Field angle testing method, device, equipment, storage medium and system

Abstract

The invention discloses a field angle test method, device, equipment, storage medium and system, and relates to the technical field of augmented reality, in the disclosed field angle test method, a first shot image obtained by shooting covers a first test image, and has pixel gray value distribution which is smoothly decreased from the center to the edge, the method comprises the following steps of: starting from an image center point of a first shot image, sequentially detecting a first pixel point of which the pixel gray value is lower than a preset gray value along a plurality of preset directions, and taking the first pixel point as an image boundary point of the first shot image in the corresponding preset direction; and the actually measured field angle of the intelligent glasses in the corresponding preset direction is determined by using the image boundary point, so that the space pose of the image acquisition equipment does not need to be continuously adjusted, and the field angle test efficiency is effectively improved.

Description

Technical Field

[0001] This application relates to the field of extended reality technology, and in particular to a field of view testing method, apparatus, device, storage medium and system. Background Technology

[0002] In the realm of extended reality, smart glasses, as wearable devices with partial display capabilities such as Augmented Reality (AR) and Virtual Reality (VR) devices, determine the immersion and comfort of the user experience through their optical performance. Among these, the field of view (FGV) of smart glasses is a core parameter, characterizing the angular range of the virtual image displayed by the smart glasses that can be observed by a single eye. Accurate measurement of the FGV is crucial for the optical design verification, production quality control, and objective performance evaluation of smart glasses.

[0003] Currently, traditional field-of-view measurement methods involve controlling smart glasses to display a test image covering the entire field of view. Then, an image acquisition device (such as a DSLR or ordinary industrial camera) whose field of view cannot cover the entire test image is used. The lens of this device is aimed at one eyepiece of the smart glasses under test (i.e., the position viewed by the human eye) to simulate the human eye's light path. The image acquisition device is moved or rotated using a simple fixture to change its spatial pose, while the test image captured by the device is observed in each pose. When the test image disappears from the field of view of the image acquisition device, the boundary angle of the device in the current spatial pose is recorded. The field of view of the smart glasses is determined based on the recorded boundary angle, and then further evaluated to see if the determined field of view of the smart glasses meets the requirements. However, this method requires continuous adjustment of the spatial pose of the image acquisition device, resulting in a complex testing process and low efficiency in field-of-view measurement. Summary of the Invention

[0004] The main objective of this application is to provide a method, apparatus, device, storage medium, and system for testing the field of view, aiming to solve the technical problem that the existing technology requires continuous adjustment of the spatial pose of the image acquisition device, resulting in a complex testing process and low testing efficiency of the field of view.

[0005] To achieve the above objectives, this application proposes a field of view testing method. The method is applied to a field of view testing device within a field of view testing system. The field of view testing system further includes smart glasses and an image acquisition device. The method includes: The first test image displayed on the smart glasses is captured by the image acquisition device to obtain the first captured image. The field of view of the image acquisition device covers the first test image. The first captured image has a pixel gray value distribution that smoothly decreases from the center to the edge. Starting from the center point of the first captured image, the pixel grayscale value is sequentially detected along multiple preset directions to see if it is lower than a preset grayscale value; In different preset directions, the first pixel with a gray value lower than the preset gray value is determined, and each of the first pixels is used as the image boundary point of the first captured image in the corresponding preset direction; The measured field of view of the smart glasses in the corresponding preset direction is determined based on the image boundary points.

[0006] In one embodiment, the step of determining the measured field of view angle of the smart glasses in the corresponding preset direction based on the image boundary points includes: The boundary angle of the first captured image in the corresponding preset direction is determined based on the boundary point; The boundary half-width of the smart glasses in the corresponding preset direction is determined based on the boundary angle; The measured field of view of the smart glasses in the corresponding preset direction is determined based on the half-width of the boundary.

[0007] In one embodiment, the step of determining the boundary angle of the first captured image in the corresponding preset direction based on the boundary point includes: Determine the target line-of-sight direction of the image acquisition device corresponding to the boundary point; Determine the angle between the target line-of-sight direction and the optical axis of the image acquisition device; The included angle is used as the boundary angle of the captured image in the corresponding preset direction.

[0008] In one embodiment, the step of determining the measured field of view angle of the smart glasses in the corresponding preset direction based on the boundary half-width includes: The smart glasses are controlled to display a second test image, which is a calibration image containing a regularly arranged array of feature points; The second test image is captured by the image acquisition device to obtain the second captured image; Determine the target's equivalent focal length based on feature points in the second captured image; The measured field of view of the smart glasses in the corresponding preset direction is determined based on the target equivalent focal length and the boundary half-width.

[0009] In one embodiment, the step of determining the target equivalent focal length based on feature points in the second captured image includes: Determine the image coordinates of feature points in the second captured image; The first projection matrix is ​​determined based on the calibration intrinsic parameters of the image acquisition device and the image coordinates of feature points in the second captured image; The current virtual image distance is determined based on the extrinsic parameters of the first projection matrix; Obtain a preset mapping relationship, which includes the correspondence between virtual image distance and equivalent focal length; Query the target equivalent focal length corresponding to the current virtual image distance in the preset mapping relationship.

[0010] In one embodiment, before the step of obtaining the preset mapping relationship, the method further includes: Under different virtual image distance calibration values, the smart glasses are controlled to display the second test image; The image acquisition device is used to capture the second test image at each of the virtual image distance calibration values ​​to obtain the third captured image corresponding to each of the virtual image distance calibration values; Determine the image coordinates of feature points in each of the third captured images; The corresponding second projection matrix is ​​determined based on the calibration intrinsic parameters of the image acquisition device and the image coordinates of feature points in each of the third captured images; Extract the equivalent focal length calibration value from the intrinsic parameters of each of the second projection matrices; The equivalent focal length calibration values ​​are associated with the corresponding virtual image distance calibration values ​​to construct a preset mapping relationship.

[0011] Furthermore, to achieve the above objectives, this application also proposes a field of view testing device, the device comprising: The image acquisition module is used to capture a first test image displayed on the smart glasses through an image acquisition device to obtain a first captured image. The field of view of the image acquisition device covers the first test image, and the first captured image has a pixel grayscale value distribution that smoothly decreases from the center to the edge. The pixel detection module is used to detect whether the pixel grayscale value is lower than a preset grayscale value by starting from the center point of the first captured image and proceeding along multiple preset directions. A boundary determination module is used to determine the first pixel point whose pixel grayscale value is lower than the preset grayscale value in different preset directions, and to use each of the first pixel points as the image boundary point of the first captured image in the corresponding preset direction; The field of view testing module is used to determine the measured field of view of the smart glasses in the corresponding preset direction based on the image boundary points.

[0012] In addition, to achieve the above objectives, this application also proposes a field of view testing device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the field of view testing method as described above.

[0013] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the field of view testing method described above.

[0014] In addition, to achieve the above objectives, this application also proposes a field of view testing system, which includes: smart glasses, an image acquisition device, and the field of view testing device described above.

[0015] One or more technical solutions proposed in this application have at least the following technical effects: This application uses an image acquisition device to capture a first test image displayed on smart glasses, obtaining a first captured image. The field of view of the image acquisition device covers the first test image. The first captured image has a pixel grayscale value distribution that smoothly decreases from the center to the edge. Starting from the image center point of the first captured image, the application sequentially detects whether the pixel grayscale value is lower than a preset grayscale value along multiple preset directions. The application identifies the first pixel point whose grayscale value is lower than the preset grayscale value in each preset direction and uses each first pixel point as the image boundary point of the first captured image in the corresponding preset direction. Based on the image boundary points, the application determines the measured field of view of the smart glasses in the corresponding preset direction. The first captured image obtained by this application covers the first test image and has a pixel grayscale value distribution that smoothly decreases from the center to the edge. By starting from the image center point of the first captured image and sequentially detecting the first pixel point whose grayscale value is lower than the preset grayscale value along multiple preset directions, and using the first pixel point as the image boundary point of the first captured image in the corresponding preset direction, the application determines the measured field of view of the smart glasses in the corresponding preset direction. This eliminates the need to continuously adjust the spatial pose of the image acquisition device, effectively improving the testing efficiency of the field of view. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the first embodiment of the field of view testing method of this application; Figure 2 This is a schematic diagram of boundary points in the first captured image of the first embodiment of this application; Figure 3 This is a flowchart illustrating the second embodiment of the field of view testing method of this application; Figure 4 This is a flowchart illustrating the third embodiment of the field of view testing method of this application; Figure 5 This is a schematic diagram of the modular structure of the field of view testing device of this application; Figure 6 This is a schematic diagram of the field of view testing device according to an embodiment of this application.

[0019] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0021] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0022] The main solution of this application embodiment is as follows: A first test image displayed on the smart glasses is captured by an image acquisition device to obtain a first captured image. The field of view of the image acquisition device covers the first test image. The first captured image has a pixel grayscale value distribution that smoothly decreases from the center to the edge. Starting from the image center point of the first captured image, the pixel grayscale value is sequentially detected along multiple preset directions to see if it is lower than a preset grayscale value. The first pixel point whose pixel grayscale value is lower than the preset grayscale value is determined in different preset directions, and each first pixel point is used as the image boundary point of the first captured image in the corresponding preset direction. The measured field of view of the smart glasses in the corresponding preset direction is determined based on the image boundary point.

[0023] Because existing technologies require constant adjustments to the spatial pose of image acquisition devices, the testing process is complex and the testing efficiency for the field of view is low.

[0024] This application provides a solution in which a first captured image covers a first test image and has a pixel grayscale value distribution that smoothly decreases from the center to the edge. Starting from the image center point of the first captured image, the first pixel with a grayscale value lower than a preset grayscale value is detected sequentially along multiple preset directions. The first pixel is used as the image boundary point of the first captured image in the corresponding preset direction. Then, the measured field of view of the smart glasses in the corresponding preset direction is determined by using the image boundary point. This eliminates the need to constantly adjust the spatial pose of the image acquisition device and effectively improves the testing efficiency of the field of view.

[0025] It should be noted that the execution entity in this embodiment is the field-of-view testing device in the field-of-view testing system. This field-of-view testing device, as the control and processing core of the system, possesses data processing, real-time control, and communication functions. It is used to run test programs, control the collaborative work of related measurement mechanisms and image acquisition equipment, and perform image processing and field-of-view calculations. In this embodiment and the following embodiments, this field-of-view testing device (hereinafter referred to as the testing device) is used as an example for description. Its specific implementation can be an industrial control computer, an embedded control system, or a dedicated test host, etc.

[0026] Based on this, embodiments of this application provide a method for testing the field of view, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the field of view testing method of this application.

[0027] In this embodiment, the field of view testing method is applied to the field of view testing device in the field of view testing system. The field of view testing system further includes smart glasses and an image acquisition device. The field of view testing method includes steps S10 to S40: Step S10: The first test image displayed on the smart glasses is captured by the image acquisition device to obtain the first captured image.

[0028] The field of view of the image acquisition device covers the first test image, and the first captured image has a pixel grayscale value distribution that smoothly decreases from the center to the edge.

[0029] It should be noted that the image acquisition device can be a high-resolution image sensor device with precise exposure control, such as an industrial camera. It is configured to receive external trigger signals to take pictures and transmit the acquired images to the testing equipment for processing.

[0030] Understandably, the first test image can be a uniform bright field image displayed by the smart glasses across its entire display area (full field of view), typically pure white (e.g., RGB values ​​of 255, 255, 255). The first test image does not carry any texture or shape information; its purpose is to provide a uniformly luminous surface.

[0031] It should be noted that the field of view testing system also includes a measurement actuator and a simulation head shell. The measurement actuator includes at least an eye-tracking simulation subsystem and an eyeball model.

[0032] The simulated head shell is used to simulate the shape of a human head. Its function is to install and fix the smart glasses under test, so that the smart glasses are in a stable and standard test posture.

[0033] An eye model is mounted at a preset eye point on the simulated head shell to accurately simulate the spatial position of the human eye. The aforementioned image acquisition device is integrated inside the eye model, with its optical center coinciding with the pupil position of the eye model.

[0034] The eye-tracking simulation subsystem is a high-precision multi-axis motion control mechanism connected to the eye model drive. Its core function is to receive motion commands from the testing equipment and drive the eye model (along with its internal image acquisition equipment) to make precise position and posture adjustments in three-dimensional space.

[0035] In practice, users can perform corresponding click operations through the human-machine interface of the testing device, such as selecting the field of view test and clicking "run." The testing device responds to the user's operation by sending test commands to the smart glasses through the communication link established between it and the smart glasses. The communication link can be a wired interface (such as USB or UART) or a wireless connection (such as Wi-Fi or Bluetooth). The control software on the testing device can construct and send a first test command to drive the smart glasses to display a first test image by calling the corresponding communication protocol (such as serial port protocol, custom USB HID command, or network API). After receiving the first test command, the smart glasses' internal processor parses and executes the test command, thereby displaying the specified first test image on its display screen.

[0036] Furthermore, the testing equipment sends motion commands to the eye-tracking simulation subsystem. Upon receiving the command, the subsystem's built-in motion controller calculates the motion command parameters and drives a high-precision motor (such as a servo motor or stepper motor) to execute the corresponding linear or rotary motion. This mechanical motion is transmitted to the eye model fixed to it via a precision transmission mechanism (such as a ball screw, linear guide, and rotary table), thereby causing the eye model to translate along the X, Y, and Z axes or rotate around its rotation center within the simulated head shell, precisely adjusting its spatial position and orientation. The image acquisition device installed inside the eye model moves along with the eye model. When the eye-tracking simulation subsystem drives the eye model to move to the vicinity of a pre-stored calibration position, it is determined that the optical center of the image acquisition device has reached the vicinity of the exit pupil center of the eyepiece of the smart glasses under test, that is, the distance range of the virtual image distance.

[0037] Subsequently, the testing equipment initiates the autofocus process: the image acquisition device continuously captures the first test image and transmits the captured image to the testing equipment; the testing equipment analyzes the sharpness evaluation function (such as gradient and frequency domain energy) of the captured image in real time; the testing equipment generates fine-tuning instructions based on the sharpness and sends them to the eye-tracking simulation subsystem, driving the eye model to perform small reciprocating movements along the optical axis until the sharpness reaches its peak, thus completing autofocus. At this point, the focal plane of the image acquisition device coincides with the virtual image plane displayed by the smart glasses under test, and the captured image is the first captured image.

[0038] The virtual image distance, or virtual image observation distance, can be the vertical distance from the center point of the exit pupil of the smart glasses eyepiece to the virtual image plane (the plane corresponding to the first test image) generated by its optical system.

[0039] It should be noted that the image acquisition device is pre-calibrated to ensure that its field of view in a single image is greater than or equal to the maximum field of view that the smart glasses under test can display. Therefore, when the smart glasses display the first test image covering its entire field of view, the image acquisition device can completely capture the entire area of ​​the first test image in its single frame. Furthermore, due to the lack of internal texture and highly uniform brightness of the first test image, the inherent vignetting effect of the smart glasses' optical system and the image acquisition device's lens is manifested in the first captured image. Specifically, this vignetting effect manifests as a gradual increase and restriction of the light path from the center of the optical axis (corresponding to the image center) towards the edges, resulting in a smooth and continuous attenuation of light intensity. Therefore, the obtained first captured image naturally exhibits a smooth and continuously decreasing pixel grayscale value distribution from the image center to the surrounding edges.

[0040] Step S20: Starting from the center point of the first captured image, detect whether the pixel grayscale value is lower than the preset grayscale value along multiple preset directions.

[0041] Step S30: Determine the first pixel whose grayscale value is lower than the preset grayscale value in different preset directions, and use each first pixel as the image boundary point of the first captured image in the corresponding preset direction.

[0042] It should be noted that the preset direction can be a specific path direction for boundary scanning that extends radially outward from the center point of the image within the two-dimensional image plane defined by the first captured image. The preset direction may include the horizontal direction (0° and 180°), the vertical direction (90° and 270°), the diagonal direction (such as 45°, 135°, 225°, 315°), or more angles that are uniformly interpolated between the horizontal and vertical directions.

[0043] Understandably, the preset grayscale value can be a global grayscale threshold for determining the boundary of a virtual image.

[0044] The testing equipment can use the pixel grayscale value at the center point of the image (corresponding to the center of the optical axis of the optical system, i.e., the area with the highest brightness) as the reference grayscale value, or the average grayscale value of all pixels in a preset area centered on the image center point (e.g., a square area with a side length of N pixels) as the reference grayscale value. Then, the reference grayscale value is multiplied by a preset scaling factor (e.g., 0.2), and the product is defined as the preset grayscale value.

[0045] Since the first captured image has a pixel grayscale value distribution that smoothly decreases from the center to the edge, that is, when the brightness of the edge area of ​​the virtual image decays to a certain proportion (such as 10%-30%) of the brightness of the center, the area is visually close to being unrecognizable, or the signal-to-noise ratio is too low to be measured stably, a scaling factor can be selected to ensure that the preset grayscale value obtained based on the scaling factor can be used to identify the physical boundary of the effective optical display.

[0046] In its implementation, the testing device uses the center point of the first captured image as the scanning starting point. For the currently selected preset direction (e.g., horizontal to the right), it moves outward pixel by pixel along the corresponding pixel path. At each new pixel location, the pixel's grayscale value is read and compared with a preset grayscale value. When the grayscale value of the first pixel is detected to be lower than the preset grayscale value, this first pixel is determined to be an image boundary point in the current preset direction, and its pixel coordinates in the image coordinate system are recorded. After completing a scan in one preset direction, the scanning starting point is reset to the image center point, and the device switches to the next preset direction (e.g., horizontal to the left), repeating the scanning and comparison process until all image boundary points in all preset directions have been detected and recorded.

[0047] For example, refer to Figure 2 , Figure 2 This is a schematic diagram of boundary points in the first captured image according to the first embodiment of this application. Figure 2 In this example, assuming the preset directions include both horizontal and vertical directions, and the image center point is pixel O, starting from pixel O in the first captured image, the first pixel with a gray value lower than the preset gray value is detected horizontally to the right (pixel A), which is then the right boundary point. Continuing from pixel O in the first captured image, the first pixel with a gray value lower than the preset gray value is detected horizontally to the left (pixel B), which is then the left boundary point. Continuing from pixel O in the first captured image, the first pixel with a gray value lower than the preset gray value is detected vertically upwards (pixel C), which is then the upper boundary point. Continuing from pixel O in the first captured image, the first pixel with a gray value lower than the preset gray value is detected vertically downwards (pixel D), which is then the lower boundary point.

[0048] Step S40: Determine the measured field of view of the smart glasses in the corresponding preset direction based on the image boundary points.

[0049] In practical implementation, the testing equipment can convert the pixel coordinates of the image boundary points detected in each preset direction into corresponding spatial angle values ​​based on pre-calibrated parameters (such as the focal length and principal point position of the image acquisition device). After obtaining the boundary angles in each preset direction, the measured field of view of the smart glasses in that preset direction is obtained through algebraic synthesis.

[0050] For example, the measured field of view in the horizontal direction can be the sum of the absolute values ​​of the right and left boundary angles; the measured field of view in the vertical direction can be the sum of the absolute values ​​of the upper and lower boundary angles; and the measured field of view in the diagonal direction can be calculated using the two corresponding orthogonal boundary angles, or directly using the boundary angles in the diagonal direction. The testing equipment can acquire the standard field of view (such as the manufacturer-specified field of view) pre-configured for the smart glasses in each preset direction. It compares the measured field of view of the smart glasses in each preset direction with the corresponding standard field of view to determine whether the measured field of view of the smart glasses in each preset direction meets the requirements and generates a corresponding test report. For example, if the deviation between the measured field of view and the standard field of view in a certain preset direction is greater than a set threshold, it is determined that the measured field of view of the smart glasses does not meet the requirements.

[0051] This embodiment captures a first test image displayed on smart glasses using an image acquisition device, obtaining a first captured image. The field of view of the image acquisition device covers the first test image. The first captured image has a pixel grayscale value distribution that smoothly decreases from the center to the edge. Starting from the center point of the first captured image, the pixel grayscale value is sequentially detected along multiple preset directions to see if it is lower than a preset grayscale value. The first pixel point with a grayscale value lower than the preset grayscale value is determined in each preset direction, and each first pixel point is used as the image boundary point of the first captured image in the corresponding preset direction. The measured field of view of the smart glasses in the corresponding preset direction is determined based on the image boundary point. In this embodiment, the first captured image covers the first test image and has a pixel grayscale value distribution that smoothly decreases from the center to the edge. By starting from the center point of the first captured image and sequentially detecting the first pixel point with a grayscale value lower than the preset grayscale value along multiple preset directions, and using the first pixel point as the image boundary point of the first captured image in the corresponding preset direction, the measured field of view of the smart glasses in the corresponding preset direction can be determined using the image boundary point. This eliminates the need to continuously adjust the spatial pose of the image acquisition device, effectively improving the testing efficiency of the field of view.

[0052] Based on the first embodiment of this application, a second embodiment of this application is proposed. In the second embodiment of this application, content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 , Figure 3 This is a flowchart illustrating the second embodiment of the field of view testing method of this application.

[0053] In this embodiment, step S40 includes steps S401 to S403: Step S401: Determine the boundary angle of the first captured image in the corresponding preset direction based on the boundary point.

[0054] In practical implementation, the spatial mapping relationship between the smart glasses and the image acquisition device can be pre-determined through calibration. This spatial mapping parameter defines the mapping relationship between any pixel on the image acquisition device and its corresponding three-dimensional spatial observation direction, with the optical center of the smart glasses as the origin. The testing device can call this spatial mapping relationship to convert the pixel coordinates of boundary points in a preset direction (e.g., the right and left boundary points in the horizontal direction) into a three-dimensional spatial direction vector pointing from the optical center of the image acquisition device to that boundary point. Subsequently, the angle between this three-dimensional spatial direction vector and a reference reference direction (e.g., the optical axis direction of the image acquisition device) is calculated, and this angle is the boundary angle corresponding to that boundary point. For example, for the horizontal direction, the left and right boundary angles corresponding to the left and right boundary points can be obtained respectively.

[0055] In one feasible implementation, step S401 includes steps S4011 to S4013: Step S4011: Determine the target line-of-sight direction of the image acquisition device corresponding to the boundary point.

[0056] In a specific implementation, the testing device can map the pixel coordinates of the boundary point located in the first captured image to a three-dimensional spatial direction vector pointing from the optical center of the image acquisition device to the spatial boundary point based on the above spatial mapping relationship. The direction corresponding to this three-dimensional spatial direction vector is the target viewing direction.

[0057] Step S4012: Determine the angle between the target line of sight and the optical axis of the image acquisition device.

[0058] In practical implementation, the testing equipment can calculate the spatial angle between the vector corresponding to the target's line of sight (a three-dimensional spatial direction vector) and the inherent optical axis direction vector of the image acquisition device. This spatial angle can be obtained by calculating the dot product of the two direction vectors and applying the inverse cosine function. Its value is the angle between the target's line of sight and the optical axis of the image acquisition device, representing the angle by which the boundary point deviates from the central axis of the imaging system.

[0059] Step S4013: The included angle is used as the boundary angle of the captured image in the corresponding preset direction.

[0060] In practice, the testing equipment can associate the determined included angle with the corresponding preset direction as the boundary angle in the preset direction.

[0061] Step S402: Determine the boundary half-width of the smart glasses in the corresponding preset direction based on the boundary angle.

[0062] In practical implementation, the testing device can calculate half the sum of the absolute values ​​of two boundary angles in a preset direction (such as the left and right boundary angles in the horizontal direction), and use the calculation result as the boundary half-width of the smart glasses in the corresponding preset direction. For example, if the measured horizontal left boundary angle is -30° and the horizontal right boundary angle is +34°, then its horizontal boundary half-width is (|-30°|+|+34°|) / 2 = 32°.

[0063] Step S403: Determine the measured field of view angle of the smart glasses in the corresponding preset direction based on the boundary half-width.

[0064] In practice, for any preset direction, the test device can obtain the field of view in the corresponding preset direction by multiplying the boundary half-width by 2.

[0065] It should be understood that by determining the boundary angle of the first captured image in the corresponding preset direction based on the boundary point; determining the boundary half-width of the smart glasses in the corresponding preset direction based on the boundary angle; and determining the measured field of view of the smart glasses in the corresponding preset direction based on the boundary half-width, the accurate testing of the measured field of view using the boundary angle is achieved, ensuring the consistency and repeatability of the measurement results.

[0066] Based on the first and second embodiments of this application, a third embodiment of this application is proposed. In this third embodiment, content that is the same as or similar to the first and second embodiments described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 4 , Figure 4 This is a flowchart illustrating the third embodiment of the field of view testing method of this application.

[0067] In this embodiment, step S403 includes steps S4031 to S4034: Step S4031: Control the smart glasses to display a second test image, the second test image being a calibration image containing a regularly arranged array of feature points.

[0068] Step S4032: The second test image is captured by the image acquisition device to obtain the second captured image.

[0069] It should be noted that the feature point array can be a set of regularly arranged points with well-defined geometric shapes and fixed spatial positions in the second test image. Each feature point has a local visual pattern (such as a corner or center of a circle) that is easily and accurately identified in the image, and the relative index order of the feature points in the entire array and their absolute three-dimensional coordinates in the real physical world are known.

[0070] For example, the second test image is illustrated using a checkerboard calibration map. The feature point array is represented by a series of internal corner points formed by the intersection of all black and white squares within the checkerboard calibration map. Each corner point is a common vertex of four adjacent squares, and its pixel-level position can be located with extremely high precision using a sub-pixel detection algorithm. These corner points naturally form a regular two-dimensional grid arrangement in the image, and their three-dimensional coordinates in the physical world can be uniquely determined based on the known square size and the number of rows and columns in the grid. Therefore, the checkerboard instantiates a regularly arranged feature point array.

[0071] In a specific implementation, the testing equipment can send a second test command to drive the smart glasses to display a second test image. Upon receiving the second test command, the smart glasses' internal processor parses and executes the command, thereby displaying the specified second test image on its screen. Subsequently, the testing equipment drives an image acquisition device to capture the second test image, obtaining a second captured image.

[0072] Step S4033: Determine the target equivalent focal length based on the feature points in the second captured image.

[0073] It should be noted that the equivalent focal length is a parameter that characterizes the optical magnification capability of a smart glasses optical system to magnify and project a tiny image from the internal display screen into a distant virtual image.

[0074] In practice, the testing equipment establishes a precise correspondence between the detected feature point positions in the second captured image and their known real-world coordinates. By calculating the scale change relationship caused by perspective projection, the focal length value of the optical system corresponding to this imaging effect is determined, and the determined focal length value is used as the target equivalent focal length.

[0075] In one feasible implementation, step S4033 includes: Step S40331: Determine the image coordinates of the feature points in the second captured image.

[0076] In a specific implementation, the testing device can determine the position of all feature points in the second captured image in the image coordinate system and output a series of two-dimensional pixel coordinates of the feature points. The two-dimensional pixel coordinates of each feature point are the image coordinates of the feature points.

[0077] Step S40332: Determine the first projection matrix based on the calibration parameters of the image acquisition device and the image coordinates of the feature points in the second captured image.

[0078] In a specific implementation, the testing device can take the image coordinates of each feature point in the second captured image and the internal parameters (including focal length, principal point coordinates and distortion coefficients) pre-calibrated by the image acquisition device as input, and calculate a mathematical transformation model describing the projection relationship from the current three-dimensional space point to the two-dimensional image point by solving the perspective projection equation (such as by using direct linear transformation or least squares method). This mathematical transformation model is the first projection matrix.

[0079] Step S40333: Determine the current virtual image distance based on the extrinsic parameters of the first projection matrix.

[0080] It should be noted that the virtual image distance can be the vertical distance from the exit pupil center of the smart glasses eyepiece to the virtual image plane generated by its optical system.

[0081] In a specific implementation, the testing device can resolve its extrinsic parameters from the first projection matrix. These extrinsic parameters include the rotation and translation relationship between the coordinate system of the image acquisition device and the coordinate system of the virtual image plane. Specifically, the testing device can extract the component of the translation vector in the optical axis direction of the image acquisition device (or the magnitude of the vector), which is the vertical distance from the optical center of the image acquisition device to the virtual image plane. This distance is determined as the current virtual image distance.

[0082] Step S40334: Obtain the preset mapping relationship.

[0083] The preset mapping relationship includes the correspondence between virtual image distance and equivalent focal length.

[0084] It should be noted that the above-mentioned preset mapping relationship can be obtained by taking pictures of the second test image under different virtual image distance calibration values, determining the corresponding equivalent focal length based on the third image obtained by the picture, and then associating each virtual image distance with the equivalent focal length to obtain the preset mapping relationship.

[0085] Specifically, steps S403341 to S403346 are included before step S40334: Step S403341: Under different virtual image distance calibration values, control the smart glasses to display the second test image.

[0086] In practice, a series of virtual image distance calibration values ​​can be pre-built. For each virtual image distance calibration value, the virtual image distance of the smart glasses is set to that calibration value by adjusting the smart glasses. Subsequently, under that virtual image distance calibration value, the smart glasses are controlled to display the second test image.

[0087] Step S403342: The second test image under each virtual image distance calibration value is captured by the image acquisition device to obtain the third captured image corresponding to each virtual image distance calibration value.

[0088] Step S403343: Determine the image coordinates of feature points in each of the third captured images.

[0089] In the specific implementation, at each virtual image distance calibration value, the testing device can capture a second test image displayed on the smart glasses using an image acquisition device to obtain a third captured image corresponding to the virtual image distance calibration value. Subsequently, the positions of all feature points in the third captured image in the image coordinate system can be determined, and a series of image coordinates of the feature points can be output.

[0090] Step S403344: Determine the corresponding second projection matrix based on the calibration parameters of the image acquisition device and the image coordinates of the feature points in each of the third captured images.

[0091] Step S403345: Extract the equivalent focal length calibration value from the intrinsic parameters of each of the second projection matrices.

[0092] In practical implementation, for any virtual image distance calibration value corresponding to the third captured image, the testing device can use the image coordinates of each feature point in the third captured image, as well as the pre-calibrated internal parameters of the image acquisition device (including focal length, principal point coordinates, and distortion coefficients), as input. By solving the perspective projection equation (such as using direct linear transformation or least squares method), a second projection matrix describing the projection relationship from the current three-dimensional space point to the two-dimensional image point is calculated. Subsequently, specific parameters on the main diagonal of the second projection matrix are extracted from its internal parameter matrix. These parameters characterize the imaging scale and magnification capability of the smart glasses optical system at the current virtual image distance calibration value. The extracted parameter value is then determined as the equivalent focal length calibration value.

[0093] Step S403346: Associate each of the equivalent focal length calibration values ​​with the corresponding virtual image distance calibration values ​​to construct a preset mapping relationship.

[0094] In a practical implementation, the testing system can repeat the above process to determine the equivalent focal length calibration value corresponding to each virtual image distance calibration value, and then pair and store each virtual image distance calibration value with its corresponding equivalent focal length calibration value to obtain a preset mapping relationship.

[0095] Step S40335: Query the target equivalent focal length corresponding to the current virtual image distance in the preset mapping relationship.

[0096] In practice, the testing equipment can traverse the preset mapping relationship based on the current virtual image distance to query the equivalent focal length corresponding to the current virtual image distance and obtain the target equivalent focal length.

[0097] Step S4034: Determine the measured field of view of the smart glasses in the corresponding preset direction based on the target equivalent focal length and the boundary half-width.

[0098] It should be noted that the following preset field of view formula can be constructed in advance:

[0099] In the formula, For the field of view, For calibration coefficients, For half the width of the boundary, It is the equivalent focal length.

[0100] The calibration coefficient can be a pre-set coefficient used to coordinate the dimensional and geometric relationship between the boundary half-width and the equivalent focal length, such as 2.2. The boundary half-width (e.g., 35°) is the angle value measured by the image acquisition device. Multiplying the boundary half-width by the calibration coefficient converts the boundary half-width into the corresponding physical length, which represents the actual length from the center to the boundary on the virtual image plane.

[0101] Specifically, for any preset direction, the testing equipment can call the above-mentioned preset field of view formula, substitute the calibration coefficient, boundary half-width and equivalent focal length, and obtain the field of view under the corresponding preset direction.

[0102] It should be understood that determining the measured field of view angle based on the sum of the absolute values ​​of the half-widths of the two boundaries on both sides of the preset direction relies on the optical center of the image acquisition device coinciding with the exit pupil center of the smart glasses. Any tiny alignment deviation will directly lead to systematic errors in the measured boundary angle, affecting the measurement result of the measured field of view angle. By using the above-mentioned preset field of view angle formula to determine the measured field of view angle of the smart glasses in the corresponding preset direction using the target equivalent focal length and the boundary half-width, the target equivalent focal length itself already contains the complete spatial projection relationship under the current test state. Therefore, even if there is a tiny alignment deviation in the image acquisition device, which will affect both the measurement of the boundary angle and the calibration of the target equivalent focal length, the deviation can be partially compensated or canceled in the final division operation of the preset field of view angle formula. This significantly reduces the requirements for mechanical positioning accuracy and effectively improves the accuracy of the field of view angle test.

[0103] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the field of view testing method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0104] This application also provides a field of view testing device, please refer to... Figure 5 , Figure 5This is a schematic diagram of the modular structure of the field of view testing device of this application. The field of view testing device includes: The image acquisition module 10 is used to capture a first test image displayed on the smart glasses through an image acquisition device to obtain a first captured image. The field of view of the image acquisition device covers the first test image, and the first captured image has a pixel grayscale value distribution that smoothly decreases from the center to the edge.

[0105] The pixel detection module 20 is used to detect whether the pixel grayscale value is lower than the preset grayscale value by starting from the center point of the first captured image and proceeding along multiple preset directions.

[0106] The boundary determination module 30 is used to determine the first pixel point whose pixel gray value is lower than the preset gray value in different preset directions, and to use each of the first pixels as the image boundary point of the first captured image in the corresponding preset direction.

[0107] The field of view testing module 40 is used to determine the measured field of view of the smart glasses in the corresponding preset direction based on the image boundary points.

[0108] The field-of-view testing device provided in this application, employing the field-of-view testing method described in the above embodiments, can solve the technical problem in the prior art where the spatial pose of the image acquisition device needs to be continuously adjusted, resulting in a complex testing process and low efficiency in field-of-view testing. Compared with the prior art, the beneficial effects of the field-of-view testing device provided in this application are the same as those of the field-of-view testing method provided in the above embodiments, and other technical features in the field-of-view testing device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0109] This application provides a field of view testing device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the field of view testing method in the above embodiment 1.

[0110] The following is for reference. Figure 6 , Figure 6 This is a schematic diagram of the field of view testing device according to an embodiment of this application. The field of view testing device in this embodiment may include, but is not limited to, industrial control computers, embedded control systems, or dedicated testing hosts. Figure 6 The field of view testing device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0111] like Figure 6As shown, the field-of-view testing device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the field-of-view testing device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the field-of-view testing equipment to communicate wirelessly or wiredly with other devices to exchange data. Although the figure shows a field-of-view testing equipment with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0112] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0113] The field-of-view testing device provided in this application, employing the field-of-view testing method described in the above embodiments, can solve the technical problem in the prior art where the spatial pose of the image acquisition device needs to be continuously adjusted, resulting in a complex testing process and low efficiency in field-of-view testing. Compared with the prior art, the beneficial effects of the field-of-view testing device provided in this application are the same as those of the field-of-view testing method provided in the above embodiments, and other technical features of this field-of-view testing device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0114] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0115] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0116] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the field of view testing method in the above embodiments.

[0117] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0118] The aforementioned computer-readable storage medium may be included in the field of view testing equipment; or it may exist independently and not be assembled into the field of view testing equipment.

[0119] The aforementioned computer-readable storage medium carries one or more programs. When the aforementioned one or more programs are executed by the field of view testing device, the field of view testing device causes the following: to capture a first test image displayed on the smart glasses using an image acquisition device, thereby obtaining a first captured image. The field of view of the image acquisition device covers the first test image, and the first captured image has a pixel grayscale value distribution that smoothly decreases from the center to the edge; starting from the image center point of the first captured image, to sequentially detect whether the pixel grayscale value is lower than a preset grayscale value along multiple preset directions; to determine the first pixel point whose pixel grayscale value is lower than the preset grayscale value in different preset directions, and to use each first pixel point as the image boundary point of the first captured image in the corresponding preset direction; and to determine the measured field of view of the smart glasses in the corresponding preset direction based on the image boundary point.

[0120] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0121] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0122] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0123] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described field-of-view testing method. This solves the technical problem in the prior art where the spatial pose of the image acquisition device needs to be continuously adjusted, leading to a complex testing process and low efficiency in field-of-view testing. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the field-of-view testing method provided in the above embodiments, and will not be repeated here.

[0124] This application also provides a field of view testing system, which includes: smart glasses, an image acquisition device, and the field of view testing device described above.

[0125] The field-of-view testing system provided in this application employs the smart glasses, image acquisition device, and field-of-view testing equipment mentioned above in the field-of-view testing method described in the above embodiments. This solves the technical problem in existing technologies where the spatial pose of the image acquisition device needs continuous adjustment, leading to a complex testing process and low efficiency in field-of-view testing. Compared with existing technologies, the beneficial effects of the field-of-view testing system provided in this application are the same as those of the optical field-of-view testing method provided in the above embodiments, and will not be elaborated upon here.

[0126] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for testing the field of view, characterized in that, The method is applied to a field-of-view testing device in a field-of-view testing system, the field-of-view testing system further including smart glasses and an image acquisition device, the method comprising: The first test image displayed on the smart glasses is captured by the image acquisition device to obtain the first captured image. The field of view of the image acquisition device covers the first test image. The first captured image has a pixel gray value distribution that smoothly decreases from the center to the edge. Starting from the center point of the first captured image, the pixel grayscale value is sequentially detected along multiple preset directions to see if it is lower than a preset grayscale value; In different preset directions, the first pixel with a gray value lower than the preset gray value is determined, and each of the first pixels is used as the image boundary point of the first captured image in the corresponding preset direction; The measured field of view of the smart glasses in the corresponding preset direction is determined based on the image boundary points.

2. The field of view testing method as described in claim 1, characterized in that, The step of determining the measured field of view of the smart glasses in the corresponding preset direction based on the image boundary points includes: The boundary angle of the first captured image in the corresponding preset direction is determined based on the boundary point; The boundary half-width of the smart glasses in the corresponding preset direction is determined based on the boundary angle; The measured field of view of the smart glasses in the corresponding preset direction is determined based on the half-width of the boundary.

3. The field of view testing method as described in claim 2, characterized in that, The step of determining the boundary angle of the first captured image in the corresponding preset direction based on the boundary point includes: Determine the target line-of-sight direction of the image acquisition device corresponding to the boundary point; Determine the angle between the target line-of-sight direction and the optical axis of the image acquisition device; The included angle is used as the boundary angle of the captured image in the corresponding preset direction.

4. The field of view testing method as described in claim 2, characterized in that, The step of determining the measured field of view angle of the smart glasses in the corresponding preset direction based on the boundary half-width includes: The smart glasses are controlled to display a second test image, which is a calibration image containing a regularly arranged array of feature points; The second test image is captured by the image acquisition device to obtain the second captured image; Determine the target's equivalent focal length based on feature points in the second captured image; The measured field of view of the smart glasses in the corresponding preset direction is determined based on the target equivalent focal length and the boundary half-width.

5. The field of view testing method as described in claim 4, characterized in that, The step of determining the target equivalent focal length based on feature points in the second captured image includes: Determine the image coordinates of feature points in the second captured image; The first projection matrix is ​​determined based on the calibration intrinsic parameters of the image acquisition device and the image coordinates of feature points in the second captured image; The current virtual image distance is determined based on the extrinsic parameters of the first projection matrix; Obtain a preset mapping relationship, which includes the correspondence between virtual image distance and equivalent focal length; Query the target equivalent focal length corresponding to the current virtual image distance in the preset mapping relationship.

6. The field of view testing method as described in claim 5, characterized in that, Before the step of obtaining the preset mapping relationship, the method further includes: Under different virtual image distance calibration values, the smart glasses are controlled to display the second test image; The image acquisition device is used to capture the second test image at each of the virtual image distance calibration values ​​to obtain the third captured image corresponding to each of the virtual image distance calibration values; Determine the image coordinates of feature points in each of the third captured images; The corresponding second projection matrix is ​​determined based on the calibration intrinsic parameters of the image acquisition device and the image coordinates of feature points in each of the third captured images; Extract the equivalent focal length calibration value from the intrinsic parameters of each of the second projection matrices; The equivalent focal length calibration values ​​are associated with the corresponding virtual image distance calibration values ​​to construct a preset mapping relationship.

7. A field-of-view testing device, characterized in that, The device includes: The image acquisition module is used to capture a first test image displayed on the smart glasses through an image acquisition device to obtain a first captured image. The field of view of the image acquisition device covers the first test image, and the first captured image has a pixel grayscale value distribution that smoothly decreases from the center to the edge. The pixel detection module is used to detect whether the pixel grayscale value is lower than a preset grayscale value by starting from the center point of the first captured image and proceeding along multiple preset directions. The boundary determination module is used to determine the first pixel point whose pixel gray value is lower than the preset gray value in different preset directions, and to use each of the first pixels point as the image boundary point of the first captured image in the corresponding preset direction; The field of view testing module is used to determine the measured field of view of the smart glasses in the corresponding preset direction based on the image boundary points.

8. A field-of-view testing device, characterized in that, The field of view testing device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the field of view testing method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the field of view testing method as described in any one of claims 1 to 6.

10. A field of view testing system, characterized in that, The field of view testing system includes: smart glasses, an image acquisition device, and the field of view testing device as described in claim 8.

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