process input information by referring to the structure of a biological neural network, such as the transmission mode between human brain neurons, and can also continuously self-learn. Through the NPU, the electronic device 100 can implement intelligent cognition applications, such as image recognition, face recognition, voice recognition, text understanding, and the like.

[0074] The memory 140 can be used to store computer-executable program code including instructions. The memory 140 can include a program storage area and a data storage area. The program storage area can store an operating system, application programs (such as a sound play application, an image play application, etc.) required by at least one function, etc. The data storage area can store data (such as audio data, a phone book, etc.) created during use of the electronic device 100, etc. In addition, the memory 140 can include a high-speed random access memory and can further include a nonvolatile memory such as at least one of a magnetic disk storage device, a flash memory device, a universal flash storage (UFS), etc. The processor 110 executes various function applications and data processing of the electronic device 100 by running instructions stored in the memory 140 and / or instructions stored in a memory disposed in the processor.

[0075] The pressure sensor 150A is used to sense a pressure signal and can convert the pressure signal into an electrical signal. In some embodiments, the pressure sensor 150A can be disposed in the display screen 160. There are many types of pressure sensors 150A, such as a resistive pressure sensor, an inductive pressure sensor, a capacitive pressure sensor, etc. A capacitive pressure sensor can include at least two parallel plates having a conductive material. When a force is applied to the pressure sensor 150A, the capacitance between the electrodes changes. The electronic device 110 determines the intensity of the pressure according to the change in capacitance. When a touch operation is applied to the display screen 160, the electronic device 110 detects the intensity of the touch operation according to the pressure sensor 150A. The electronic device 110 can also calculate the position of the touch according to the detection signal of the pressure sensor 150A. In some embodiments, touch operations applied to the same touch position but with different touch operation intensities can correspond to different operation instructions. For example, when a touch operation with an intensity less than a first pressure threshold is applied to a target object in a first image, a target object selection operation instruction is executed.

[0076] The touch sensor 150B, also referred to as a "touch device". The touch sensor 150B can be disposed in the display screen 160, and the touch sensor 150B and the display screen 160 form a touch screen, also referred to as a "touch screen". The touch sensor 150B is used to detect a touch operation applied thereto or in the vicinity thereof. The touch sensor can pass the detected touch operation to the application processor to determine the touch event type. Visual output related to the touch operation can be provided through the display screen 160. For example, when the touch sensor detects a touch operation on a target object in a first image, the application processor responds to the touch operation and executes an identification operation on the target object. In other embodiments, the touch sensor 150B can also be disposed on the surface of the electronic device 110, which is different from the position of the display screen 160.

[0077] The display screen 160 is configured to display images, videos, geographical position information of the target object, and the like. The display screen 160 includes a display panel. The display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light emitting diode (AMOLED), a flex light-emitting diode (FLED), a Miniled, a MicroLed, a Micro-oLed, a quantum dot light emitting diodes (QLED), or the like. In some embodiments, the electronic device 110 can include one or N display screens 160, where N is a positive integer greater than 1.

[0078] It should be noted that the electronic device 100 can be a desktop computer, a laptop computer, a mobile phone, a tablet computer, a wireless terminal, an embedded device, a chip system, or a device with a similar structure. In addition, the electronic device 100 can be a device with a different structure. Figure 1 It should be noted that the electronic device 100 can be a desktop computer, a laptop computer, a mobile phone, a tablet computer, a wireless terminal, an embedded device, a chip system, or a device with a similar structure. In addition, the electronic device 100 can be a device with a different structure. Figure 1 It should be noted that the electronic device 100 can be a desktop computer, a laptop computer, a mobile phone, a tablet computer, a wireless terminal, an embedded device, a chip system, or a device with a similar structure. In addition, the electronic device 100 can be a device with a different structure. Figure 1 It should be noted that the electronic device 100 can be a desktop computer, a laptop computer, a mobile phone, a tablet computer, a wireless terminal, an embedded device, a chip system, or a device with a similar structure. In addition, the electronic device 100 can be a device with a different structure.

[0079] In the embodiments of the present application, the chip system can be composed of a chip, or can include a chip and other discrete devices.

[0080] As shown in the above-mentioned embodiments, the positioning system 200 can include an electronic device 210 and at least one camera 220. The camera 220 can be the camera 120 in the above-mentioned embodiments, and the implementation functions are not repeated here. The electronic device 210 can include the processor 110, the universal serial bus (USB) interface 130, the memory 140, the sensor module 150, the display screen 160, and the like in the above-mentioned embodiments. The related content of each component is described in detail in the above-mentioned embodiments, and is not repeated here. Figure 2

[0081] In addition, in some embodiments of the present application, the electronic device 210 can further include a wireless communication module, an antenna, and the like.

[0082] ​The wireless communication module can provide a wireless communication solution including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) network), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared technology (IR), and the like, which is applied to the electronic device 210. The wireless communication module can be one or more devices integrated with at least one communication processing module. The wireless communication module receives electromagnetic waves via an antenna, frequency-modulates and filters the electromagnetic wave signals, and transmits the processed signals to the electronic device 210. The wireless communication module can also receive signals to be transmitted from the processor, frequency-modulate them, amplify them, and radiate them as electromagnetic waves via the antenna.

[0083] In some embodiments, the antenna is coupled to the wireless communication module so that the electronic device 210 can communicate with a network and other devices (such as the camera 220) via wireless communication technologies. The wireless communication technologies may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), wideband code division multiple access (WCDMA), time-division code division multiple access (TD-SCDMA), long term evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR technology. The GNSS may include global positioning system (GPS), global navigation satellite system (GLONASS), Beidou navigation satellite system (BDS), quasi-zenith satellite system (QZSS) and / or satellite based augmentation system (SBAS).

[0084] It should be understood that the structures illustrated in the embodiments of the present application do not constitute a specific limitation on the electronic device 210. In other embodiments of the present application, the electronic device 210 may include more or fewer components than shown, or may combine or separate certain components, or arrange the components differently. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0085] like Figure 3 As shown, the positioning system 300 may include at least one camera 310, a server 320, and an electronic device 330. The camera 310 may be the camera 120 described in the above embodiment, and its implementation functions are not further described. The server 320 may include the processor 110, the universal serial bus (USB) interface 130, the memory 140, and other components described in the above embodiment. The details of each component are described in the above embodiment and are not further described here.

[0086] The electronic device 330 can include the display 160 and the sensor module 150 in the above embodiments. The electronic device 330 can be configured to perform a selection operation of the target object in response to a click operation on the target object in the first image. The electronic device 330 can also be configured to display geographical location information of the target object, such as "the target object is located in XX country XX province XX city XX district XXX street", according to the geographical location information corresponding to the first positioning pixel obtained by the server 320.

[0087] Of course, in some embodiments of the present application, the server 320 can include the processor 110, the universal serial bus (USB) interface 130, the memory 140, the display 160, and the sensor module 150 in the above embodiments. The server 320 can be configured to perform a selection operation of the target object in response to a click operation on the target object in the first image. The details of the components in the server 320 are described in the above embodiments, and will not be repeated here.

[0088] The electronic device 330 can include the display 160 in the above embodiments. The electronic device 330 can be configured to display geographical location information of the target object, such as "the target object is located in XX country XX province XX city XX district XXX street", according to the geographical location information corresponding to the first positioning pixel obtained by the server 320.

[0089] In addition, in some embodiments of the present application, the server 320 can further include a wireless communication module, an antenna, and the like.

[0090] The wireless communication module can provide a wireless communication solution applied to the server 320, including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) network), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared technology (IR), and the like. The wireless communication module can be one or more devices integrated with at least one communication processing module. The wireless communication module receives electromagnetic waves via an antenna, performs frequency modulation and filtering processing on the electromagnetic wave signals, and sends the processed signals to the server 320. The wireless communication module can also receive signals to be sent from the processor, perform frequency modulation, amplification, and convert the signals to electromagnetic wave radiation via the antenna.

[0091] In some embodiments, the antenna is coupled to the wireless communication module so that the server 320 can communicate with the network and other devices (such as the camera 310 and the electronic device 330) via wireless communication technologies. The wireless communication technologies may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), wideband code division multiple access (WCDMA), time-division code division multiple access (TD-SCDMA), long-term evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR technology. The GNSS may include global positioning system (GPS), global navigation satellite system (GLONASS), Beidou navigation satellite system (BDS), quasi-zenith satellite system (QZSS) and / or satellite-based augmentation system (SBAS).

[0092] It should be noted that the electronic device 330 can be a desktop computer, a portable computer, a mobile phone, a tablet computer, or a wireless terminal system. Figure 3 The structure shown in the figure does not constitute a limitation of the positioning system, except Figure 3 In addition to the components shown, the positioning system may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0093] Below is Figure 3 Taking the architecture shown in the figure as an example, the positioning method provided by the embodiment of the present application is described. Each network element in the following embodiment may have Figure 3The components shown are not described again. It should be noted that the message names or parameter names in the messages exchanged between various devices in the embodiments of the present application are only examples, and other names can also be used in specific implementation. For example, the positioning pixels described in the embodiments of the present application can be replaced by anchor points, positioning points, etc. The determination in the embodiments of the present application can also be understood as creation or generation, and the "includes" in the embodiments of the present application can also be understood as "carries", which are uniformly described here. The embodiments of the present application do not make specific limitations.

[0094] Figure 4 A flowchart of a positioning method provided in the embodiments of the present application is shown in Figure 4 The method can include the following steps:

[0095] Step 401, the server determines the positioning pixel of the target object in the image.

[0096] The image can be obtained by the camera collecting the target object in the collection area. The image can be a photo or a video.

[0097] The positioning pixel is used to represent the position of the target object in the image. In other words, the positioning pixel is the pixel of the target object in the image. For example, the positioning pixel can be the center pixel of the bounding box of the target object in the image, which can be understood as the pixel corresponding to the geometric center point of the bounding box of the target object. The positioning pixel can also be any pixel on the bounding box of the target object in the image.

[0098] In a specific implementation, the step can be specifically implemented as: step 4011, the server determines the pixel coordinates of the reference pixel of the target object in the image according to the type of the target object, and the reference pixel is used to determine the pixel coordinates of the positioning pixel of the target object in the image. The type of the target object can refer to the category of the target object, which is used to indicate which object the target object is. For example, the type of the target object can be a pedestrian or a vehicle.

[0099] For example, the camera 1 collects an image and sends it to the server 2. The server 2 receives the image collected by the camera 1, and the image is displayed on the display screen of the electronic device 3. When the electronic device 3 detects a click operation on the target object A on the image, or the electronic device 3 detects that the cursor (such as the arrow shown in Figure 5 When the electronic device 3 detects a click operation on the target object A on the first image, the electronic device 3 performs the operation of selecting the target object A in response to the operation, and displays the selection area of the target object A (such as the rectangle shown in Figure 6The outline of the target object A shown). The electronic device 3 sends the information of the selected target object A to the server 2, the server 2 determines the type of the target object A according to the information of the target object A, and determines the pixel coordinates of the reference pixel of the target object A in the image. The server 2 determines the pixel coordinates of the locating pixel of the target object A according to the pixel coordinates of the reference pixel.

[0100] In example 1, if the type of the target object is a vehicle, the server determines the pixel coordinates of the reference pixel of the vehicle in the image, the height value and the width value of the vehicle; and determines the pixel coordinates of the locating pixel of the vehicle in the image according to the pixel coordinates of the reference pixel, the height value and the width value of the vehicle.

[0101] Suppose, as shown in Figure 7 , the pixel coordinates of the locating pixel Q0 are (xc, yc), the width value is w, and the height value is h.

[0102] Since the vehicle is a cuboid structure, the top-left corner point Q1 of the vehicle can be determined as the first reference pixel, and the pixel coordinates of the first reference pixel are (topx, topy) ; the bottom-right corner point Q2 of the vehicle can be determined as the second reference pixel, and the pixel coordinates of the second reference pixel are (bottomx, bottomy).

[0103] The server determines the pixel coordinates (xc, yc) of the locating pixel according to the pixel coordinates (topx, topy) of the first reference pixel of the vehicle, the pixel coordinates (bottomx, bottomy) of the second reference pixel of the vehicle, the width value w of the vehicle, and the height value h of the vehicle. In actual implementation, the following relationships can be met: topx = xc - 0.5 * w, topy = yc - 0.5 * h, bottomx = xc + 0.5 * w, and bottomy = yc + 0.5 * h.

[0104] Of course, the above embodiments only represent one implementation, and other implementations can also exist, and the embodiments of the present application will not be listed one by one.

[0105] In example 2, if the type of the target object is a pedestrian, the server determines the pixels corresponding to the feet of the pedestrian in the image as the reference pixels, and determines the locating pixel according to the pixels corresponding to the feet of the pedestrian in the image.

[0106] For example, as shown in Figure 8As shown, the server can determine that the pixel corresponding to the right foot of the pedestrian in the image as the first reference pixel, and the pixel corresponding to the left foot of the pedestrian in the image as the second reference pixel. Assuming that the pixel coordinates of the first reference pixel P1 are (X1, Y1), and the pixel coordinates of the second reference pixel P2 are (X2, Y2). The server can determine the positioning pixel P0 of the pedestrian as (X0, Y0). The positioning pixel P0 can be the middle point of the connecting line of the contact points of the left foot and the right foot with the ground, and in actual implementation, the following relationship can be satisfied: X0 = 0.5 * (X2 - X1), Y0 = 0.5 * (Y2 - Y1).

[0107] Of course, the server can also determine the center pixel of the pedestrian from the head to the foot in the image as the reference pixel. The pixel coordinates of the center pixel can be the pixel coordinates of the positioning pixel, or the pixel coordinates of the positioning pixel can be calculated according to other algorithms.

[0108] Of course, since the postures of pedestrians are various, the above-mentioned embodiments only represent one implementation mode, and other implementation modes can also exist according to different postures of pedestrians, and the embodiments of the present application will not be listed one by one.

[0109] In some embodiments, before determining the pixel coordinates of the reference pixel of the target object in the image according to the type of the target object, the positioning method provided by the embodiments of the present application further includes: the server determines the type of the target object. In a specific implementation mode, determining the type of the target object can be specifically implemented as: the server inputs the image and the sample image of the first real object into a deep learning model, outputs the confidence degree that the target object in the image is the first real object, and in the case that the confidence degree is greater than or equal to a threshold value, determines that the target object is the first real object, that is, determines the type of the target object. The confidence degree is used to represent the confidence degree that the target object in the image is the first real object. The deep learning model is trained according to the image and the sample image of the first real object. The threshold value can be set according to requirements, such as 96%, 85%, or 92%.

[0110] Step 402, the server determines the grid of the physical space corresponding to the positioning pixel according to the target pixel set corresponding to the positioning pixel and the mapping relationship between the target pixel set and the grid of the physical space.

[0111] The physical space can be a collection region corresponding to the image photographed by the camera at the first geographical position coordinate and in the first pose. The pose parameters of the camera can include the geographical position coordinate of the camera, the pitch angle, the roll angle and the side view angle of the camera. The first geographical position coordinate and the first pose of the camera can be determined according to the feature points in the image and the corresponding geographical position coordinates. The first pose of the camera can be determined according to the feature points in the image and the corresponding geographical position coordinates by using various methods, such as direct linear transformation method or PnP method.

[0112] In an implementable manner, the server extracts a feature point in the sample image, and determines the pixel coordinates and the geographical position coordinates corresponding to the feature point. The server determines the first pose of the camera according to the pixel coordinates and the geographical position coordinates corresponding to the feature point. For example, the first pose of the camera is calculated by a direct linear transformation method:

[0113] Suppose the geographical position coordinates of the target object P in the physical space are P = (X, Y, Z, 1) T , and the pixel coordinates of the feature point corresponding to the target object in the sample image are x1 = (u1, v1, 1) T (normalized plane homogeneous coordinates), and the first pose of the camera is R and t. The rotation and translation matrix composed of R and t is denoted as [R|t], which is a 3x4 matrix. Then the geographical position coordinates of the target object in the physical space, the pixel coordinates of the target object in the sample image, and the first pose of the camera satisfy the following relationship:

[0114]

[0115] where s is the depth information of the P point from the camera optical center, is the expansion expression of the determinant of [R|t].

[0116] Eliminate s, and the above expression (1) is transformed into the following two expressions:

[0117]

[0118]

[0119] Suppose there are N feature points, and a linear equation system can be listed:

[0120]

[0121] Since formula (2) has 12 unknowns, the server determines the pixel coordinates and the geographical position coordinates corresponding to at least six feature points in the sample image, so as to realize linear solution of the matrix [R|t], and thus determine the first pose of the camera. When the number of matching points is greater than six pairs, the least square solution of the overdetermined equation can be obtained by using singular value decomposition (SVD) and the like, which will not be described herein.

[0122] For example, the first pose of the camera is calculated by the PnP (such as P3P) method. The P3P method is based on the fact that the spatial distribution of points remains unchanged in different camera coordinate systems, and the principle of similar triangles. The P3P method has the feature that the server needs to extract the pixel coordinates and the geographical position coordinates of three groups of feature points for calculation, and then extract the pixel coordinates and the geographical position coordinates of one group of feature points for verification, so as to select the correct solution. The specific process is as follows:

[0123] As Figure 9 shown, assuming the optical center point of the camera is O, the target object A, the target object B and the target object C in the physical space, and the corresponding feature points in the sample images are feature point a, feature point b and feature point c respectively, three sets of similar triangles can be obtained: ΔOab ~ ΔOAB, ΔOac ~ ΔOAC, ΔObc ~ ΔOBC.

[0124] Using the cosine theorem, the following relationship can be obtained:

[0125] OA 2 +OB 2 -2OA*OB*cos(a,b)=AB 2

[0126] OA 2 +OC 2 -2OA*OC*cos(b,c)=AC 2

[0127] OB 2 +OC 2 -2OB*OC*cos(c,a)=BC 2

[0128] Assuming x=OA / OC, y=OB / OC, u=BC 2 / AB 2 , w=AC / AB, the above relationship can be transformed into:

[0129] (1-u)y 2 -ux 2 -ycos(b,c)+2uxycos(a,b)+1=0

[0130] (1-w)x 2 -wy 2 -xcos(a,c)+2wxycos(a,b)+1=0

[0131] The equation set is a binary quadratic equation about x and y, which can be solved by elimination method. Then, the pixel coordinates and the geographic position coordinates of a set of feature points extracted by the server are used for verification, so as to obtain the first pose of the camera.

[0132] After obtaining the first pose of the camera by the method described in the above embodiment, the server can determine the pitch angle, the roll angle and the side view angle of the camera, and the height of the viewpoint center of the camera relative to the ground, and the geographic position coordinates of the viewpoint center. As Figure 11As shown, assuming the parameters of the camera are C={X, Y, Z, ω, θ, γ}, where (X, Y, Z) represents the geographic position coordinates of the camera, ω represents the pitch angle of the camera, θ represents the roll angle of the camera, and γ represents the side view angle of the camera. The server can determine the size of the collection area A when the camera is in the first pose according to the parameters of the camera.

[0133] In some embodiments of the present application, the positioning method provided by the embodiments of the present application can further include: step 403, the server grids the physical space to obtain various grids of the physical space. That is, the server grids the collection area (such as the area A shown in the figure) when the camera is in the first pose to obtain various grids of the collection area. In a specific implementation, the physical space can be divided into any level according to the Discrete Global Grid (DGG) subdivision rule according to actual needs, so as to obtain various grids of the physical space. For example, the physical space can be divided into the 20th level, and the edge length of each grid is 2.26 m. Since the DGG is a kind of quasi-regular grid of the earth body that can be infinitely subdivided without changing the shape of the sphere (or ellipsoid), when subdivided to a certain extent, the purpose of simulating the earth's surface can be achieved. Moreover, the DGG has the characteristics of hierarchy and global continuity. Therefore, the physical space in the embodiments of the present application is divided into grids by using the DGG subdivision rule, which not only avoids the angle, length and area distortion caused by projection and the discontinuity of spatial data, but also overcomes many constraints and uncertainties of geographic information system (GIS) applications, so that spatial data of any resolution (different accuracy) obtained at any position on the earth can be standardized to express and analyze, and can be operated at a certain accuracy, and the earth's surface can be accurately simulated. Figure 11

[0134] Among them, the grid can be a triangular grid, a quadrilateral grid, a hexagonal grid, a degenerate quadtree grid, a spherical latitude-longitude subdivision grid GeoSOT, etc.

[0135] Among them, the grid of the physical space is used to represent geographic position information, which can include geographic position coordinates or global position encoding. In a specific implementation, taking the example that the geographic position information includes global position encoding, the global position encoding of each grid of the physical space is determined, which can be specifically implemented as follows:

[0136] Step 1, determine the latitude and longitude coordinates of the center point of each grid of the physical space, and the latitude and longitude coordinates of the center point are expressed in degrees, minutes, seconds and decimal seconds. For example, the latitude and longitude coordinates of the center point are expressed as A°B′C.D″. ​

[0137] Step 2, the longitude and latitude coordinates of the center point are converted into binary numbers in sequence according to degrees, minutes, seconds and decimal seconds to obtain longitude binary number and latitude binary number.

[0138] Specifically, degrees |A| is converted from a decimal number into an 8-bit fixed-length binary number (A) 2, minutes B is converted from a decimal number into a 6-bit fixed-length binary number (B) 2, seconds C is converted from a decimal number into a 6-bit fixed-length binary number (C) 2, and decimal seconds D is converted from a decimal number into an 11-bit fixed-length binary number (D) 2.

[0139] Step 3, the longitude binary number is prefixed, the latitude binary number is suffixed, and a Minterm algorithm is used to obtain a binary mixed code, and the binary mixed code is converted into a quaternary code.

[0140] Specifically, (A) 2, (B) 2, (C) 2 and (D) 2 obtained are directly spliced into a 31-bit fixed-length binary number (E) 2 in sequence, i.e. (E) 2 = (A) 2 (B) 2 (C) 2 (D) 2, to obtain two 31-bit fixed-length numbers of longitude (EL) 2 and latitude (EB) 2; secondly, the latitude (EB) 2 is prefixed, the longitude (EL) 2 is suffixed, and a Minterm algorithm is used to generate a 62-bit mixed code (F) 2, for example, if (EB) 2 is 100111 and (EL) 2 is 011010, (EB) 2 is prefixed and (EL) 2 is suffixed, and a Minterm algorithm is used to obtain a binary mixed code (F) 2 of 100101101110; finally, the binary mixed code (F) 2 is converted into a quaternary code (F) 4, and according to the level m of the grid to be solved, the last 32m quaternary symbols in (F) 4 are removed to obtain (F') 4.

[0141] Step 4, according to the encoding of the region to which the center point of each grid of the physical space belongs in the coordinate system, the level of each grid of the physical space and the quaternary code, the global position code of each grid of the physical space is determined.

[0142] Specifically, according to the longitude and latitude, the global position code of each grid can be obtained by adding G0, G1, G2 or G3 in front of (F') 4 according to the arrow direction shown in the following formula. Figure 10

[0143] Of course, other implementation manners can also be used, and the embodiments of the application are not limited in this regard.

[0144] After the server grids the region A to obtain each grid of the physical space, the server determines the geographic position information of the corner points of each grid of the physical space according to the planar position and geographic terrain data of region A. ​

[0145] Example 3: The server determines the acquisition area when the camera is in the first pose according to the camera parameters (such as Figure 11 After that, the server divides the area A into multiple grids {A1, A2, ..., A N}, where the DGG code of each grid is A codei , the corner point is {a i1 ,a i2 ,…,a im}(m≥3, corner point a i1 ,a i2 ,…,a im Arrange in clockwise or counterclockwise order of the grid). Assume that {a i1 ,a i2 ,…,a iM} represents the set of corner points of the ith grid, then C represents the set of all grid corner points in area A, and C={c1,c2,…,c K The server obtains the three-dimensional coordinate positions of all grid corner points in C based on the plane position and geographical terrain data of area A, which is recorded as P = {P c1 ,P c2 ,…,P cK}. Among them, P cj ={x cj ,y cj ,z cj}(j=1,....,K).

[0146] In some embodiments of the present application, after the server grids the physical space to obtain each grid of the physical space, the positioning method provided by the embodiment of the present application may also include: step 404, the server determines each pixel set in the image based on the grid of the physical space and the parameter information of the camera, wherein the pixels in each pixel set correspond to the points on the grid of the physical space, and the camera is used to collect images. The parameter information of the camera may include focal length, main image point position, video CCD size and posture parameters. The parameter information of the camera can be determined based on the feature points in the image and their corresponding geographic location coordinates. For details on the specific implementation method, please refer to the relevant content in the above embodiment, and the embodiment of the present application will not be repeated.

[0147] In one achievable manner, step 404 may be specifically implemented as follows:

[0148] Step 4041: The server determines the pixel coordinates corresponding to each of the multiple corner points in the image based on the geographic coordinates of the multiple corner points of the grid in the physical space, the projection matrix, the focal length of the camera, and the geographic coordinates of the viewpoint center.

[0149] The projection matrix is used to represent the conversion relationship between the pixel coordinates of the pixels in the image and the geographical position coordinates of the corner points on the grid in the physical space. The projection matrix can be determined according to the world coordinate system and the angle of the camera in the world coordinate system, or the geographical position coordinates of a plurality of sample points in a local area are converted into the geographical position coordinates in the world coordinate system after translation and rotation, and the same conversion relationship matrix used in the conversion process is the projection matrix. The projection matrix in the embodiment of the application is the same as the first pose of the camera in the above embodiment, so the method for obtaining the projection matrix is the same as described above, and will not be described here.

[0150] Example 4, step 4041 can be implemented using the following expression: continuing with example 3, assuming that the three-dimensional position coordinates of all the grid corner points in the corner point set C of the region A are P cj cj cj cj (j = 1, …, K), and the geographical position coordinates of the viewpoint center of the camera are (c x y , which can be determined according to the parameter information of the camera.

[0151] And the focal length of the camera is fx (the focal length of the camera in the x direction) and fy (the focal length of the camera in the y direction), and the projection matrix is Then the server can obtain the pixel coordinates of the pixels corresponding to the grid corner points on the image according to the above parameters as

[0152] The expression can be:

[0153]

[0154] Because the lens of the camera usually has some deformation, in addition, it is considered that the camera can be a special camera, such as a fisheye camera. Therefore, the image collected by the camera will be distorted compared with the ideal image. When the positioning pixels of the target object in the distorted image are used to locate the target object, the positioning will be inaccurate.

[0155] In order to solve this problem, in one implementation, after step 4041 is performed, the positioning method provided by the embodiment of the application can further include: step 4043, the server determines the corrected pixel coordinates of each pixel in the image according to the pixel coordinates of each pixel in the image, and the radial distortion coefficient and / or the tangential distortion coefficient, and the corrected pixel coordinates are used to determine the pixel set to which each pixel in the image belongs.

[0156] ​​​​​In a specific implementation, after the server obtains the pixel coordinates of the plurality of distorted pixels in the image, the server determines the corresponding pixels of the distorted image and the non-distorted image according to the parameter matrix and the distortion coefficient vector of the camera, and uses the function cvInitUndistortMap to pre-calculate the pixel coordinates of each pixel in the non-distorted corresponding-correct image in the distorted image, and then calculates the pixel coordinates of the distorted pixels in the output image by bilinear interpolation, so as to offset the radial and tangential lens distortion by transforming the image.

[0157] The parameter matrix and the distortion coefficient vector of the camera can be obtained by using the function cvCalibrateCamera2.

[0158] In Example 5, the pixel coordinates corresponding to the grid corner points on the image obtained by the server in Example 4 are The pixel coordinates are the pixel coordinates of the distorted pixels.

[0159] For example, in the case of radial distortion, the radial distortion coefficient vector is [k1, k2, k3], and the pixel coordinates of the corrected pixels are (u cj ,v cj ), the pixel coordinates of the distorted pixels and the pixel coordinates of the corrected pixels can satisfy the following expression:

[0160]

[0161]

[0162]

[0163] The embodiments of the present application can effectively prevent the positioning pixels of the target object in the distorted image from positioning the target object, and improve the accuracy of the positioning of the target object.

[0164] Since the number of corner points on the grid in the physical space is limited, the mapping relationship between the corner points of the grid and the pixels on the image is established, so that the area formed by mapping the grid in the physical space to the image is not accurate. In order to accurately map the grid in the physical space to the image, in one implementation, the step 4041 in the present application can be implemented as follows: determining the pixel coordinates of each pixel in the image according to the geographical position coordinates of at least one sampling point and a plurality of corner points on each side of a grid in the physical space, the projection matrix, the focal length of the camera, and the geographical position coordinates of the center of the view point.

[0165] The sampling point can be any point on the line connecting the first corner point and the second corner point, and the coordinates of the sampling point satisfy the linear equation of the first corner point and the second corner point, wherein the first corner point and the second corner point are two adjacent corner points.

[0166] Example 6, as in example 3, the server divides the region A into a plurality of grids {A1, A2, …, A N} according to the rules of the DGG, wherein the DGG code of each grid is A codei , and the corner points are {a i1 , a i2 , …, a im} (m≥3, the corner points a i1 , a i2 , …, a im are arranged in clockwise or counterclockwise order according to the grid).

[0167] On the basis of the above, the edges of each grid are denoted as {edge i1-i2 , edge i2-i3 , …, edge im-i1}, and interpolation sampling is performed for each edge to obtain more points on the edge.

[0168] Without loss of generality, taking edge i1-i2 as an example, the server can determine the linear equation determined by the two corner points (x i1 , y c1 ) and (x c1 , y i2 ) according to the first corner point a c2 , whose position coordinates are (x c2 , y c1 ), and the second corner point a c1 , whose position coordinates are (x c2 , y c2 ). The server samples n (n≥1) sampling points in the interval [x c1 , x c2 ], and calculates the y values of the n sampling points according to y=f(x). Since each edge increases n sampling points {b1, b2, …, b n}, each grid increases N*n sampling points. The server further processes the N*n sampling points added to each grid in the same manner as the corner points (see the corresponding content in the above embodiments), and determines the pixel coordinates of each pixel corresponding to the N*n sampling points in the image.

[0169] The server obtains the pixel coordinates of each pixel corresponding to the N*n sampling points, and the pixel coordinates of each pixel corresponding to each corner point, and thus obtains the pixel coordinates of each pixel in the image.

[0170] The embodiment of the present application adds at least one sampling point on the edge of the grid of the physical space, and determines each pixel in the image through the at least one sampling point and the corner point of the grid, so that the area of the grid of the physical space mapped on the image is closer to itself, thereby realizing more fine projection expression of the grid of the physical space on the image. In addition, the mapping relationship between the corner point and / or the sampling point of the grid of the physical space and the pixel of the image is established, the grid projection expression of the physical space is effectively and accurately realized, the influence of the terrain on the positioning accuracy is reduced, and the large-scale grid positioning accuracy is improved.

[0171] In step 4042, the server determines a target polygon surrounded by each pixel in the image according to the pixel coordinates of each pixel in the image and the association relationship between the plurality of corner points. The pixels surrounded by the target polygon, or the pixels surrounded by the target polygon and the pixels on the edge of the target polygon are used to construct the pixel set.

[0172] If the image captured by the camera is distorted, the server determines the corrected pixel coordinates of each pixel in the image according to the pixel coordinates of each pixel in the image, and the radial distortion coefficient and / or the tangential distortion coefficient. The server determines a target polygon surrounded by each pixel in the image according to the corrected pixel coordinates of each pixel in the image and the association relationship between the plurality of corner points.

[0173] This step can be specifically implemented in that the server determines that each corner point in the plurality of corner points corresponds to each pixel in the plurality of pixels one by one, that is, the plurality of corner points of one grid are arranged in the clockwise or counterclockwise order of the grid, and that each pixel can be arranged and connected in the arrangement order of the plurality of corner points to obtain a target polygon. The pixels surrounded by the target polygon can be used to construct the pixel set. The pixels surrounded by the target polygon and the pixels on the edge of the target polygon can be used to construct the pixel set.

[0174] In an implementation manner, if the pixel coordinates of each pixel in the image are determined based on the geographical position coordinates of at least one sampling point on each edge of one grid in the physical space and the plurality of corner points, the projection matrix, the focal length of the camera, and the geographical position coordinates of the viewpoint center, this step can be specifically implemented in that the server determines that each corner point corresponds to each pixel one by one according to the correspondence relationship between the corner points and the pixels, and that the plurality of corner points and the plurality of sampling points of one grid are arranged in the clockwise or counterclockwise order of the grid. Each pixel can be arranged and connected in the arrangement order of the plurality of corner points and the plurality of sampling points to obtain a target polygon. The pixels surrounded by the target polygon can be used to construct the pixel set. The pixels surrounded by the target polygon and the pixels on the edge of the target polygon can be used to construct the pixel set.

[0175] It should be noted that pixels on the same side of two adjacent target polygons can be randomly assigned to the pixel set corresponding to either target polygon. Pixels on the same side of two adjacent target polygons can also be assigned according to a priority rule, such as the left side taking precedence over the right side, or the top side taking precedence over the bottom side.

[0176] For example, take the allocation according to the priority rule as an example, Figure 12 As shown, it is assumed that the first target polygon 1 is adjacent to the second target polygon 2, and the first target polygon 1 is located to the left of the second target polygon 2. The second target polygon 2 is adjacent to the third target polygon 3, and the second target polygon 2 is located above the third target polygon 3. Among them, the first side L1 is a common side between the first target polygon 1 and the second target polygon 2. The pixels a on this side can be allocated to the pixel set corresponding to the first target polygon 1 according to the allocation rule that the left side takes precedence over the right side. The second side L2 is a common side between the second target polygon 2 and the third target polygon 3. The pixels b on this side can be allocated to the pixel set corresponding to the second target polygon 2 according to the allocation rule that the upper side takes precedence over the lower side.

[0177] The server then uses the method described in the preceding embodiment to obtain a set of pixels that map the physical space grid to the image. The server then assigns the geographic location information represented by the physical space grid to the set of pixels corresponding to the grid. After obtaining the correspondence between the pixel set and the geographic location information, the server constructs a geographic location index table indexed by the pixels.

[0178] Example 7: Using Example 3, the server obtains the physical space grid A i The pixel coordinates of the corner points projected onto the image are {p i1 ,p i2 ,…,p im},in, By p i1 ,p i2 ,…,p im Points are connected to form a target polygon (such as Figure 11 As shown), the pixel set of the image contained in the target polygon is {p i1 ,p i2 ,…,p iL Since the physical space grid is used to represent the global position code A codei Therefore, the server determines that the global position code corresponding to the pixel set is A codei After the server obtains the correspondence between the pixel set and the global position code, it constructs a geographical location index table indexed by pixels, such as Index(p i1 )=A codei,Index(p i2 )=A codei ,…,Index(p iL )=A codei . As shown in Table 1.

[0179] Table 1

[0180]

[0181] Step 405: The server determines the geographic location information of the positioning pixel based on the geographic location information corresponding to the grid of the physical space corresponding to the positioning pixel.

[0182] In practical applications, such as Figure 13 As shown, it is assumed that the target object is in grid A in area A. i Corner point a i2 In image 1, the target pixel is P i2 , corner point a i2 With the positioning pixel P i2 The relationship is shown in Table 1.

[0183] Combine Figure 3 The positioning system shown in FIG. 3 is described in detail. The camera 310 captures image 1 and sends image 1 to the server 320. The server 320 receives image 1 captured by the camera 310 and sends image 1 to the electronic device 330 for display. When the electronic device 330 detects a click operation on a target object in the image, the electronic device 330 selects the target object in response to the operation on the target object in the image and displays the selected area of ​​the target object. The electronic device 330 sends the information of the selected target object to the server 320. The server 320 determines the type of the target object based on the information of the target object and determines the positioning pixel P of the target object in the image 1. i2 The server locates the pixel P i2 Determine the pixel set P to which the positioning pixel belongs i , which is the target pixel set, the server calculates the target pixel set P i The corresponding global position code determines the positioning pixel P i2 Corresponding to the global location code A codei The server will locate pixel P i2 and its corresponding global position code A codei The data is sent to the electronic device 330, and the display screen of the electronic device 330 displays the geographical location information of the target object (such as Figure 3 (the display result of the electronic device in the video).

[0184] Therefore, when the target object is positioned by using the positioning method provided in the embodiments of the present application, the server can determine the grid of the physical space corresponding to the positioning pixel according to the mapping relationship between the target pixel set corresponding to the positioning pixel of the target object in the image and the grid of the physical space, and the geographical position information represented by the grid is the geographical position information of the positioning pixel of the target object, so that the positioning of the target object can be realized, the table query is used to replace the pixel-by-pixel matching rendezvous, the calculation amount is reduced, the resource consumption is reduced, and the positioning efficiency is improved.

[0185] Figure 14 A positioning device is provided in the embodiments of the present application, and the positioning device 1400 can include:

[0186] A positioning pixel determination unit 1401 is configured to determine a positioning pixel of a target object in an image, and the positioning pixel is used to represent the position of the target object in the image.

[0187] A grid determination unit 1402 is configured to determine a grid of a physical space corresponding to the positioning pixel according to a target pixel set corresponding to the positioning pixel and a mapping relationship between the target pixel set and the grid of the physical space.

[0188] A geographical position information determination unit 1403 is configured to determine geographical position information of the positioning pixel according to the geographical position information corresponding to the grid of the physical space corresponding to the positioning pixel.

[0189] The target pixel set is obtained by dividing the image according to the grid of the physical space and parameter information of a camera used to collect the image.

[0190] The mapping relationship is determined according to the grid of the physical space to which the pixels in the target pixel set belong.

[0191] It should be noted that the physical space needs to be gridded in advance, and therefore the positioning device 1400 can include a physical space gridding unit 1407 configured to perform grid division on the physical space to obtain the grid of the physical space.

[0192] Further, the positioning device 1400 includes a pixel set determination unit, which includes:

[0193] A first pixel coordinate determination unit 1404 is configured to determine a pixel coordinate in the image corresponding to each of a plurality of corner points in the grid of the physical space according to geographical position coordinates of the plurality of corner points in the grid of the physical space, a projection matrix, and geographical position coordinates of a focal length and a viewpoint center of the camera, wherein the projection matrix is used to represent a conversion relationship between the pixel coordinates of the pixels in the image and the geographical position coordinates of the corner points on the grid of the physical space.

[0194] The target polygon determination unit 1405 is configured to determine a target polygon in the image according to pixel coordinates of each pixel in the image and a correlation between the plurality of corner points, wherein the target polygon surrounds the pixels or the target polygon surrounds the pixels and the pixels on the edges of the target polygon to form a pixel set.

[0195] Further, if the image captured by the camera is distorted, the positioning device 1400 comprises:

[0196] The second pixel coordinate determination unit 1406 is configured to determine corrected pixel coordinates of each pixel in the image according to the pixel coordinates of each pixel in the image and a radial distortion coefficient and / or a tangential distortion coefficient, wherein the corrected pixel coordinates are used to determine the pixel set to which each pixel in the image belongs.

[0197] Further, the first pixel coordinate determination unit 1404 comprises:

[0198] The first pixel coordinate determination sub-unit is configured to determine the pixel coordinates of each pixel in the image according to at least one sampling point on each edge of the grid in the physical space, geographical position coordinates of the plurality of corner points, the projection matrix, a focal length of the camera, and geographical position coordinates of a viewpoint center.

[0199] Further, the parameter information of the camera is determined according to feature points in a sample image and corresponding geographical position coordinates.

[0200] Further, the parameter information of the camera comprises a focal length, a principal point position, a video CCD size, and a pose parameter, wherein the pose parameter comprises geographical position coordinates of the camera, a pitch angle, a roll angle, and a side view angle.

[0201] Further, the geographical position information comprises a global position code or geographical position coordinates.

[0202] Further, the positioning pixel determination unit 1401 comprises:

[0203] The third pixel coordinate determination sub-unit is configured to determine pixel coordinates, a height value, and a width value of a reference pixel of the vehicle in the image if the type of the target object is a vehicle.

[0204] The fourth pixel coordinate determination sub-unit is configured to determine pixel coordinates of a positioning pixel of the vehicle in the image according to the pixel coordinates, the height value, and the width value of the reference pixel.

[0205] Specifically, in the possible design, the above Figures 1 to 13All relevant content of each step involving the electronic device in the method embodiment shown can be cited to the function description of the corresponding function module, which will not be repeated here. The electronic device described in this possible design is used to perform the function of the positioning method shown Figures 1 to 13 The function of the electronic device in the positioning method shown, so the same effect as the above positioning method can be achieved.

[0206] Figure 15 A positioning system provided by the embodiment of the present application, the positioning system 1500 can include: at least one camera 1501 and a positioning device 1502; wherein the camera 1501 is used to collect the first image of the target object located in the collection area and the second image of the collection area, and send the first image and the second image to the positioning device 1502. The positioning device 1502 is used to receive the first image and the second image collected by the camera 1501, and execute Figures 1 to 13 The positioning method shown.

[0207] Specifically, in the possible design, the above Figures 1 to 13 All relevant content of each step involving the positioning device in the method embodiment shown can be cited to the function description of the corresponding function module, which will not be repeated here. The electronic device described in this possible design is used to perform the function of the positioning method shown Figures 1 to 13 The function of the positioning device in the positioning method shown, so the same effect as the above positioning method can be achieved.

[0208] An electronic device provided by the embodiment of the present application, comprising: a processor and a memory, the memory is coupled with the processor, the memory is used to store computer program code, the computer program code includes computer instructions, when the processor reads the computer instructions from the memory, so that the electronic device executes Figures 1 to 13 The positioning method shown.

[0209] A computer program product provided by the embodiment of the present application, when the computer program product runs on the computer, so that the computer executes Figures 1 to 13 The positioning method shown.

[0210] A computer readable storage medium provided by the embodiment of the present application, including computer instructions, when the computer instructions run on the terminal, so that the network equipment executes Figures 1 to 13 The positioning method shown.

[0211] A chip system provided by the embodiment of the present application, including one or more processors, when the one or more processors execute instructions, the one or more processors execute Figures 1 to 13 The positioning method shown.

[0212] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0213] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0214] The units described as separate components may or may not be physically separate, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0215] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0216] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. According to this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a device (which can be a single-chip microcomputer, chip, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

[0217] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any change or replacement within the technical scope disclosed by the present application should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A positioning method, characterized by, The method comprises: determining a locating pixel of a target object in an image, the locating pixel being used to represent a position of the target object in the image; determining a grid of a physical space corresponding to the locating pixel according to a target pixel set corresponding to the locating pixel and a mapping relationship between the target pixel set and the grid of the physical space; determining geographical position information of the locating pixel according to geographical position information corresponding to the grid of the physical space corresponding to the locating pixel; the target pixel set is obtained by dividing the image according to the grid of the physical space and parameter information of a camera used to collect the image; and the parameter information of the camera is determined according to feature points in a sample image and corresponding geographical position coordinates of the feature points; wherein the mapping relationship is determined according to a grid of the physical space to which a pixel in the target pixel set belongs and the pixel on the image.

2. The method of claim 1, wherein, determining each pixel set in the image according to the grid of the physical space and the parameter information of the camera, comprising: determining pixel coordinates in the image corresponding to each of a plurality of corner points of the grid in the physical space according to geographical position coordinates of the plurality of corner points, a projection matrix, a focal length of the camera and geographical position coordinates of a view center of the camera, the projection matrix being used to represent a conversion relationship between pixel coordinates of the image and the geographical position coordinates of the corner points on the grid in the physical space; determining a target polygon in the image surrounded by the pixels according to the pixel coordinates of each pixel in the image and a correlation relationship between the plurality of corner points; wherein the pixels surrounded by the target polygon, or the pixels surrounded by the target polygon and the pixels on the edges of the target polygon, are used to construct a pixel set.

3. The method of claim 2, wherein, if the image collected by the camera is distorted, then after determining the pixel coordinates of each pixel in the image according to the geographical position coordinates of the plurality of corner points of the grid in the physical space, the projection matrix, the focal length of the camera and the geographical position coordinates of the view center of the camera, comprising: determining corrected pixel coordinates of each pixel in the image according to the pixel coordinates of each pixel in the image, a radial distortion coefficient and / or a tangential distortion coefficient, the corrected pixel coordinates being used to determine the pixel set to which each pixel in the image belongs.

4. The method of claim 2, wherein, determining the pixel coordinates of each pixel in the image according to the geographical position coordinates of the plurality of corner points of the grid in the physical space, the projection matrix, the focal length of the camera and the geographical position coordinates of the view center of the camera, comprising: determining the pixel coordinates of each pixel in the image according to the geographical position coordinates of at least one sampling point on each edge of the grid in the physical space and the plurality of corner points, the projection matrix, the focal length of the camera and the geographical position coordinates of the view center of the camera.

5. The method according to any one of claims 1 to 4, characterized in that, the parameter information of the camera comprises a focal length, a principal point position, a video CCD size and a pose parameter, the pose parameter comprising geographical position coordinates of the camera, a pitch angle, a roll angle and a side view angle of the camera.

6. The method according to any one of claims 1 to 4, characterized in that, the geographical position information comprises a global position code or geographical position coordinates.

7. The method according to any one of claims 1 to 4, characterized in that, the determining of the locating pixel of the target object in the image comprises: If the type of the target object is a vehicle, determining pixel coordinates, a height value and a width value of a reference pixel of the vehicle in the image; According to the pixel coordinates, the height value and the width value of the reference pixel, determining pixel coordinates of a locating pixel of the vehicle in the image.

8. A positioning device, characterized in that Comprise: A locating pixel determination unit is configured to determine a locating pixel of a target object in an image, wherein the locating pixel is used to represent a position of the target object in the image; A grid determination unit is configured to determine a grid of a physical space corresponding to the locating pixel according to a target pixel set corresponding to the locating pixel and a mapping relationship between the target pixel set and the grid of the physical space; A geographic position information determination unit is configured to determine geographic position information of the locating pixel according to geographic position information corresponding to the grid of the physical space corresponding to the locating pixel. The target pixel set is obtained by dividing the image according to the grid of the physical space and parameter information of a camera used to collect the image, wherein the parameter information of the camera is determined according to feature points in a sample image and corresponding geographic position coordinates of the feature points. The mapping relationship is determined according to a grid of the physical space to which a pixel in the target pixel set belongs and the pixel on the image.

9. The positioning device of claim 8, wherein, The locating device comprises: A first pixel coordinate determination unit is configured to determine pixel coordinates corresponding to each of a plurality of corner points of a grid in the physical space in the image according to geographic position coordinates of the plurality of corner points, a projection matrix, a focal length of the camera and geographic position coordinates of a viewpoint center, wherein the projection matrix is used to represent a conversion relationship between pixel coordinates of the image and the geographic position coordinates of the corner points on the grid in the physical space; A target polygon determination unit is configured to determine a target polygon in the image surrounded by a plurality of pixels according to pixel coordinates of the plurality of pixels and a correlation relationship between the plurality of corner points, wherein the pixels surrounded by the target polygon or the pixels surrounded by the target polygon and pixels on edges of the target polygon are used to construct a pixel set.

10. The positioning device of claim 9, wherein, If the image collected by the camera is distorted, the locating device comprises: A second pixel coordinate determination unit is configured to determine corrected pixel coordinates of each of the plurality of pixels in the image according to pixel coordinates of each of the plurality of pixels in the image and a radial distortion coefficient and / or a tangential distortion coefficient, wherein the corrected pixel coordinates are used to determine a pixel set to which each of the plurality of pixels in the image belongs.

11. The positioning device of claim 9, wherein, The first pixel coordinate determination unit comprises: A first pixel coordinate determination subunit is configured to determine pixel coordinates of each of the plurality of pixels in the image according to geographic position coordinates of at least one sampling point on each edge of the grid in the physical space and a plurality of corner points, the projection matrix, the focal length of the camera and the geographic position coordinates of the viewpoint center.

12. The positioning device according to any one of claims 8-11, characterized in that, The parameter information of the camera comprises a focal length, a principal point position, a video CCD size and a pose parameter, wherein the pose parameter comprises geographic position coordinates of the camera, a pitch angle, a roll angle and a side view angle of the camera.

13. The positioning device according to any one of claims 8-11, characterized in that, The geographic position information comprises a global position code or geographic position coordinates.

14. The positioning device according to any one of claims 8-11, characterized in that, The locating pixel determination unit comprises: a third pixel coordinate determining sub-unit, configured to determine a pixel coordinate, a height value and a width value of a reference pixel of the vehicle in the image if the type of the target object is a vehicle; a fourth pixel coordinate determining sub-unit, configured to determine a pixel coordinate of a positioning pixel of the vehicle in the image according to the pixel coordinate, the height value and the width value of the reference pixel.

15. A positioning system, characterized by comprising: at least one camera and a positioning device; wherein, the camera is configured to collect an image and send the image to the positioning device; the positioning device is configured to receive the image collected by the camera and perform the positioning method according to any one of claims 1-7.

16. An electronic device, comprising: comprising: a processor and a memory, the memory being coupled to the processor, the memory being configured to store computer program code, the computer program code comprising computer instructions, when the computer instructions are read from the memory by the processor, so that the electronic device executes the positioning method according to any one of claims 1-7.

17. A computer program product, characterised in that, the computer program product comprises computer instructions, when the computer instructions are run on a computer, so that the computer executes the positioning method according to any one of claims 1-7.

18. A computer-readable storage medium, characterized in that, the computer readable storage medium comprises computer instructions, when the computer instructions are run on a computer, so that the computer executes the positioning method according to any one of claims 1-7.

19. A chip system, characterized by one or more processors, when the one or more processors execute instructions, the one or more processors execute the positioning method according to any one of claims 1-7.

Images