Eye tracking latency and accuracy performance testing method and system for smart devices

Abstract

The present application discloses a method and system for testing the delay and accuracy performance of eye tracking of a smart device, which belongs to the field of eye tracking. The eye tracking delay performance testing method includes: controlling the human eye emulating device to perform a first movement according to a preset path; obtaining a first timestamp corresponding to the encoder signal output when the human eye emulating device moves to the response mark point; obtaining a second timestamp corresponding to the response signal output when the smart device detects that the human eye emulating device moves to the target mark point; based on the time difference between the first timestamp and the second timestamp, determining the eye tracking delay of the smart device at the response mark point. The eye tracking delay performance testing method also includes: calibrating the position of the target mark point based on the spatial mapping relationship between the target mark point position of the human eye emulating device and the response mark point position of the smart device to obtain the response mark point. In this way, the influence of the accuracy error on the delay test is eliminated, and the reliability of the eye tracking delay test is improved.

Description

Technical Field

[0001] The present application relates to the field of eye tracking technology, and in particular to an eye tracking delay performance testing method for an intelligent device, an eye tracking delay performance testing device, an eye tracking delay performance testing device, an eye tracking delay performance testing system, an eye tracking accuracy performance testing method, an eye tracking accuracy performance testing device, an eye tracking accuracy performance testing device, and a computer-readable storage medium. Background Art

[0002] Eye tracking technology plays a crucial role in smart devices, such as Extended Reality (XR) devices. It accurately captures user eye movements and gaze points in real time, enabling a more natural, efficient, and immersive interactive experience. However, current eye tracking technology faces significant challenges in performance testing. Accuracy and latency are key metrics for measuring eye tracking performance. Testing eye tracking latency and accuracy in smart devices has become a pressing issue. Summary of the Invention

[0003] The embodiments of the present application provide an eye tracking delay performance testing method, an eye tracking delay performance testing device, an eye tracking delay performance testing device, an eye tracking delay performance testing system, an eye tracking accuracy performance testing method, an eye tracking accuracy performance testing device, an eye tracking accuracy performance testing device and a computer-readable storage medium for an intelligent device to solve at least one of the above-mentioned technical problems.

[0004] In a first aspect, the eye tracking latency performance testing method of a smart device according to an embodiment of the present application includes:

[0005] controlling the human eye-simulating device to perform a first movement along a preset path;

[0006] Obtaining a first timestamp corresponding to an encoder signal output when the human eye emulating device moves to a response marked point;

[0007] Obtain a second timestamp corresponding to a response signal output by the smart device when detecting that the human eye-simulating device moves to a target marked point, wherein the smart device includes a display module and an eye tracking module, and the response signal includes any one of the following:

[0008] A brightness change signal of the display module;

[0009] A level change signal of the eye tracking module;

[0010] determining, based on a time difference between the first timestamp and the second timestamp, an eye tracking delay of the smart device at the response marked point;

[0011] The eye tracking delay performance testing method further includes:

[0012] Presetting the target marking point of the human eye-simulating device;

[0013] Controlling the human eye emulating device to perform a second movement along the preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device;

[0014] The target annotation point is calibrated based on the spatial mapping relationship to obtain the response annotation point.

[0015] In a second aspect, the eye tracking latency performance testing device of the smart device according to the embodiment of the present application includes:

[0016] A first control module is used to control the human eye-simulating device to perform a first movement along a preset path;

[0017] A first acquisition module is configured to acquire a first timestamp corresponding to an encoder signal output when the human eye emulating device moves to a response marked point;

[0018] A second acquisition module is configured to acquire a second timestamp corresponding to a response signal output by the smart device when the smart device detects that the human eye-simulating device moves to a target marked point, wherein the smart device includes a display module and an eye tracking module, and the response signal includes any one of the following:

[0019] A brightness change signal of the display module;

[0020] A level change signal of the eye tracking module;

[0021] a first determining module, configured to determine an eye tracking delay of the smart device at the response marked point based on a time difference between the first timestamp and the second timestamp;

[0022] The eye tracking delay performance testing device also includes:

[0023] A first setting module is used to preset the target marking point of the human eye simulation device;

[0024] a second control module, configured to control the human eye emulating device to perform a second movement along the preset path, so as to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device;

[0025] The first calibration module is configured to perform position calibration on the target annotation point based on the spatial mapping relationship to obtain the response annotation point.

[0026] On the third aspect, the eye tracking delay performance testing device of the smart device of the embodiment of the present application includes one or more processors and a memory, and the memory stores a computer program. When the computer program is executed by the processor, the above-mentioned eye tracking delay performance testing method is implemented.

[0027] In a fourth aspect, a computer-readable storage medium of an embodiment of the present application stores a computer program thereon, and when the program is executed by a processor, the above-mentioned eye tracking delay performance testing method is implemented.

[0028] In a fifth aspect, the eye tracking delay performance test method of a smart device according to an embodiment of the present application is applied to an eye tracking delay performance test system for a smart device, wherein the eye tracking delay performance test system includes an eye tracking delay performance test device, a human eye-simulating device, a smart device, and a control device. The eye tracking delay performance test method includes:

[0029] The eye tracking delay performance testing device controls the human eye emulating device to perform a first movement along a preset path;

[0030] When the human eye emulating device moves to the response marking point, it outputs an encoder signal to the control device, and the control device records a first timestamp corresponding to the encoder signal;

[0031] When the smart device detects that the human eye-simulating device moves to a target marked point, it outputs a response signal to the control device, and the control device records a second timestamp corresponding to the response signal. The smart device includes a display module and an eye tracking module, and the response signal includes any one of the following:

[0032] A brightness change signal of the display module;

[0033] A level change signal of the eye tracking module;

[0034] The control device uploads the first timestamp and the second timestamp to the eye tracking delay performance testing device;

[0035] The eye tracking delay performance testing device determines the eye tracking delay of the smart device at the response marked point based on the time difference between the first timestamp and the second timestamp;

[0036] The eye tracking delay performance testing method further includes:

[0037] The eye tracking delay performance testing device presets the target marking point of the human eye simulation device;

[0038] The eye tracking latency performance testing device controls the human eye emulating device to perform a second movement along the preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device;

[0039] The eye tracking delay performance testing device calibrates the position of the target annotation point based on the spatial mapping relationship to obtain the response annotation point.

[0040] In a sixth aspect, an eye tracking delay performance test system for a smart device according to an embodiment of the present application includes an eye tracking delay performance test device, a human eye-mimicking device, a smart device, and a control device;

[0041] The eye tracking delay performance testing device is used to control the human eye emulating device to perform a first movement along a preset path;

[0042] The human eye-simulating device is used to output an encoder signal to the control device when moving to the response mark point, and the control device is used to record a first timestamp corresponding to the encoder signal;

[0043] The smart device is configured to output a response signal to the control device when detecting that the human eye-simulating device moves to a target marked point, and the control device is configured to record a second timestamp corresponding to the response signal. The smart device includes a display module and an eye tracking module, and the response signal includes any one of the following:

[0044] A brightness change signal of the display module;

[0045] A level change signal of the eye tracking module;

[0046] The control device is used to upload the first timestamp and the second timestamp to the eye tracking delay performance testing device;

[0047] The eye tracking delay performance testing device is used to determine the eye tracking delay of the smart device at the response marked point based on the time difference between the first timestamp and the second timestamp;

[0048] The eye tracking delay performance testing device is also used to: preset the target marking point of the human eye emulating device; control the human eye emulating device to perform a second movement along the preset path to establish a spatial mapping relationship between the target marking point position of the human eye emulating device and the response marking point position of the smart device; and calibrate the position of the target marking point based on the spatial mapping relationship to obtain the response marking point.

[0049] In a seventh aspect, the eye tracking accuracy performance testing method of the smart device according to the embodiment of the present application includes:

[0050] Preset target marking points of human eye-mimicking equipment;

[0051] Controlling the human eye emulating device to perform a second movement along a preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device;

[0052] Performing position calibration on the target annotation point based on the spatial mapping relationship to obtain a response annotation point;

[0053] An eye tracking accuracy error of the smart device at the target marked point is determined according to the response marked point and the target marked point.

[0054] In an eighth aspect, an eye tracking accuracy performance test device for a smart device according to an embodiment of the present application includes:

[0055] The second setting module is used to preset the target marking point of the human eye simulation device;

[0056] a third control module, configured to control the human eye emulating device to perform a second movement along a preset path, so as to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device;

[0057] A second calibration module is configured to perform position calibration on the target annotation point based on the spatial mapping relationship to obtain a response annotation point;

[0058] The second determination module is configured to determine an eye tracking accuracy error of the smart device at the target marked point based on the response marked point and the target marked point.

[0059] Ninthly, the eye tracking accuracy performance testing device of the smart device according to the embodiment of the present application includes one or more processors and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the above-mentioned eye tracking accuracy performance testing method is implemented.

[0060] In a tenth aspect, the computer-readable storage medium of the embodiment of the present application stores a computer program thereon, and when the program is executed by a processor, the above-mentioned eye tracking accuracy performance testing method is implemented.

[0061] The eye tracking delay performance test method, eye tracking delay performance test device, eye tracking delay performance test device, eye tracking delay performance test system, eye tracking accuracy performance test method, eye tracking accuracy performance test device, eye tracking accuracy performance test device and computer-readable storage medium of the smart device of the embodiment of the present application, on the one hand, obtains the first timestamp corresponding to the encoder signal output when the human eye emulating device moves to the response mark point; on the other hand, obtains the second timestamp corresponding to the response signal output when the smart device detects that the human eye emulating device moves to the target mark point. Based on the time difference between the first timestamp and the second timestamp, the eye tracking delay of the smart device at the response mark point can be determined. Because before the delay test, the target mark point is calibrated to obtain the response mark point based on the spatial mapping relationship between the target mark point position of the human eye emulating device and the response mark point position of the smart device, the influence of the accuracy error on the delay test is eliminated, and the reliability of the eye tracking delay test is improved.

[0062] Additional aspects and advantages of the embodiments of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the embodiments of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0064] Figure 1 1 is a flowchart of a method for testing the eye tracking latency performance of a smart device according to certain embodiments of the present application;

[0065] Figure 2 Schematic diagram of the hardware architecture of an eye tracking latency performance test system for a smart device according to certain embodiments of the present application;

[0066] Figure 3 Schematic diagram of the hardware architecture of an eye tracking latency performance test system for a smart device according to certain embodiments of the present application;

[0067] Figure 4 is a schematic diagram of brightness changes of a display module in certain embodiments of the present application;

[0068] Figure 5 is a schematic diagram of multiple target marking points of multiple polar angles and multiple azimuth angles in some embodiments of the present application;

[0069] Figure 6 is a schematic diagram of polar angles of a human eye-mimicking device according to certain embodiments of the present application;

[0070] Figure 7is a schematic diagram of a human eye-mimicking device according to certain embodiments of the present application moving along a preset path;

[0071] Figure 8 is a schematic diagram of the spatial mapping relationship between the target annotation point position of the human eye-simulating device and the response annotation point position of the smart device in certain embodiments of the present application;

[0072] Figure 9 1 is a flowchart of a method for testing the eye tracking latency performance of a smart device according to certain embodiments of the present application;

[0073] Figure 10 is a schematic diagram of a process for determining an eye tracking accuracy error of a smart device at a predetermined polar angle according to certain embodiments of the present application;

[0074] Figure 11 1 is a flowchart of a method for testing the eye tracking latency performance of a smart device according to certain embodiments of the present application;

[0075] Figure 12 is a schematic diagram of level changes of an eye tracking module in certain embodiments of the present application;

[0076] Figure 13 is a schematic diagram of level changes of an eye tracking module in certain embodiments of the present application;

[0077] Figure 14 is a schematic diagram of a process for determining an eye tracking accuracy error of a smart device at a predetermined polar angle according to certain embodiments of the present application;

[0078] Figure 15 1 is a flowchart of a method for testing the eye tracking latency performance of a smart device according to certain embodiments of the present application;

[0079] Figure 16 is a schematic diagram of a process for determining multiple eye tracking delays of a smart device at multiple response annotation points according to certain embodiments of the present application;

[0080] Figure 17 is a schematic diagram of a process for determining multiple eye tracking delays of a smart device at multiple response annotation points according to certain embodiments of the present application;

[0081] Figure 18 1 is a flowchart of a method for testing the eye tracking latency performance of a smart device according to certain embodiments of the present application;

[0082] Figure 19 This is a schematic diagram of a module of an eye tracking latency performance test device for a smart device according to certain embodiments of the present application;

[0083] Figure 20Schematic diagram of a module of an eye tracking accuracy performance test device for a smart device according to certain embodiments of the present application;

[0084] Figure 21 This is a schematic diagram of a module of an eye tracking latency performance test device for a smart device according to certain embodiments of the present application;

[0085] Figure 22 is a schematic diagram of the connection state between a computer-readable storage medium and a processor in certain embodiments of the present application;

[0086] Figure 23 Schematic diagram of a module for testing the eye tracking accuracy performance of a smart device according to certain embodiments of the present application;

[0087] Figure 24 This is a schematic diagram of the connection status between a computer-readable storage medium and a processor in certain embodiments of the present application. DETAILED DESCRIPTION

[0088] The following further describes the embodiments of the present application in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions. Furthermore, the embodiments of the present application described below in conjunction with the accompanying drawings are exemplary and are intended only to explain the embodiments of the present application and are not to be construed as limiting the present application.

[0089] See also Figures 1 to 3 The eye tracking latency performance testing method of the smart device 300 according to the embodiment of the present application includes:

[0090] 011: Controlling the human eye-simulating device 200 to perform a first movement along a preset path;

[0091] 012: Obtain a first timestamp corresponding to an encoder signal output by the human eye emulating device 200 when the device moves to the response marking point;

[0092] 013: Obtain a second timestamp corresponding to a response signal output by the smart device 300 when the smart device 300 detects that the human eye-simulating device 200 moves to the target marked point. The smart device 300 includes a display module and an eye tracking module. The response signal includes any one of the following:

[0093] Brightness change signal of the display module;

[0094] Level change signal of the eye tracking module;

[0095] 014: Determine the eye tracking delay of the smart device 300 at the response marked point based on the time difference between the first timestamp and the second timestamp;

[0096] Eye tracking latency performance testing methods also include:

[0097] 015: Preset the target marking point of the human eye simulation device 200;

[0098] 016: Controlling the human eye emulating device 200 to perform a second movement along a preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device 200 and the response annotation point position of the smart device 300;

[0099] 017: Calibrate the target annotation points based on the spatial mapping relationship to obtain the response annotation points.

[0100] The eye tracking delay performance test method of the smart device 300 of the embodiment of the present application, on the one hand, obtains the first timestamp corresponding to the encoder signal output when the human eye emulating device 200 moves to the response mark point; on the other hand, obtains the second timestamp corresponding to the response signal output when the smart device 300 detects that the human eye emulating device 200 moves to the target mark point. Based on the time difference between the first timestamp and the second timestamp, the eye tracking delay of the smart device 300 at the response mark point can be determined. Because before the delay test, based on the spatial mapping relationship between the target mark point position of the human eye emulating device 200 and the response mark point position of the smart device 300, the target mark point is calibrated to obtain the response mark point, which eliminates the influence of accuracy error on the delay test and improves the reliability of the eye tracking delay test.

[0101] Specifically, the smart device 300 includes but is not limited to an XR device. It is understood that in addition to XR devices, the eye tracking latency performance test method of the embodiment of the present application and the eye tracking accuracy performance test method described below can also be applied to other smart devices 300 with similar requirements.

[0102] See also Figure 2 and Figure 3 The eye tracking delay performance test system 1000 may include an eye tracking delay performance test device 100, a human eye emulation device 200, an intelligent device 300, and a control device 400. The eye tracking delay performance test device 100 may be a personal computer (PC). The control device 400 may be a microcontroller unit (MCU). The control device 400 may be integrated into the human eye emulation device 200 or provided independently of the human eye emulation device 200, without limitation. The intelligent device 300 includes a display module and an eye tracking module. The display module is, for example, a screen.

[0103] The eye tracking delay performance test device 100 is used to control the human eye emulation device 200 to perform a first movement along a preset path. When the human eye emulation device 200 moves to the response mark point, the human eye emulation device 200 outputs an encoder signal to the control device 400, and the control device 400 records a first timestamp corresponding to the encoder signal. When the smart device 300 detects that the human eye emulation device 200 has moved to the target mark point, the smart device 300 outputs a response signal to the control device 400, and the control device 400 records a second timestamp corresponding to the response signal. The control device 400 uploads the first timestamp and the second timestamp to the eye tracking delay performance test device 100. Based on the time difference between the first timestamp and the second timestamp, the eye tracking delay performance test device 100 can determine the eye tracking delay of the smart device 300 at the response mark point.

[0104] The following combination Figure 2 and Figure 3 The principle of the eye tracking delay test is introduced. The eye tracking delay performance test device 100 sends a control instruction to the human eye device 200 to control the movement of the human eye device 200. The control device 400 collects the encoder signal of the human eye device 200 in real time through one signal, thereby obtaining the actual movement state of the human eye device 200; the other signal is obtained from the smart device 300, and different signal types can be selected according to different delay tests. The time required for the control device 400 to collect these two signals is less than 50us and can be ignored. The two signals are timestamped in the control device 400 and then uploaded to the eye tracking delay performance test device 100. The analysis software in the eye tracking delay performance test device 100 performs data analysis and processing, and compares the time when the human eye device 200 is detected to move to the pre-defined marked point corresponding to the two signals. The difference is the eye tracking delay.

[0105] Eye tracking latency can be divided into end-to-end eye tracking latency and eye tracking algorithm recognition latency. End-to-end eye tracking latency refers to the delay from the movement of the human eye emulating device 200 to the brightness change of the display module of the smart device 300. Eye tracking algorithm recognition latency refers to the delay from the movement of the human eye emulating device 200 to the successful recognition of the eye tracking module of the smart device 300 (i.e., the voltage level change of the eye tracking module).

[0106] The difference between the two delay tests is that the signal types of the smart device 300 obtained by the control device 400 are different. Figure 2 As shown in , the end-to-end delay of eye tracking requires detecting the brightness change of the display module, so the brightness signal (or light intensity signal) of the display module can be obtained through optical fiber. Figure 3As shown, the eye tracking algorithm needs to detect the level change of the eye tracking module to identify the delay, so the eye tracking module can be connected to the general purpose input / output (GPIO) interface of the control device 400 to obtain the level signal of the eye tracking module.

[0107] Research has found that the eye tracking delay is likely to be different when the eye moves to different positions. Accuracy errors can also interfere with the delay test. The specific analysis process is as follows:

[0108] See also Figure 8 , pre-define the target marking points of the human eye-simulating device 200, and take point A and point B as examples of the target marking points. Control the movement of the human eye-simulating device 200 so that its gaze point moves from O to X along a straight line. In theory, when the human eye-simulating device 200 moves to look at point A or point B, the brightness signal or level signal output by the smart device 300 will change, that is, a response signal is output, and the response signal includes a brightness change signal or a level change signal. However, due to errors in the eye tracking recognition of the smart device 300, the brightness signal or level signal output by the smart device 300 may change when the human eye-simulating device 200 moves to look at point A' or point B'. Point A' and point B' are the response gaze points. At this time, the position error between point A and point A' is the accuracy error of the smart device 300 at point A, and the same applies to other points.

[0109] When performing a delay test, if the encoder signal output by the human eye emulator 200 when it moves to point A is obtained and the first timestamp corresponding to the encoder signal is recorded, and the response signal output by the smart device 300 when it detects the human eye emulator 200 moving to point A is obtained and the second timestamp corresponding to the response signal is recorded, and then the eye tracking delay of the smart device 300 at point A is determined based on the time difference between the first and second timestamps, the resulting eye tracking delay will be inaccurate. This is because, although the smart device 300 outputs a response signal when it detects the human eye emulator 200 moving to point A, the human eye emulator 200 has not actually moved to point A at this time, but rather to point A'. Therefore, the second timestamp recorded at this time actually represents the timestamp when the human eye emulator 200 moves to point A'. However, when the human eye emulator 200 moves to point A and outputs an encoder signal, the first timestamp recorded at this time represents the timestamp when the human eye emulator 200 moves to point A. If the time stamp when the human eye emulating device 200 moves to point A is analyzed and compared with the time stamp when the human eye emulating device 200 moves to point A′, there will be an accuracy error in the spatial position.

[0110] Therefore, in the embodiment of the present application, a spatial mapping relationship is established between the target annotation point position of the human eye emulating device 200 and the response annotation point position of the smart device 300. The target annotation point position represents the position of the target annotation point (such as point A), and the response annotation point position represents the position of the response annotation point (such as point A'). The spatial mapping relationship is the mapping relationship between the position of point A and the position of point A'. Based on the spatial mapping relationship, point A can be calibrated to point A'. In the embodiment of the present application, the definition of the response annotation point and the target annotation point can be as follows: the response annotation point refers to the point corresponding to the position calibration based on the spatial mapping relationship between the target annotation point position of the human eye emulating device 200 and the actual response annotation point position of the smart device 300, which is used as a reference annotation point in the delay test phase. The target annotation point refers to the theoretical point position preset by the human eye emulating device 200 for gaze or motion path positioning, which is usually used as a reference annotation point in the accuracy test phase.

[0111] When performing a delay test, the encoder signal output by the human eye emulating device 200 when it moves to point A' is obtained, and the first timestamp corresponding to the encoder signal is recorded. The response signal output by the smart device 300 when it detects that the human eye emulating device 200 has moved to point A is obtained, and the second timestamp corresponding to the response signal is recorded. In this way, the first timestamp represents the timestamp when the human eye emulating device 200 moves to point A'. As mentioned above, the second timestamp also represents the timestamp when the human eye emulating device 200 moves to point A'. Therefore, based on the time difference between the first timestamp and the second timestamp corresponding to point A', the eye tracking delay of the smart device 300 at point A' can be determined by taking the difference. In this way, introducing accuracy pre-calibration in the eye tracking delay test can eliminate the impact of accuracy error on the delay test.

[0112] In traditional testing solutions, accuracy testing and delay testing are independent of each other. During the delay testing process, there is a lack of effective consideration of accuracy errors, which will affect the reliability of the delay test.

[0113] In the embodiments of this application, the accuracy test and delay test are perfectly combined based on the human eye emulation device 200. This can improve the reliability of the delay test through the accuracy test and promote the development of eye tracking technology. Specifically, the brightness change signal of the display module and the level change signal of the eye tracking module can respectively implement the end-to-end delay test of eye tracking and the delay test of eye tracking algorithm recognition.

[0114] In some embodiments, a plurality of target marking points with a plurality of polar angles and a plurality of azimuth angles are set on the preset path.

[0115] See also Figures 4 to 6 , the gaze area of the human eye-mimicking device 200 can be regarded as a circle. Figure 6In the figure, the X-axis direction is the line connecting the two eyeballs of the human eye device 200, the Y-axis direction is the vertical direction of the human eye device 200, and the Z-axis direction is the direction in which the human eye device 200 is looking directly at the gaze area, that is, the line connecting the midpoints of the two eyeballs of the human eye device 200 and the center of the gaze area. The X-axis direction, the Y-axis direction, and the Z-axis direction are perpendicular to each other. is the azimuth, is the polar angle.

[0116] In one example, the gaze area of the human eye-mimicking device 200 can be divided into three polar angles and 12 azimuth angles. The three polar angles are 10°, 20°, and 30°, and the 12 azimuth angles are 0°, 30°, 60°, 90°, 120°, 150°, 180°, 210°, 240°, 270°, 300°, and 330°. Each polar angle is combined with a corresponding azimuth angle to form a target marking point. The above three polar angles and 12 azimuth angles can be combined to form 36 target marking points. In addition, a 0° polar angle and a 0° azimuth angle can also be combined to form a target marking point. In other words, a total of 37 target marking points are set on the preset path.

[0117] Please combine Figure 7 and Figure 8 When controlling the human eye emulating device 200 to move along a preset path, the human eye emulating device 200 may be first controlled to sequentially scan through the three polar angles of 10°, 20°, and 30° in the azimuth direction of 0°; then the human eye emulating device 200 may be controlled to sequentially scan through the three polar angles of 10°, 20°, and 30° in the azimuth direction of 30°, and so on, until the human eye emulating device 200 is controlled to sequentially scan through the three polar angles of 10°, 20°, and 30° in the azimuth direction of 330°.

[0118] When controlling the human eye emulating device 200 to perform a first movement and a second movement along a preset path, the first movement can be a rapid sweep, and the second movement can be a slow sweep. This is because, based on the first movement of the human eye emulating device 200, it is sufficient to obtain the encoder signal output by the human eye emulating device 200 when it moves to the response mark point, and the response signal output by the smart device 300 when it detects that the human eye emulating device 200 has moved to the target mark point. Rapid sweeping can quickly obtain the encoder signal and response signal. Based on the second movement of the human eye emulating device 200, it is necessary to establish a spatial mapping relationship between the target mark point position of the human eye emulating device 200 and the response mark point position of the smart device 300. This process requires precise determination of the accuracy error between the target mark point and the response mark point. This process may also involve processes such as bidirectional sweeping and threshold detection (which will be discussed in detail later), as slow sweeping is required to continuously conduct experimental judgments.

[0119] See also Figure 9 In some embodiments, the response signal includes a brightness change signal of the display module. The eye tracking delay performance test method further includes:

[0120] 018: Setting a brightness change strategy for the display module. The brightness change strategy includes: when the eye tracking module detects that the human eye emulating device 200 moves to a predetermined polar angle, the brightness of the display module changes, so that the brightness signal output by the smart device 300 undergoes a predetermined brightness change;

[0121] Controlling the human eye emulating device 200 to perform a second movement along a preset path to establish a spatial mapping relationship (i.e., 016) between the target annotation point position of the human eye emulating device 200 and the response annotation point position of the smart device 300 includes:

[0122] 0161: Controlling the human eye-simulating device 200 to perform a second movement along a preset path;

[0123] 0162: Obtaining the actual polar angle to which the human eye emulating device 200 moves when the brightness signal output by the smart device 300 undergoes a predetermined brightness change;

[0124] 0163: Determine an eye tracking accuracy error of the smart device 300 at the predetermined polarity angle according to the predetermined polarity angle and the actual polarity angle;

[0125] 0164: Establish a spatial mapping relationship based on multiple eye tracking accuracy errors of the smart device 300 at multiple polar angles and multiple azimuth angles.

[0126] Specifically, a specific application program can be developed for the smart device 300 to set the brightness change strategy of the display module. Figure 4 For example, the gaze area of the human-eye device 200 can be divided into three circular areas. Area 3 is where the eye tracking module detects a polarity angle of 10°. At this time, the screen appears entirely dark, and the electrical signal converted by the photodiode (PD) is A±0.1A. Area 2 is where the eye tracking module detects a polarity angle of 10°-20°. At this time, the screen appears entirely dark, and the electrical signal converted by the PD is 2A±0.1A. Area 1 is where the eye tracking module detects a polarity angle of 20°-30°. At this time, the screen appears entirely bright, and the electrical signal converted by the PD is 3A±0.1A. These electrical signals converted by the PD can serve as the brightness signals output by the smart device 300.

[0127] After setting the brightness change strategy of the display module, an accuracy test is performed to determine the response calibration point for the subsequent delay test. The human eye device 200 is controlled to move slowly along a preset path and synchronously obtain the brightness signal output by the smart device 300.

[0128] See also Figure 8 Taking one of the directional angles as an example, control the human eye device 200 to move slowly and sweep, so that its gaze point moves along a straight line from O to X. Theoretically, when the human eye device 200 moves to look at points A and B, a sudden change in the brightness signal will be detected. However, due to errors in the eye tracking recognition of the smart device 300, the brightness signal may suddenly change when the human eye device 200 moves to look at points A' and B'. Among them, point A is the predetermined polar angle, point A' is the actual polar angle, and the difference in polar angles between points A and A' is the accuracy error of the smart device 300 at point A. The same applies to other points.

[0129] By testing the accuracy error of the smart device 300 at various polar angles (10°, 20°, 30°) and various azimuth angles (0°, 30°, 60°...330°), a spatial mapping relationship between the target annotation point position of the human eye-simulating device 200 and the response annotation point position of the smart device 300 can be established. Figure 8 The yellow dot is marked in the middle.

[0130] See also Figure 10 In some embodiments, during the process of controlling the human eye emulating device 200 to perform the second movement along a preset path, the eye tracking latency performance testing method further includes:

[0131] positively changing the polar angle of the human eye-simulating device 200 according to a predetermined angle change amount;

[0132] Determining whether a brightness signal output by the smart device 300 undergoes a predetermined brightness change;

[0133] When the brightness signal output by the smart device 300 changes by a predetermined brightness, determining whether a predetermined angle change is less than an angle change threshold;

[0134] When the predetermined angle change is less than the angle change threshold, determining an eye tracking accuracy error of the smart device 300 at the predetermined polarity angle according to the predetermined polarity angle and the actual polarity angle;

[0135] When the predetermined angle change is greater than or equal to the angle change threshold, the polarity angle of the human eye emulating device 200 is reversely changed according to half of the predetermined angle change, and the process returns to the step of determining whether the brightness signal output by the smart device 300 undergoes a predetermined brightness change.

[0136] The embodiment of the present application uses a bidirectional scanning and threshold detection method to determine the eye tracking accuracy error, so as to establish a spatial mapping relationship between the target annotation point position of the human eye simulation device 200 and the response annotation point position of the smart device 300.

[0137] Specifically, the predetermined angle change is represented by α. In one example, α is less than 5°. According to the predetermined angle change α, the polar angle of the human eye emulating device 200 is positively changed. That is, the predetermined angle change α is increased based on the current polar angle. This process controls the human eye emulating device 200 to scan forward.

[0138] Then, a determination is made as to whether the brightness signal output by the smart device 300 undergoes a predetermined brightness change. The predetermined brightness change may be a sudden brightness change. If the brightness signal output by the smart device 300 does not undergo the predetermined brightness change, the polarity angle of the human eye emulating device 200 continues to be positively changed by the predetermined angle change α, i.e., the predetermined angle change α is continuously increased based on the current polarity angle.

[0139] When the brightness signal output by the smart device 300 undergoes a predetermined brightness change, a determination is made as to whether the predetermined angle change α is less than an angle change threshold. In one example, the angle change threshold is 0.1°. If α is less than 0.1°, the eye tracking accuracy error of the smart device 300 at the predetermined polarity angle is determined based on the actual polarity angle to which the human eye-simulating device 200 moves when the brightness signal undergoes the predetermined brightness change and the predetermined polarity angle.

[0140] It can be understood that if the predetermined angle change α is greater than or equal to the angle change threshold, it indicates that the current polarity angle change span is too large, and a sudden brightness change may occur at a smaller polarity angle. Therefore, a binary method is used to reverse the polarity angle of human eye emulating device 200 by half of the predetermined angle change, i.e., 0.5α. This process controls the human eye emulating device 200 to scan in the opposite direction. Then, it is re-determined whether the brightness signal output by the smart device 300 has undergone the predetermined brightness change. In this way, through bidirectional scanning and threshold detection, the actual polarity angle to which the human eye emulating device 200 moves when the brightness signal undergoes the predetermined brightness change can be obtained with the highest accuracy.

[0141] Please refer again Figure 8After establishing a spatial mapping relationship between the target annotation point position of the human eye device 200 and the response annotation point position of the smart device 300, the position of point A can be calibrated based on the spatial mapping relationship to obtain point A'. When performing an eye tracking delay test, the human eye device 200 is controlled to move and scan quickly so that its gaze point moves from O to X along a straight line. The first timestamp t1 when the human eye device 200 looks at point A' is obtained, and the second timestamp t2 when the brightness signal undergoes a predetermined brightness change is obtained. t2-t1 is the eye tracking delay of point A'. By testing the eye tracking delay of the aforementioned 37 points in sequence, an eye tracking delay distribution map of the smart device 300 as a whole can be generated. This eye tracking delay distribution map is the end-to-end delay distribution map of the eye tracking of the smart device 300.

[0142] See also Figure 11 In some embodiments, the response signal includes a level change signal of the eye tracking module. The eye tracking delay performance testing method further includes:

[0143] 019: Setting a level change strategy for the eye tracking module. The level change strategy includes: when the eye tracking module detects that the human eye device 200 moves to a predetermined polarity angle, the level of the eye tracking module changes, so that the level signal output by the smart device 300 changes to a predetermined level;

[0144] Controlling the human eye emulating device 200 to perform a second movement along a preset path to establish a spatial mapping relationship (i.e., 016) between the target annotation point position of the human eye emulating device 200 and the response annotation point position of the smart device 300 includes:

[0145] 0165: Controlling the human eye-simulating device 200 to perform a second movement along a preset path;

[0146] 0166: Obtaining the actual polar angle to which the human eye emulating device 200 moves when the level signal output by the smart device 300 undergoes a predetermined level change;

[0147] 0167: Determine an eye tracking accuracy error of the smart device 300 at the predetermined polarity angle based on the predetermined polarity angle and the actual polarity angle;

[0148] 0168: Establish a spatial mapping relationship based on multiple eye tracking accuracy errors of the smart device 300 at multiple polar angles and multiple azimuth angles.

[0149] Specifically, a specific application can be developed for the smart device 300 to set the level change strategy of the eye tracking module. Figure 12For example, the gaze area of the human-eye-simulating device 200 can be divided into three circular areas. When the eye tracking module detects that the human-eye-simulating device 200 moves to the circular areas with polar angles of 10°, 20°, and 30°, the level of the eye tracking module changes. For example, in the initial state, the level of the eye tracking module is low. When the eye tracking module detects that the gaze point is located on the three circular areas, the eye tracking module outputs a high level, and the other areas still output a low level. For another example, please refer to Figure 13 When the eye tracking module detects that the gaze point is located in the area between 0° and 10° polarity angles, the eye tracking module outputs a low level. When the eye tracking module detects that the gaze point is located in the area between 10° and 20° polarity angles, the eye tracking module outputs a high level. When the eye tracking module detects that the gaze point is located in the area between 20° and 30° polarity angles, the eye tracking module outputs a low level. In both cases, the level of the eye tracking module will jump at the circles of 10°, 20°, and 30° polarity angles, for example, from low to high or from high to low.

[0150] After setting the level change strategy for the eye tracking module, an accuracy test is performed to determine the response calibration point for the subsequent delay test. The human eye device 200 is controlled to move slowly along a preset path and simultaneously obtain the level signal output by the smart device 300.

[0151] See also Figure 8 Taking one of the directional angles as an example, the human eye device 200 is controlled to move slowly and sweep, so that its gaze point moves from O to X along a straight line. Theoretically, when the human eye device 200 moves to look at points A and B, a jump in the level signal will be detected respectively. However, due to errors in the eye tracking recognition of the smart device 300, the level signal may jump when the human eye device 200 moves to look at points A' and B'. Among them, point A is the predetermined polarity angle, point A' is the actual polarity angle, and the polarity angle difference between points A and A' is the accuracy error of the smart device 300 at point A. The same applies to other points.

[0152] By testing the accuracy error of the smart device 300 at various polar angles (10°, 20°, 30°) and various azimuth angles (0°, 30°, 60°...330°), a spatial mapping relationship between the target annotation point position of the human eye-simulating device 200 and the response annotation point position of the smart device 300 can be established. In the aforementioned divided area, at the predetermined position corresponding to a specific polar angle and a specific azimuth angle, the response annotation point of the smart device 300 is at Figure 8 The yellow dot is marked in the middle.

[0153] See also Figure 14In some embodiments, during the process of controlling the human eye emulating device 200 to perform the second movement along a preset path, the eye tracking latency performance testing method further includes:

[0154] positively changing the polar angle of the human eye-simulating device 200 according to a predetermined angle change amount;

[0155] Determining whether the level signal output by the smart device 300 changes to a predetermined level;

[0156] When the level signal output by the smart device 300 changes to a predetermined level, determining whether a predetermined angle change is less than an angle change threshold;

[0157] When the predetermined angle change is less than the angle change threshold, determining an eye tracking accuracy error of the smart device 300 at the predetermined polarity angle according to the predetermined polarity angle and the actual polarity angle;

[0158] When the predetermined angle change is greater than or equal to the angle change threshold, the polarity angle of the human eye emulating device 200 is reversely changed according to half of the predetermined angle change, and the process returns to the step of determining whether the level signal output by the smart device 300 undergoes a predetermined level change.

[0159] The embodiment of the present application uses a bidirectional scanning and threshold detection method to determine the eye tracking accuracy error, so as to establish a spatial mapping relationship between the target annotation point position of the human eye simulation device 200 and the response annotation point position of the smart device 300.

[0160] Specifically, the predetermined angle change is represented by α. In one example, α is less than 5°. According to the predetermined angle change α, the polar angle of the human eye emulating device 200 is positively changed. That is, the predetermined angle change α is increased based on the current polar angle. This process controls the human eye emulating device 200 to scan forward.

[0161] Then, it is determined whether the level signal output by the smart device 300 undergoes a predetermined level change. The predetermined level change may be a level jump. If the level signal output by the smart device 300 does not undergo the predetermined level change, the polarity angle of the human eye emulating device 200 continues to be positively changed according to the predetermined angle change α, that is, the predetermined angle change α is continuously increased based on the current polarity angle.

[0162] When the level signal output by the smart device 300 undergoes a predetermined level change, a determination is made as to whether a predetermined angle change α is less than an angle change threshold. In one example, the angle change threshold is 0.1°. If α is less than 0.1°, the eye tracking accuracy error of the smart device 300 at the predetermined polarity angle is determined based on the actual polarity angle to which the human eye emulating device 200 moves when the level signal undergoes the predetermined level change and the predetermined polarity angle.

[0163] It can be understood that if the predetermined angle change α is greater than or equal to the angle change threshold, it indicates that the current polarity angle change span is too large, and a level jump may occur at a smaller polarity angle. Therefore, a binary method is used to reverse the polarity angle of human eye emulating device 200 by half of the predetermined angle change, i.e., 0.5α. This process controls the human eye emulating device 200 to perform a reverse scan. Then, a reassessment is made as to whether the level signal output by smart device 300 has undergone a predetermined level change. In this way, through bidirectional scanning and threshold detection, the actual polarity angle to which human eye emulating device 200 moves when the level signal undergoes a predetermined level change can be obtained with the highest accuracy.

[0164] Please refer again Figure 8 After establishing a spatial mapping relationship between the target annotation point position of the human eye device 200 and the response annotation point position of the smart device 300, the position of point A can be calibrated based on the spatial mapping relationship to obtain point A'. When performing an eye tracking delay test, the human eye device 200 is controlled to move and scan quickly so that its gaze point moves from O to X along a straight line. The first timestamp t1 when the human eye device 200 looks at point A' is obtained, and the second timestamp t2 when the level signal undergoes a predetermined level change is obtained. t2-t1 is the eye tracking delay of point A'. By sequentially testing the eye tracking delay of the aforementioned 37 points, an eye tracking delay distribution map of the smart device 300 as a whole can be generated. This eye tracking delay distribution map is the delay distribution map identified by the eye tracking algorithm.

[0165] See also Figure 15 In some embodiments, obtaining a first timestamp (i.e., 012) corresponding to an encoder signal output when the human eye emulating device 200 moves to a response mark point includes:

[0166] 0121: Acquire multiple first timestamps corresponding to multiple encoder signals output when the human eye emulating device 200 moves to multiple response marking points;

[0167] Obtaining a second timestamp (i.e., 013) corresponding to a response signal output by the smart device 300 when detecting that the human eye-simulating device 200 moves to the target marked point includes:

[0168] 0131: Acquire multiple second timestamps corresponding to multiple response signals output by the smart device 300 when detecting that the human eye emulating device 200 moves to multiple target marking points.

[0169] Determining the eye tracking delay (i.e., 014) of the smart device 300 at the response marked point based on the time difference between the first timestamp and the second timestamp includes:

[0170] 0141: Determine, based on multiple time differences between the multiple first timestamps and the multiple second timestamps, multiple eye tracking delays of the smart device 300 at multiple response annotation points;

[0171] Eye tracking latency performance testing methods also include:

[0172] 020: Generate an eye tracking delay distribution map of the smart device 300 according to multiple eye tracking delays.

[0173] Specifically, see Figure 16 and Figure 17 ,First, initialize the azimuth angle and set the azimuth angle β=0.

[0174] Then, the gaze point of the human eye-simulating device 200 is controlled to rapidly change from O to X. During this process, the azimuth angle β remains unchanged, and the polar angle changes from 0° to 30°. The azimuth angle 0° is combined with the polar angles 10°, 20°, and 30° to form three marked points.

[0175] Three encoder signals outputted when the human eye emulating device 200 moves to three response marking points are obtained, and three first time stamps corresponding to the three encoder signals are recorded, which are represented by t1, t2, and t3 respectively.

[0176] When the smart device 300 detects that the human eye device 200 moves to three target marking points (corresponding to Figure 16 The brightness signal in the middle has a predetermined brightness change, corresponding to Figure 17 The three response signals are outputted when the level signal undergoes a predetermined level change, and three second time stamps corresponding to the three response signals are recorded, which are represented by t1', t2', and t3' respectively.

[0177] Based on the time difference between t1 and t1', the time difference between t2 and t2', and the time difference between t3 and t3', the three eye tracking delays of the smart device 300 at the three response annotation points can be determined.

[0178] Then, it is determined whether the detection is complete. Since the above only detects the eye tracking delay when the azimuth angle β = 0, the azimuth angle β is updated to 30°, that is, the azimuth angle β = 30°, and the step of "controlling the gaze point of the human eye-simulating device 200 to change rapidly from O to X" is re-entered, and the detection is directly completed.

[0179] The above can generate an overall eye tracking delay distribution diagram of the smart device 300 at multiple polar angles and multiple azimuth angles to comprehensively evaluate the eye tracking performance of the smart device 300 and solve the problem in related technologies that the eye tracking delay test fails to achieve full coverage of multiple viewing angles.

[0180] See also Figure 2 and Figure 3 The eye tracking accuracy performance testing method of the smart device 300 according to the embodiment of the present application includes:

[0181] Preset target marking points of the human eye-simulating device 200;

[0182] Controlling the human eye emulating device 200 to perform a second movement along a preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device 200 and the response annotation point position of the smart device 300;

[0183] Calibrate the target annotation points based on the spatial mapping relationship to obtain the response annotation points;

[0184] The eye tracking accuracy error of the smart device 300 at the target marked point is determined according to the response marked point and the target marked point.

[0185] The eye tracking accuracy performance testing method of the smart device 300 in the embodiment of the present application controls the human eye emulating device 200 to perform a second movement along a preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device 200 and the response annotation point position of the smart device 300, and then calibrates the position of the target annotation point based on the spatial mapping relationship to obtain the response annotation point. According to the response annotation point and the target annotation point, the eye tracking accuracy error of the smart device 300 at the target annotation point can be accurately determined.

[0186] The eye tracking accuracy performance testing method of the smart device 300 according to the embodiment of the present application can be used alone to implement the eye tracking accuracy test of the smart device 300, or it can be combined with the eye tracking delay test of the smart device 300 to improve the reliability of the delay test.

[0187] It should be noted that the explanation of the accuracy test part of the eye tracking delay performance test method of the smart device 300 in the aforementioned embodiment is also applicable to the eye tracking accuracy performance test method of the smart device 300 in the embodiment of the present application, and will not be elaborated here.

[0188] The difference is that after obtaining the response annotation point, the embodiment of the present application determines the eye tracking accuracy error of the smart device 300 at the target annotation point based on the response annotation point and the target annotation point.

[0189] For example, consider multiple target points on a preset path with multiple polar angle and azimuth combinations. A correspondence exists between the predetermined polar angle and the actual polar angle for a given azimuth angle. This correspondence represents the eye tracking accuracy error γ of the smart device 300: γ = |actual polar angle - predetermined polar angle|. After obtaining the differences between the predetermined polar angles and the actual polar angles, a distribution graph of the eye tracking accuracy error for the smart device 300 can be plotted, thereby obtaining the accuracy error range for the smart device 300. Alternatively, the eye tracking accuracy error value for the smart device 300 can be obtained by averaging all the differences.

[0190] See also Figure 2 and Figure 3 、 Figure 18 The eye tracking delay performance test method of the smart device 300 according to the embodiment of the present application is applied to the eye tracking delay performance test system 1000 of the smart device 300. The eye tracking delay performance test system 1000 includes an eye tracking delay performance test device 100, a human eye device 200, a smart device 300, and a control device 400. The eye tracking delay performance test method includes:

[0191] 031: The eye tracking latency performance testing device 100 controls the human eye emulating device 200 to perform a first movement along a preset path;

[0192] 032: When the human eye simulation device 200 moves to the response mark point, it outputs an encoder signal to the control device 400, and the control device 400 records a first timestamp corresponding to the encoder signal;

[0193] 033: When the smart device 300 detects that the human eye-simulating device 200 moves to the target marked point, the smart device 300 outputs a response signal to the control device 400. The control device 400 records a second timestamp corresponding to the response signal. The smart device 300 includes a display module and an eye tracking module. The response signal includes any one of the following:

[0194] Brightness change signal of the display module;

[0195] Level change signal of the eye tracking module;

[0196] 034: The control device 400 uploads the first timestamp and the second timestamp to the eye tracking latency performance testing device 100;

[0197] 035: The eye tracking latency performance testing device 100 determines the eye tracking latency of the smart device 300 at the response marked point based on the time difference between the first timestamp and the second timestamp;

[0198] Eye tracking latency performance testing methods also include:

[0199] 036: The eye tracking delay performance test device 100 presets the target marking point of the human eye simulation device 200;

[0200] 037: The eye tracking latency performance testing device 100 controls the human eye emulating device 200 to perform a second movement along a preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device 200 and the response annotation point position of the smart device 300;

[0201] 038: The eye tracking delay performance test device 100 calibrates the position of the target annotation point based on the spatial mapping relationship to obtain the response annotation point.

[0202] In some embodiments, a plurality of target marking points with a plurality of polar angles and a plurality of azimuth angles are set on the preset path.

[0203] In some embodiments, the response signal includes a brightness change signal of the display module. The eye tracking delay performance test method further includes:

[0204] The eye tracking delay performance testing device 100 sets a brightness change strategy for the display module. The brightness change strategy includes: when the eye tracking module detects that the human eye emulating device 200 moves to a predetermined polarity angle, the brightness of the display module changes, so that the brightness signal output by the smart device 300 undergoes a predetermined brightness change.

[0205] The eye tracking latency performance testing device 100 controls the human eye emulating device 200 to perform a second movement along a preset path to establish a spatial mapping relationship (i.e., 037) between the target annotation point position of the human eye emulating device 200 and the response annotation point position of the smart device 300, including:

[0206] The eye tracking latency performance testing device 100 controls the human eye emulating device 200 to perform a second movement along a preset path;

[0207] The eye tracking latency performance testing device 100 obtains the actual polar angle to which the human eye emulating device 200 moves when the brightness signal output by the smart device 300 undergoes a predetermined brightness change;

[0208] The eye tracking delay performance testing device 100 determines the eye tracking accuracy error of the smart device 300 at the predetermined polarity angle based on the predetermined polarity angle and the actual polarity angle;

[0209] The eye tracking delay performance testing device 100 establishes a spatial mapping relationship based on multiple eye tracking accuracy errors of the smart device 300 at multiple polar angles and multiple azimuth angles.

[0210] In some embodiments, during the process in which the eye tracking latency performance testing device 100 controls the human eye emulating device 200 to perform a second movement along a preset path, the eye tracking latency performance testing method further includes:

[0211] The eye tracking delay performance testing device 100 positively changes the polar angle of the human eye simulation device 200 according to a predetermined angle change amount;

[0212] The eye tracking latency performance testing device 100 determines whether a predetermined brightness change occurs in the brightness signal output by the smart device 300;

[0213] When the brightness signal output by the smart device 300 changes in a predetermined brightness, the eye tracking latency performance testing device 100 determines whether a predetermined angle change is less than an angle change threshold.

[0214] When the predetermined angle change is less than the angle change threshold, the eye tracking delay performance testing device 100 determines the eye tracking accuracy error of the smart device 300 at the predetermined polarity angle based on the predetermined polarity angle and the actual polarity angle.

[0215] When the predetermined angle change is greater than or equal to the angle change threshold, the eye tracking delay performance test device 100 reversely changes the polarity angle of the human eye simulation device 200 according to half of the predetermined angle change, and returns to the step where the eye tracking delay performance test device 100 determines whether the brightness signal output by the smart device 300 undergoes a predetermined brightness change.

[0216] In some embodiments, the response signal includes a level change signal of the eye tracking module. The eye tracking delay performance testing method further includes:

[0217] The eye tracking latency performance testing device 100 sets a level change strategy for the eye tracking module. The level change strategy includes: when the eye tracking module detects that the human eye device 200 moves to a predetermined polarity angle, the level of the eye tracking module changes, so that the level signal output by the smart device 300 changes to a predetermined level;

[0218] The eye tracking latency performance testing device 100 controls the human eye emulating device 200 to perform a second movement along a preset path to establish a spatial mapping relationship (i.e., 037) between the target annotation point position of the human eye emulating device 200 and the response annotation point position of the smart device 300, including:

[0219] The eye tracking latency performance testing device 100 controls the human eye emulating device 200 to perform a second movement along a preset path;

[0220] The eye tracking delay performance testing device 100 obtains the actual polar angle to which the human eye emulating device 200 moves when the level signal output by the smart device 300 undergoes a predetermined level change;

[0221] The eye tracking delay performance testing device 100 determines the eye tracking accuracy error of the smart device 300 at the predetermined polarity angle based on the predetermined polarity angle and the actual polarity angle;

[0222] The eye tracking delay performance testing device 100 establishes a spatial mapping relationship based on multiple eye tracking accuracy errors of the smart device 300 at multiple polar angles and multiple azimuth angles.

[0223] In some embodiments, during the process in which the eye tracking latency performance testing device 100 controls the human eye emulating device 200 to perform a second movement along a preset path, the eye tracking latency performance testing method further includes:

[0224] The eye tracking delay performance testing device 100 positively changes the polar angle of the human eye simulation device 200 according to a predetermined angle change amount;

[0225] The eye tracking delay performance testing device 100 determines whether a level signal output by the smart device 300 undergoes a predetermined level change;

[0226] When the level signal output by the smart device 300 changes to a predetermined level, the eye tracking delay performance testing device 100 determines whether a predetermined angle change is less than an angle change threshold.

[0227] When the predetermined angle change is less than the angle change threshold, the eye tracking delay performance testing device 100 determines the eye tracking accuracy error of the smart device 300 at the predetermined polarity angle based on the predetermined polarity angle and the actual polarity angle.

[0228] When the predetermined angle change is greater than or equal to the angle change threshold, the eye tracking delay performance test device 100 reversely changes the polarity angle of the human eye simulation device 200 according to half of the predetermined angle change, and returns to the step where the eye tracking delay performance test device 100 determines whether the level signal output by the smart device 300 undergoes a predetermined level change.

[0229] In some embodiments, when the human eye emulating device 200 moves to the response mark point, it outputs an encoder signal to the control device 400, and the control device 400 records a first timestamp (i.e., 032) corresponding to the encoder signal, including:

[0230] When the human eye emulating device 200 moves to a plurality of response marking points, it outputs a plurality of encoder signals to the control device 400, and the control device 400 records a plurality of first time stamps corresponding to the plurality of encoder signals;

[0231] When the smart device 300 detects that the human eye-simulating device 200 moves to the target marked point, it outputs a response signal to the control device 400. The control device 400 records the second timestamp (i.e., 033) corresponding to the response signal, including:

[0232] When the smart device 300 detects that the human eye-simulating device 200 moves to multiple target marking points, it outputs multiple response signals to the control device 400, and the control device 400 records multiple second timestamps corresponding to the multiple response signals;

[0233] The control device 400 uploads the first timestamp and the second timestamp to the eye tracking latency performance test device 100 (ie, 034), including:

[0234] The control device 400 uploads the plurality of first timestamps and the plurality of second timestamps to the eye tracking delay performance testing device 100;

[0235] The eye tracking latency performance testing device 100 determines the eye tracking latency (i.e., 035) of the smart device 300 at the response marked point based on the time difference between the first timestamp and the second timestamp, including:

[0236] The eye tracking delay performance testing device 100 determines a plurality of eye tracking delays of the smart device 300 at a plurality of response annotation points based on a plurality of time differences between the plurality of first timestamps and the plurality of second timestamps;

[0237] Eye tracking latency performance testing methods also include:

[0238] The eye tracking delay performance testing device 100 generates an eye tracking delay distribution diagram of the smart device 300 according to multiple eye tracking delays.

[0239] It should be noted that the explanation of the eye tracking delay performance test method of the smart device 300 in the aforementioned embodiment is also applicable to the eye tracking delay performance test method of the smart device 300 in the embodiment of the present application, and will not be elaborated here.

[0240] See also Figure 2 and Figure 3The eye tracking delay performance test system 1000 of the smart device 300 in the embodiment of the present application includes an eye tracking delay performance test device 100, a human eye emulating device 200, a smart device 300 and a control device 400. The eye tracking delay performance test device 100 is used to control the human eye emulating device 200 to perform a first movement along a preset path. The human eye emulating device 200 is used to output an encoder signal to the control device 400 when it moves to a response mark point, and the control device 400 is used to record a first timestamp corresponding to the encoder signal. The smart device 300 is used to output a response signal to the control device 400 when it detects that the human eye emulating device 200 has moved to a target mark point, and the control device 400 is used to record a second timestamp corresponding to the response signal. The smart device 300 includes a display module and an eye tracking module. The response signal includes any one of the following: a brightness change signal of the display module; a level change signal of the eye tracking module. The control device 400 uploads the first timestamp and the second timestamp to the eye tracking delay performance test device 100. The eye tracking latency performance testing device 100 is configured to determine the eye tracking latency of the smart device 300 at the response annotation point based on the time difference between the first timestamp and the second timestamp. The eye tracking latency performance testing device 100 is further configured to: preset a target annotation point for the human eye emulating device 200; control the human eye emulating device 200 to perform a second movement along a preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device 200 and the response annotation point position of the smart device 300; and calibrate the target annotation point based on the spatial mapping relationship to obtain the response annotation point.

[0241] It should be noted that the explanation of the eye tracking delay performance test method of the smart device 300 in the aforementioned embodiment is also applicable to the eye tracking delay performance test system 1000 of the smart device 300 in the embodiment of the present application, and will not be elaborated here.

[0242] See also Figure 19The eye tracking latency performance testing apparatus 500 for a smart device 300 according to an embodiment of the present application includes a first control module 510, a first acquisition module 520, a second acquisition module 530, a first determination module 540, a first setting module 550, a second control module 560, and a first calibration module 570. The first control module 510 is used to control the human eye emulating device 200 to perform a first movement along a preset path. The first acquisition module 520 is used to obtain a first timestamp corresponding to an encoder signal output when the human eye emulating device 200 moves to a response mark point. The second acquisition module 530 is used to obtain a second timestamp corresponding to a response signal output when the smart device 300 detects that the human eye emulating device 200 has moved to a target mark point. The smart device 300 includes a display module and an eye tracking module. The response signal includes any one of the following: a brightness change signal from the display module; a level change signal from the eye tracking module. The first determination module 540 is used to determine the eye tracking latency of the smart device 300 at the response mark point based on the time difference between the first and second timestamps. The first setting module 550 is used to preset the target annotation point of the human eye emulating device 200. The second control module 560 is used to control the human eye emulating device 200 to perform a second movement along a preset path to establish a spatial mapping relationship between the position of the target annotation point of the human eye emulating device 200 and the position of the response annotation point of the smart device 300. The first calibration module 570 is used to calibrate the position of the target annotation point based on the spatial mapping relationship to obtain the response annotation point.

[0243] In some embodiments, a plurality of target marking points with a plurality of polar angles and a plurality of azimuth angles are set on the preset path.

[0244] In some embodiments, the response signal includes a brightness change signal of the display module. The first setting module 550 is also used to set the brightness change strategy of the display module. The brightness change strategy includes: when the eye tracking module detects that the human eye emulating device 200 moves to a predetermined polarity angle, the brightness of the display module changes, so that the brightness signal output by the smart device 300 undergoes a predetermined brightness change. The second control module 560 is specifically used to: control the human eye emulating device 200 to perform a second movement according to a preset path; obtain the actual polarity angle to which the human eye emulating device 200 moves when the brightness signal output by the smart device 300 undergoes a predetermined brightness change; determine the eye tracking accuracy error of the smart device 300 at the predetermined polarity angle based on the predetermined polarity angle and the actual polarity angle; establish a spatial mapping relationship based on multiple eye tracking accuracy errors of the smart device 300 at multiple polarity angles and multiple azimuth angles.

[0245] In some embodiments, the second control module 560 is further used to, in the process of controlling the human eye emulating device 200 to perform a second movement along a preset path: positively change the polarity angle of the human eye emulating device 200 according to a predetermined angle change; determine whether the brightness signal output by the smart device 300 undergoes a predetermined brightness change; when the brightness signal output by the smart device 300 undergoes a predetermined brightness change, determine whether the predetermined angle change is less than an angle change threshold; when the predetermined angle change is less than the angle change threshold, execute the step of determining the eye tracking accuracy error of the smart device 300 at the predetermined polarity angle based on the predetermined polarity angle and the actual polarity angle; when the predetermined angle change is greater than or equal to the angle change threshold, reversely change the polarity angle of the human eye emulating device 200 according to half of the predetermined angle change, and return to the step of determining whether the brightness signal output by the smart device 300 undergoes a predetermined brightness change.

[0246] In some embodiments, the response signal includes a level change signal of the eye tracking module. The first setting module 550 is also used to set the level change strategy of the eye tracking module. The level change strategy includes: when the eye tracking module detects that the human eye emulating device 200 moves to a predetermined polarity angle, the level of the eye tracking module changes, so that the level signal output by the smart device 300 undergoes a predetermined level change. The second control module 560 is specifically used to: control the human eye emulating device 200 to perform a second movement along a preset path; obtain the actual polarity angle to which the human eye emulating device 200 moves when the level signal output by the smart device 300 undergoes a predetermined level change; determine the eye tracking accuracy error of the smart device 300 at the predetermined polarity angle based on the predetermined polarity angle and the actual polarity angle; establish a spatial mapping relationship based on multiple eye tracking accuracy errors of the smart device 300 at multiple polarity angles and multiple azimuth angles.

[0247] In some embodiments, the second control module 560 is further configured to, during the process of controlling the human eye emulating device 200 to perform a second movement along a preset path: positively change the polarity angle of the human eye emulating device 200 according to a predetermined angle change; determine whether a predetermined level change occurs in the level signal output by the smart device 300; when the predetermined level change occurs in the level signal output by the smart device 300, determine whether the predetermined angle change is less than an angle change threshold; when the predetermined angle change is less than the angle change threshold, determine the eye tracking accuracy error of the smart device 300 at the predetermined polarity angle based on the predetermined polarity angle and the actual polarity angle; when the predetermined angle change is greater than or equal to the angle change threshold, reversely change the polarity angle of the human eye emulating device 200 according to half of the predetermined angle change, and return to the step of determining whether the predetermined level change occurs in the level signal output by the smart device 300.

[0248] In certain embodiments, the first acquisition module 520 is specifically configured to acquire multiple first timestamps corresponding to multiple encoder signals output by the human eye emulating device 200 when the device moves to multiple response markup points. The second acquisition module 530 is specifically configured to acquire multiple second timestamps corresponding to multiple response signals output by the smart device 300 when the device detects that the human eye emulating device 200 has moved to multiple target markup points. The first determination module 540 is specifically configured to determine multiple eye tracking delays of the smart device 300 at the multiple response markup points based on multiple time differences between the multiple first timestamps and the multiple second timestamps. The first determination module 540 is further configured to generate an eye tracking delay distribution map of the smart device 300 based on the multiple eye tracking delays.

[0249] It should be noted that the explanation of the eye tracking delay performance testing method of the smart device 300 in the aforementioned embodiment is also applicable to the eye tracking delay performance testing device 500 of the smart device 300 in the embodiment of the present application, and will not be elaborated here.

[0250] See also Figure 20 The eye tracking accuracy performance testing device 600 of the smart device 300 according to the embodiment of the present application includes a second setting module 610, a third control module 620, a second calibration module 630, and a second determination module 640. The second setting module 610 is used to preset the target annotation point of the human eye emulating device 200. The third control module 620 is used to control the human eye emulating device 200 to perform a second movement along a preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device 200 and the response annotation point position of the smart device 300. The second calibration module 630 is used to calibrate the position of the target annotation point based on the spatial mapping relationship to obtain the response annotation point. The second determination module 640 is used to determine the eye tracking accuracy error of the smart device 300 at the target annotation point based on the response annotation point and the target annotation point.

[0251] It should be noted that the explanation of the eye tracking accuracy performance test method of the smart device 300 in the aforementioned embodiment is also applicable to the eye tracking accuracy performance test device 600 of the smart device 300 in the embodiment of the present application, and will not be elaborated here.

[0252] See also Figure 21 The eye tracking latency performance testing device 100 of the smart device 300 according to the embodiments of the present application includes one or more processors 110 and a memory 120, wherein the memory 120 stores a computer program. When the computer program is executed by the processor 110, the eye tracking latency performance testing method according to any of the above embodiments is implemented.

[0253] It should be noted that the explanation of the eye tracking delay performance test method of the smart device 300 in the aforementioned embodiment is also applicable to the eye tracking delay performance test device 100 of the smart device 300 in the embodiment of the present application, and will not be elaborated here.

[0254] See also Figure 22 The computer-readable storage medium 700 of the embodiment of the present application stores a computer program 710. When the program is executed by the processor 720, the eye tracking delay performance testing method of any of the above embodiments is implemented.

[0255] It should be noted that the explanation of the eye tracking delay performance testing method of the smart device 300 in the aforementioned embodiment is also applicable to the computer-readable storage medium 700 of the embodiment of the present application and will not be elaborated here.

[0256] See also Figure 23 The eye tracking accuracy performance testing device 800 of the smart device 300 according to the embodiments of the present application includes one or more processors 810 and a memory 820, wherein the memory 820 stores a computer program. When the computer program is executed by the processor 810, the eye tracking accuracy performance testing method according to any of the above embodiments is implemented.

[0257] It should be noted that the explanation of the eye tracking accuracy performance test method of the smart device 300 in the aforementioned embodiment is also applicable to the eye tracking accuracy performance test device 800 of the smart device 300 in the embodiment of the present application, and will not be elaborated here.

[0258] See also Figure 24 The computer-readable storage medium 900 of the embodiment of the present application stores a computer program 910. When the program is executed by the processor 920, the eye tracking accuracy performance test method of any of the above embodiments is implemented.

[0259] It should be noted that the explanation of the eye tracking accuracy performance testing method of the smart device 300 in the aforementioned embodiment is also applicable to the computer-readable storage medium 900 of the embodiment of the present application and will not be further explained here.

[0260] In summary, the eye tracking latency performance testing method, eye tracking accuracy performance testing method, eye tracking latency performance testing system 1000, eye tracking latency performance testing apparatus 500, eye tracking accuracy performance testing apparatus 600, eye tracking latency performance testing device 100, computer-readable storage medium 700, eye tracking accuracy performance testing device 800, and computer-readable storage medium 900 of the smart device 300 according to the embodiments of the present application, on the one hand, obtain a first timestamp corresponding to the encoder signal output when the human eye emulating device 200 moves to the response mark point; on the other hand, obtain a second timestamp corresponding to the response signal output when the smart device 300 detects that the human eye emulating device 200 has moved to the target mark point. Based on the time difference between the first timestamp and the second timestamp, the eye tracking latency of the smart device 300 at the response mark point can be determined. Because before the delay test, the target annotation point is calibrated to obtain the response annotation point based on the spatial mapping relationship between the target annotation point position of the human eye simulation device 200 and the response annotation point position of the smart device 300, the influence of the accuracy error on the delay test is eliminated, and the reliability of the eye tracking delay test is improved.

[0261] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0262] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0263] The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a computer-readable storage medium can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable storage media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disc read-only memory (CDROM). In addition, the computer-readable storage medium may even be paper or other suitable medium on which the program is printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing it in another suitable manner as necessary, and then stored in a computer memory.

[0264] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0265] Those skilled in the art will appreciate that all or part of the steps carried out in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a program, and the program can be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment. In addition, the various functional units in the various embodiments of the present application can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium mentioned above can be a read-only memory, a disk or an optical disk, etc.

[0266] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are illustrative and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application. The scope of the present application is defined by the claims and their equivalents.

Claims

1. A method for testing the delay performance of eye tracking of smart devices, characterized in that: include: controlling the human eye-simulating device to perform a first movement along a preset path; Obtaining a first timestamp corresponding to an encoder signal output when the human eye emulating device moves to a response marked point; Obtain a second timestamp corresponding to a response signal output by the smart device when detecting that the human eye-simulating device moves to a target marked point, wherein the smart device includes a display module and an eye tracking module, and the response signal includes any one of the following: A brightness change signal of the display module; A level change signal of the eye tracking module; determining, based on a time difference between the first timestamp and the second timestamp, an eye tracking delay of the smart device at the response marked point; The eye tracking delay performance testing method further includes: Presetting the target marking point of the human eye-simulating device; Controlling the human eye emulating device to perform a second movement along the preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device; The target annotation point is calibrated based on the spatial mapping relationship to obtain the response annotation point.

2. The eye tracking delay performance testing method according to claim 1, characterized in that: A plurality of target marking points, each comprising a combination of a plurality of polar angles and a plurality of azimuth angles, are arranged on the preset path.

3. The eye tracking delay performance testing method according to claim 2, characterized in that: The response signal includes a brightness change signal of the display module, and the eye tracking delay performance testing method further includes: Setting a brightness change strategy for the display module, the brightness change strategy comprising: when the eye tracking module detects that the human eye-simulating device moves to a predetermined polar angle, changing the brightness of the display module so that a brightness signal output by the smart device undergoes a predetermined brightness change; The controlling the human eye emulating device to perform a second movement along the preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device includes: controlling the human eye-simulating device to perform a second movement along the preset path; obtaining an actual polar angle to which the human eye emulating device moves when the brightness signal output by the smart device undergoes the predetermined brightness change; determining an eye tracking accuracy error of the smart device at the predetermined polarity angle according to the predetermined polarity angle and the actual polarity angle; The spatial mapping relationship is established according to a plurality of eye tracking accuracy errors of the smart device at a plurality of polar angles and a plurality of azimuth angles.

4. The eye tracking delay performance testing method according to claim 3, characterized in that: During the process of controlling the human eye emulating device to perform the second movement along the preset path, the eye tracking delay performance testing method further includes: positively changing the polar angle of the human eye-simulating device according to a predetermined angle change; Determining whether the brightness signal output by the smart device undergoes the predetermined brightness change; When the brightness signal output by the smart device undergoes the predetermined brightness change, determining whether the predetermined angle change is less than an angle change threshold; When the predetermined angle change is less than the angle change threshold, performing the step of determining the eye tracking accuracy error of the smart device at the predetermined polarity angle according to the predetermined polarity angle and the actual polarity angle; When the predetermined angle change is greater than or equal to the angle change threshold, the polarity angle of the human eye emulating device is reversely changed according to half of the predetermined angle change, and the process returns to the step of determining whether the brightness signal output by the smart device undergoes the predetermined brightness change.

5. The eye tracking delay performance testing method according to claim 2, characterized in that: The response signal includes a level change signal of the eye tracking module, and the eye tracking delay performance testing method further includes: Setting a level change strategy for the eye tracking module, the level change strategy comprising: when the eye tracking module detects that the human eye emulating device moves to a predetermined polarity angle, changing the level of the eye tracking module so that the level signal output by the smart device changes to a predetermined level; The controlling the human eye emulating device to perform a second movement along the preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device includes: controlling the human eye-simulating device to perform a second movement along the preset path; obtaining an actual polar angle to which the human eye simulating device moves when the level signal output by the smart device undergoes the predetermined level change; determining an eye tracking accuracy error of the smart device at the predetermined polarity angle according to the predetermined polarity angle and the actual polarity angle; The spatial mapping relationship is established according to a plurality of eye tracking accuracy errors of the smart device at a plurality of polar angles and a plurality of azimuth angles.

6. The eye tracking delay performance testing method according to claim 5, characterized in that: During the process of controlling the human eye emulating device to perform the second movement along the preset path, the eye tracking delay performance testing method further includes: positively changing the polar angle of the human eye-simulating device according to a predetermined angle change; Determining whether the level signal output by the smart device undergoes the predetermined level change; When the level signal output by the smart device undergoes the predetermined level change, determining whether the predetermined angle change is less than an angle change threshold; When the predetermined angle change is less than the angle change threshold, performing the step of determining the eye tracking accuracy error of the smart device at the predetermined polarity angle according to the predetermined polarity angle and the actual polarity angle; When the predetermined angle change is greater than or equal to the angle change threshold, the polarity angle of the human eye emulating device is reversely changed according to half of the predetermined angle change, and the process returns to the step of determining whether the level signal output by the smart device undergoes the predetermined level change.

7. The eye tracking delay performance testing method according to claim 2, characterized in that: The obtaining of a first timestamp corresponding to an encoder signal output when the human eye emulating device moves to a response mark point includes: Acquire a plurality of first timestamps corresponding to a plurality of encoder signals output when the human eye emulating device moves to a plurality of the response marking points; The obtaining of a second timestamp corresponding to a response signal output by the smart device when detecting that the human eye emulating device moves to a target marked point includes: Acquire a plurality of second timestamps corresponding to a plurality of response signals output by the smart device when detecting that the human eye emulating device moves to a plurality of target marking points; The determining, based on the time difference between the first timestamp and the second timestamp, the eye tracking delay of the smart device at the response marked point includes: determining, based on a plurality of the time differences between a plurality of the first timestamps and a plurality of the second timestamps, a plurality of the eye tracking delays of the smart device at a plurality of the response annotation points; The eye tracking delay performance testing method further includes: An eye tracking delay distribution graph of the smart device is generated according to the multiple eye tracking delays.

8. A device for testing the delay performance of eye tracking of smart devices, characterized in that: include: A first control module is used to control the human eye-simulating device to perform a first movement along a preset path; A first acquisition module is configured to acquire a first timestamp corresponding to an encoder signal output when the human eye emulating device moves to a response marked point; A second acquisition module is configured to acquire a second timestamp corresponding to a response signal output by the smart device when the smart device detects that the human eye-simulating device moves to a target marked point, wherein the smart device includes a display module and an eye tracking module, and the response signal includes any one of the following: A brightness change signal of the display module; A level change signal of the eye tracking module; a first determining module, configured to determine an eye tracking delay of the smart device at the response marked point based on a time difference between the first timestamp and the second timestamp; The eye tracking delay performance testing device also includes: A first setting module is used to preset the target marking point of the human eye simulation device; a second control module, configured to control the human eye emulating device to perform a second movement along the preset path, so as to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device; The first calibration module is configured to perform position calibration on the target annotation point based on the spatial mapping relationship to obtain the response annotation point.

9. An eye tracking delay performance test device for smart devices, characterized in that: The eye tracking delay performance testing device includes one or more processors and a memory, wherein the memory stores a computer program. When the computer program is executed by the processor, the eye tracking delay performance testing method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the eye tracking delay performance testing method described in any one of claims 1 to 7 is implemented.

11. A method for testing the delay performance of eye tracking of smart devices, characterized in that: An eye tracking delay performance test system for smart devices includes an eye tracking delay performance test device, a human eye-mimicking device, a smart device, and a control device. The eye tracking delay performance test method includes: The eye tracking delay performance testing device controls the human eye emulating device to perform a first movement along a preset path; When the human eye emulating device moves to the response marking point, it outputs an encoder signal to the control device, and the control device records a first timestamp corresponding to the encoder signal; When the smart device detects that the human eye-simulating device moves to a target marked point, it outputs a response signal to the control device, and the control device records a second timestamp corresponding to the response signal. The smart device includes a display module and an eye tracking module, and the response signal includes any one of the following: A brightness change signal of the display module; A level change signal of the eye tracking module; The control device uploads the first timestamp and the second timestamp to the eye tracking delay performance testing device; The eye tracking delay performance testing device determines the eye tracking delay of the smart device at the response marked point based on the time difference between the first timestamp and the second timestamp; The eye tracking delay performance testing method further includes: The eye tracking delay performance testing device presets the target marking point of the human eye simulation device; The eye tracking latency performance testing device controls the human eye emulating device to perform a second movement along the preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device; The eye tracking delay performance testing device calibrates the position of the target annotation point based on the spatial mapping relationship to obtain the response annotation point.

12. A system for testing the delay performance of eye tracking of smart devices, characterized in that: Including eye tracking delay performance test equipment, human eye simulation equipment, intelligent equipment and control equipment; The eye tracking delay performance testing device is used to control the human eye emulating device to perform a first movement along a preset path; The human eye-simulating device is used to output an encoder signal to the control device when moving to the response mark point, and the control device is used to record a first timestamp corresponding to the encoder signal; The smart device is configured to output a response signal to the control device when detecting that the human eye-simulating device moves to a target marked point, and the control device is configured to record a second timestamp corresponding to the response signal. The smart device includes a display module and an eye tracking module, and the response signal includes any one of the following: A brightness change signal of the display module; A level change signal of the eye tracking module; The control device is used to upload the first timestamp and the second timestamp to the eye tracking delay performance testing device; The eye tracking delay performance testing device is used to determine the eye tracking delay of the smart device at the response marked point based on the time difference between the first timestamp and the second timestamp; The eye tracking latency performance testing device is further configured to: preset a target annotation point of the human eye emulating device; and control the human eye emulating device to perform a second movement along the preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device; The target annotation point is calibrated based on the spatial mapping relationship to obtain the response annotation point.

13. A method for testing the eye tracking accuracy performance of a smart device, characterized in that: include: Preset target marking points of human eye-mimicking equipment; Controlling the human eye emulating device to perform a second movement along a preset path to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device; Performing position calibration on the target annotation point based on the spatial mapping relationship to obtain a response annotation point; An eye tracking accuracy error of the smart device at the target marked point is determined according to the response marked point and the target marked point.

14. A device for testing the eye tracking accuracy of a smart device, characterized in that: include: The second setting module is used to preset the target marking point of the human eye simulation device; a third control module, configured to control the human eye emulating device to perform a second movement along a preset path, so as to establish a spatial mapping relationship between the target annotation point position of the human eye emulating device and the response annotation point position of the smart device; A second calibration module is configured to perform position calibration on the target annotation point based on the spatial mapping relationship to obtain a response annotation point; The second determination module is configured to determine an eye tracking accuracy error of the smart device at the target marked point based on the response marked point and the target marked point.

15. An eye tracking accuracy performance test device for smart devices, characterized in that: The eye tracking accuracy performance testing device includes one or more processors and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the eye tracking accuracy performance testing method according to claim 13 is implemented.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the eye tracking accuracy performance testing method described in claim 13 is implemented.

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