Evaluation method for comparison of different projection display and interaction technologies

Abstract

The embodiment of the invention discloses an evaluation method for comparison of different projection display and interaction technologies. A specific embodiment of the method comprises the steps that a preset-format user questionnaire is created, the preset-format user questionnaire comprises a plurality of key experience indexes, and the preset-format user questionnaire is a questionnaire after a user fills in initial experience data according to a preset format; notifying a user to perform multi-scene interaction in the three-dimensional virtual environment to obtain an interaction data set; performing cognitive data determination on the user in the three-dimensional virtual environment to obtain user cognitive data; performing data integration on the interaction data set, the user physiological data, the user cognitive data and a preset format user questionnaire to obtain an integrated data set; and performing multi-dimensional scoring on the integrated data set to optimize the stereoscopic presentation system. According to the embodiment, the performance of the three-dimensional presentation system and the multi-modal interaction system is comprehensively and objectively analyzed through a multi-dimensional evaluation system.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of computer technology, and in particular to an evaluation method for comparing different projection display and interaction technologies. Background Art

[0002] With the rapid development of information technology, artificial intelligence and digital media, stereoscopic presentation technology and human-computer interaction technology have become core components of modern intelligent devices and systems. As a key means to provide realistic three-dimensional visual experience, stereoscopic presentation technology is widely used in film and television entertainment, medical care, education and other fields; at the same time, human-computer interaction technology plays a vital role in smart phones, virtual reality (VR), augmented reality (AR), smart homes and other devices. With the continuous advancement of these technologies, they are no longer limited to providing traditional visual experience or operating functions, but pay more attention to the user's immersion, interaction convenience, and the overall improvement of physiological and psychological reactions.

[0003] Stereoscopic presentation technology provides users with a three-dimensional visual experience through different display systems and has been widely used in many fields. Projection display systems usually use multi-screen projection or stereoscopic area projection to achieve the presentation of stereoscopic images. They are suitable for large scenes and multiple people watching at the same time and have good practicality. However, this technology is affected by ambient light, projection angle and screen quality, and the display effect may not be stable enough. Grating holographic display system uses grating or holographic film technology to achieve naked-eye 3D display. Users can watch stereoscopic images without wearing any auxiliary equipment, which improves the convenience of experience. However, due to the complexity of technical implementation, high manufacturing cost, and limited viewing angle range and resolution, this has a certain impact on image quality and user viewing experience. Wearable helmet display systems, such as virtual reality (VR) helmets and mixed reality (MR) glasses, wear display devices on the user's head, provide a highly immersive visual experience, and support interactive functions such as head tracking and gesture recognition. These devices have unique advantages in games, training and design, but due to the heavy weight and discomfort of the equipment, long-term use may cause physical discomfort such as visual fatigue and motion sickness. At the same time, the high cost of the equipment also limits its wide application.

[0004] At present, the evaluation of stereoscopic presentation systems mainly focuses on the measurement of technical parameters and the collection of user subjective feelings. The measurement of technical parameters includes the testing of physical indicators such as the system's resolution, refresh rate, delay and viewing angle range, which can objectively reflect the performance of the system. However, these parameters cannot fully reflect the user's subjective experience and physiological response, and lack consideration of the user's psychological and physiological load during use. User subjective evaluation obtains information such as user satisfaction, immersion and usage experience of the system through questionnaires or interviews. However, subjective evaluation is affected by individual differences and subjective factors of users, and the evaluation results may have large uncertainties and deviations, making it difficult to provide consistent and comparable evaluation data. Given the limitations of existing evaluation methods, it is difficult to comprehensively and objectively evaluate the performance and user experience of different stereoscopic presentation systems, and it is impossible to provide a strong basis for the improvement and optimization of the system. This situation restricts the further development and application promotion of stereoscopic presentation technology.

[0005] Existing interaction mode evaluation methods usually focus on the measurement of a single indicator, such as response time, recognition accuracy, and user satisfaction. Although these indicators can partially reflect the interaction performance, they lack comprehensive consideration of user experience, cognitive load, and physiological load. Although user subjective evaluation can collect user preferences and satisfaction with interaction modes, it is greatly affected by individual differences and subjective factors, which may lead to bias and uncertainty in the evaluation results.

[0006] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the invention

[0007] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0008] Some embodiments of the present disclosure propose an evaluation method for comparing different projection display and interaction technologies to solve one or more of the technical problems mentioned in the above background technology section.

[0009] In a first aspect, some embodiments of the present disclosure provide an evaluation method for comparing different projection display and interaction technologies, the method comprising: creating a preset format user questionnaire, wherein the preset format user questionnaire comprises: multiple key experience indicators, the preset format user questionnaire is a questionnaire after the user fills in the initial experience data in a preset format; notifying the user to perform multiple scene interactions in the three-dimensional virtual environment to obtain an interaction data set; determining the cognitive data in the three-dimensional virtual environment to obtain user cognitive data; collecting the physiological signal data of the user in the three-dimensional virtual environment to obtain user physiological data; integrating the interaction data set, the user physiological data, the user cognitive data and the preset format user questionnaire to obtain an integrated data set; and performing multi-dimensional scoring on the integrated data set to optimize the stereoscopic presentation system.

[0010] The present disclosure proposes a comprehensive multi-dimensional evaluation method, which aims to comprehensively and objectively evaluate the performance of different stereoscopic presentation technologies and multimodal interactive systems, covering stereoscopic presentation technologies such as projection display systems, grating holographic display systems, wearable helmet display systems, and multiple interactive modes such as touch, somatosensory, gestures, voice and eye movement. By combining user questionnaires, experimental verification and physiological signal analysis, the present disclosure comprehensively evaluates stereoscopic presentation systems and multimodal interactive systems from multiple dimensions, provides a consistency evaluation framework, and provides theoretical basis and data support for the optimization and development of related technologies. In the evaluation of stereoscopic presentation systems, the present disclosure systematically analyzes the subjective feelings of users such as immersion, stereoscopic feeling, embodiment, comfort and satisfaction under different systems through quantitative user questionnaire design, and reveals the differences in user experience of different systems through statistical analysis. In the user spatial cognition experiment, the user's spatial cognitive ability is objectively measured through carefully designed three-dimensional scenes and spatial tasks. The experimental results show that different stereoscopic presentation systems have a significant impact on users' spatial perception, which provides a scientific basis for evaluating the performance of the system in spatial presentation and cognitive support. In the physiological signal analysis, the user's heart rate, body temperature, blood oxygen saturation and other physiological indicators were monitored in real time, and the impact of the stereoscopic presentation system on the user's physiological load and fatigue was evaluated. The changing trend of the physiological data is consistent with the subjective fatigue evaluation results, which further verifies the effectiveness and reliability of this method. Based on the above multi-dimensional evaluation results, the performance and user experience of different stereoscopic presentation systems were comprehensively compared and analyzed. The experimental results show that the wearable helmet display system has outstanding performance in immersion and stereoscopic sense, but the physiological load is high; the projection display system has more advantages in comfort and physiological load, but the immersion is slightly inferior; the grating holographic display system has advantages in convenience and embodiment, but it still needs to be improved in spatial cognitive support. In the evaluation of multimodal interactive systems, this disclosure comprehensively evaluates the performance of various interactive methods in typical interactive tasks through scientific experimental design and systematic data analysis, and identifies the key factors affecting user experience. During the experiment, the user's operation time, accuracy, satisfaction and other indicators were recorded in detail, providing reliable data support for the optimization design of the interactive system. The results of multivariate analysis and correlation analysis show that there is a significant consistency between the user's subjective evaluation and the objective measurement results, which provides a theoretical basis for the reliability and effectiveness of the verification method. Specifically, touch interaction shows excellent operational convenience and accuracy, but may cause user fatigue; somatosensory and gesture interaction provide an intuitive and natural experience, but perform poorly in low-light environments; voice interaction is suitable for contactless operation, but is sensitive to environmental noise; eye movement interaction has a high sense of immersion, but lacks accuracy in fine operations. In response to these problems, this disclosure proposes a multimodal fusion optimization solution to improve the robustness of the system and user experience.Therefore, the method disclosed in this paper comprehensively and objectively analyzes the performance of the stereoscopic presentation system and the multimodal interaction system through a multi-dimensional evaluation system, fills the gap in existing evaluation methods, and provides a clear research direction for future technological innovation and system optimization. This method is not only applicable to multiple fields such as virtual reality, augmented reality, and smart home, but also provides theoretical support and practical guidance for promoting the development and popularization of human-computer interaction technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0012] Figure 1 is a flow chart of some embodiments of an evaluation method for comparing different projection display and interaction technologies according to the present disclosure; DETAILED DESCRIPTION

[0013] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0014] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0015] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0016] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0017] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0018] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0019] Figure 1 This is a process 100 of some embodiments of the evaluation method for comparing different projection display and interaction technologies disclosed in the present invention. The evaluation method for comparing different projection display and interaction technologies includes the following steps:

[0020] Step 101, creating a user questionnaire in a preset format, wherein the user questionnaire in the preset format includes: a plurality of key experience indicators, and the user questionnaire in the preset format is a questionnaire after the user fills in the initial experience data in accordance with the preset format.

[0021] In some embodiments, the executor (e.g., a computing device) of the evaluation method for comparing different projection display and interaction technologies can create a user questionnaire in a preset format, wherein the user questionnaire in the preset format includes: multiple key experience indicators, and the user questionnaire in the preset format is a questionnaire after the user fills in the initial experience data in a preset format.

[0022] Here, the above-mentioned multiple key experience indicators may include but are not limited to at least one of the following: immersion experience indicator, stereoscopic experience indicator. The above-mentioned initial experience data may refer to the user's subjective experience data of the three-dimensional virtual environment. For example, the above-mentioned initial experience data may refer to the user's belief that the immersive experience of the three-dimensional virtual environment is good. The above-mentioned preset format may refer to the format of the preset question setting and the corresponding scoring options. The above-mentioned scoring options adopt the Likert five-point scale. For example, the above-mentioned preset format may refer to the preset "Question setting: How immersed do you feel in the three-dimensional virtual environment? Scoring options: 1 point (not immersed at all), 2 points (general immersion), 3 points (good immersion), 4 points (relatively immersed), 5 points (very immersed)." The above-mentioned three-dimensional virtual environment may refer to a three-dimensional virtual test room.

[0023] It should be noted that the above-mentioned computing device can be hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or it can be implemented as a single server or a single terminal device. For example, the computing device can be the above-mentioned target terminal. When the computing device is embodied as software, it can be installed in the hardware devices listed above. It can be implemented as multiple software or software modules for providing distributed services, for example, or it can be implemented as a single software or software module. No specific limitation is made here.

[0024] Step 102 , notifying the user to perform multiple scene interactions in the three-dimensional virtual environment to obtain an interaction data set.

[0025] In some embodiments, the execution entity may notify the user to perform multiple scene interactions in the three-dimensional virtual environment to obtain an interaction data set.

[0026] Here, the above-mentioned multiple scenes may refer to scenes in which multiple movable objects are randomly arranged.

[0027] Optionally, the execution subject may notify the user to perform multiple scene interactions in the three-dimensional virtual environment to obtain an interaction data set through the following steps:

[0028] The first step is to notify the user to drag the target object to a preset position in the three-dimensional virtual environment to obtain the position of the target object.

[0029] Here, the target object may refer to a 10×10 hollow cube. The preset position may refer to the center position of the ground of the three-dimensional virtual environment.

[0030] In the second step, in response to determining that the user dragging is completed, determining the dragging time and position dragging error of the user.

[0031] Here, the dragging time may refer to the time taken by the user to drag the target object. The position dragging error may refer to the error between the position of the target object and the preset position.

[0032] The third step is to notify the user to reset the moved object to the initial marked position in the three-dimensional virtual environment to obtain the position of the object after the move.

[0033] Here, the object to be moved may refer to a 5×5 hollow cube. The initial marking position may refer to the position of the three-dimensional coordinates (2, 3, 4) of the three-dimensional virtual environment.

[0034] In the fourth step, in response to determining that the user reset is completed, determining the reset time of the user.

[0035] Here, the above reset time may refer to the time taken by the user to move the moved object to the initial marked position.

[0036] The fifth step is to notify the user to adjust the azimuth viewing angle of the virtual camera at the designated position in the three-dimensional virtual environment, wherein the azimuth viewing angle is the frontal viewing angle for observing the target object.

[0037] Step 6: In response to determining that the above user adjustment is completed, determine the adjustment time.

[0038] Here, the adjustment time may refer to the time taken by the user to adjust the orientation and viewing angle of the virtual camera.

[0039] Step 7: Notify the user to zoom the virtual camera according to a preset zoom level.

[0040] Here, the above-mentioned zooming may refer to enlarging or reducing. The above-mentioned preset zooming degree may refer to a preset zooming degree. For example, the above-mentioned preset zooming degree may refer to a preset “zooming in 2 times”.

[0041] In step 8, in response to determining that the user zooming is completed, determine the zooming time.

[0042] The ninth step is to notify the user to measure the distance between the target object position and the moved object position according to a preset number of times.

[0043] Here, the preset number of times may refer to a pre-set number of times. For example, the preset number of times may refer to 3 times.

[0044] In step 10, in response to determining that the user measurement is completed, determining the measurement time and the number of measurement errors.

[0045] Here, the number of measurement errors may refer to the number of times that the distance tested by the user is different from the actual distance.

[0046] In the eleventh step, the dragging time, the position dragging error, the reset time, the adjustment time, the zoom time, the measurement time and the number of measurement errors are combined into an interactive data set.

[0047] Here, the above combination may refer to a merger.

[0048] Step 103: determining cognitive data of the user in the three-dimensional virtual environment to obtain user cognitive data.

[0049] In some embodiments, the execution entity may determine cognitive data of the user in the three-dimensional virtual environment to obtain user cognitive data.

[0050] Optionally, the execution subject may determine the cognitive data of the user in the three-dimensional virtual environment through the following steps to obtain the user cognitive data:

[0051] The first step is to notify the user to view the spatial position relationship of objects in the three-dimensional virtual environment according to a preset time.

[0052] Here, the preset duration may refer to a pre-set duration. For example, the preset duration may refer to 2 minutes.

[0053] In the second step, in response to determining that the user has finished viewing, the user is notified to draw the spatial position relationship of the objects to obtain a spatial position diagram of the objects after drawing.

[0054] Here, the above-mentioned drawn object space position map may refer to a two-dimensional image including the spatial position relationship of the object.

[0055] The third step is to determine the accuracy of the spatial position map of the object drawn above to obtain the user accuracy.

[0056] Here, the accuracy rate may refer to the similarity between the drawn object space position diagram and the actual object space position relationship in the three-dimensional virtual environment. For example, the accuracy rate may refer to 80%.

[0057] The fourth step is to determine the completion time of the above-drawn object space position diagram to obtain the user completion time.

[0058] Here, the completion time may refer to the time taken by the user to draw the spatial position map of the drawn object.

[0059] The fifth step is to determine the error distance of the object space position map drawn above to obtain the user error distance.

[0060] Here, the user error distance may refer to the error distance between the drawn object space position map and the actual object space position relationship in the three-dimensional virtual environment.

[0061] The sixth step is to perform data analysis on the user accuracy, the user completion time and the user error distance to obtain user cognitive data.

[0062] As an example, the execution entity may perform data analysis on the user accuracy, the user completion time, and the user error distance through a multi-level analysis method (AHP) to obtain user cognition data.

[0063] Step 104 , collecting physiological signal data of the user in the three-dimensional virtual environment to obtain user physiological data.

[0064] In some embodiments, the execution entity may collect physiological signal data of the user in the three-dimensional virtual environment to obtain physiological data of the user.

[0065] Here, the user physiological data may refer to heart rate data. The user physiological data may also refer to brain wave data. The user physiological data may be used to evaluate the physiological burden of the user under different interaction modes.

[0066] As an example, the above-mentioned execution entity can collect the user's physiological data in real time through wearable devices before, during and after the user experience, quantify the user's physical reaction during the operation, and then evaluate the impact of different interaction methods on the user's physical fatigue and psychological stress.

[0067] Step 105 , integrating the above interaction data set, the above user physiological data, the above user cognitive data and the above user questionnaire in the preset format to obtain an integrated data set.

[0068] In some embodiments, the execution entity may integrate the interaction data set, the user physiological data, the user cognitive data, and the user questionnaire in the preset format to obtain an integrated data set.

[0069] Optionally, the execution subject may integrate the interaction data set, the user physiological data, the user cognitive data and the user questionnaire in the preset format through the following steps to obtain an integrated data set:

[0070] The first step is to associate the above interaction data set, the above user physiological data, the above user cognitive data and the above preset format user questionnaire to obtain an associated data set.

[0071] The second step is to clean the above associated data set to obtain a cleaned data set.

[0072] Here, the cleaned data set may refer to a data set after removing duplicate data from the associated data set.

[0073] The third step is to normalize the cleaned data set to obtain the processed data set as the integrated data set.

[0074] Step 106 , performing multi-dimensional scoring on the integrated data set to optimize the stereoscopic presentation system.

[0075] In some embodiments, the execution entity may perform multi-dimensional scoring on the integrated data set to optimize the stereoscopic presentation system.

[0076] Here, the multi-dimensional scoring may refer to scoring in multiple dimensions. The multiple dimensions may include but are not limited to at least one of the following: physiological signal dimension, user questionnaire dimension.

[0077] As an example, the execution entity may use principal component analysis to perform multi-dimensional scoring on the integrated data set to optimize the stereoscopic presentation system.

[0078] Optionally, the execution subject may perform multi-dimensional scoring on the integrated data set through the following steps to optimize the stereoscopic presentation system:

[0079] In the first step, missing values ​​are filled in the above integrated data set to generate a filled data set.

[0080] As an example, the execution entity may use an interpolation method to fill missing values ​​in the integrated data set to generate a filled data set.

[0081] The second step is to remove outliers from the above-mentioned filled data set to generate a removed data set.

[0082] As an example, the execution subject may determine the standard deviation and mean of the padded data set. Then, the padded data that exceeds the mean plus or minus a certain number of standard deviations (e.g., mean ± 3 standard deviations) is determined as outlier data. Finally, the outlier data is removed from the padded data set to obtain a removed data set.

[0083] The third step is to input the above-mentioned eliminated data set into the performance evaluation model to obtain the performance evaluated data set.

[0084] Here, the above-mentioned performance evaluation model may refer to a model used to evaluate the performance of a stereoscopic presentation system and an interactive modality. The above-mentioned performance evaluation model integrates multi-dimensional indicators such as task completion time, operation error rate, user satisfaction, physiological load, etc., uses an analytical method (such as fuzzy comprehensive evaluation method) to determine the indicator weight, and then determines the comprehensive score, and uses principal component analysis PCA to perform multi-dimensional comparison, and finally achieves a comprehensive evaluation of the system and modality, and obtains a performance evaluation data set.

[0085] The fourth step is to determine the indicator weights for the above performance evaluation data set, and perform weighted processing on the above performance evaluation data set according to the determined indicator weights to generate a comprehensive data score to optimize the stereoscopic presentation system.

[0086] Here, the above-mentioned index weights may include: task completion time weight, user satisfaction weight, operation error rate weight and physiological load weight. The above-mentioned comprehensive data score = task completion time index value × task completion time weight + operation error rate index value × operation error rate weight + user satisfaction index value × user satisfaction weight + physiological load index value × physiological load weight.

[0087] The first to fourth steps mentioned above comprehensively and objectively analyze the performance of the stereoscopic presentation system and the multimodal interaction system through a multi-dimensional evaluation system, filling the gap in existing evaluation methods and providing a clear research direction for future technological innovation and system optimization, while improving the system's robustness and user experience.

[0088] The technical details are further described below in conjunction with embodiments.

[0089] Example 1

[0090] Some embodiments of the evaluation method for comparing different projection display and interaction technologies disclosed in Example 1 may include the following steps:

[0091] 1. Questionnaire Design

[0092] 1. How immersed do you feel when using this stereoscopic rendering system?

[0093] Options: 1 (not at all immersive) to 5 (very immersive)

[0094] 2. What do you think of the 3D effect?

[0095] Options: 1 (no three-dimensional effect) to 5 (strong three-dimensional effect).

[0096] 3. During the experience, did you feel that you were integrated into the environment?

[0097] Options: 1 (not at all) to 5 (very strongly).

[0098] 4. How comfortable did you feel during the experience?

[0099] Options: 1 (very uncomfortable) to 5 (very comfortable).

[0100] 5. How satisfied are you with the stereoscopic presentation system overall?

[0101] Options: 1 (very dissatisfied) to 5 (very satisfied).

[0102] 6. When using this interaction mode, do you feel it is simple and easy to use?

[0103] Options: 1 (very inconvenient) to 5 (very convenient)

[0104] 7. When using this interaction mode, do you feel that the operation is smooth without lag or interruption? Can the system respond to your input operation in time without noticeable delay?

[0105] Options: 1 (very choppy / slow to respond) to 5 (very smooth / responsive).

[0106] 8. Do you find it difficult to learn to use this interaction mode? Does it take a long time to adapt?

[0107] Options: 1 (very difficult) to 5 (very easy).

[0108] 9. When using this interactive mode, do you feel comfortable and does it not cause fatigue? Do you feel dizzy, hand fatigue or eye discomfort during long-term use?

[0109] Options: 1 (very uncomfortable) to 5 (very comfortable).

[0110] 10. Do you think this interaction mode has application potential in other scenarios?

[0111] Options: 1 (no potential at all) to 5 (very potential).

[0112] 11. Please rank the following interaction modes (from most satisfactory to least satisfactory).

[0113] Options: touch, somatosensory, gesture, voice, eye movement.

[0114] 2. User Space Cognition Experiment

[0115] 1. Purpose

[0116] By designing specific spatial cognition tasks, the spatial cognition ability of users in different stereoscopic presentation systems is evaluated, including the understanding and memory of spatial relationships such as object position, distance, direction, etc.

[0117] 2. Experimental Design

[0118] 2.1 Experimental scene setting

[0119] Scene design: Create a three-dimensional virtual scene containing multiple objects with different positions, sizes and colors and random positions.

[0120] Number of objects: It is recommended to set 5-10 objects to increase the difficulty of the task while avoiding excessive complexity that causes user fatigue.

[0121] 2.2 Experimental Process

[0122] Observation phase: Users watch the scene in the stereoscopic presentation system for 1 minute. Users are encouraged to remember the spatial position relationship of objects as much as possible.

[0123] Description stage: Turn off the display and let the user describe or draw the spatial position relationship of objects without watching, including up and down, left and right, far and near, etc.

[0124] Repeat the experiment: Each user performed the experiment three times under each stereoscopic presentation system to reduce the influence of accidental factors.

[0125] 2.3 Data Collection and Analysis

[0126] Accuracy calculation: Count the number of spatial relationships correctly described by the user and calculate the accuracy. Accuracy = (number of correctly described spatial relationships / total number of spatial relationships) × 100%

[0127] Response time: Record the time it takes the user to complete the description.

[0128] Spatial error measurement: If the user draws the position of an object, calculate the distance error between the position drawn by the user and the actual position, using three-dimensional coordinates for calculation.

[0129] Data analysis: Compare the accuracy, reaction time, and spatial error of different stereoscopic presentation systems. Use statistical methods (such as repeated measures analysis of variance) to evaluate the differences between systems. Analyze the correlation between users' spatial cognition ability and subjective experience indicators.

[0130] 3. Physiological signal analysis

[0131] 3.1 Purpose

[0132] By monitoring the user's physiological signals in a stereoscopic presentation environment, the system's impact on the user's physiological load and fatigue is evaluated, including indicators such as heart rate, body temperature and blood oxygen saturation.

[0133] 3.2 Measurement Method

[0134] 1. Heart rate (HR) measurement

[0135] Equipment: Use a heart rate monitor belt, bracelet or electrocardiograph to ensure accurate and real-time measurement.

[0136] Measurement process:

[0137] Baseline measurement: Before the user starts the experience, record the heart rate at rest as the baseline value.

[0138] Real-time monitoring: During the experience, the heart rate is continuously monitored and the changes in heart rate are recorded.

[0139] Note: Make sure the device is worn correctly and the data is recorded correctly.

[0140] 2. Temperature measurement

[0141] Equipment: Use an infrared thermometer or a patch-type temperature sensor.

[0142] Measurement process:

[0143] Measuring location: forehead, ear or armpit, choose the appropriate measurement method.

[0144] Measurement time: Measure once before, during, and after the experience.

[0145] Note: Keep the measurement environment stable and avoid interference from external factors.

[0146] 3. Blood oxygen saturation (SpO2) measurement

[0147] Equipment: Finger clip oximeter or wrist blood oxygen monitor.

[0148] Measurement process:

[0149] Baseline measurement: Record baseline blood oxygen saturation value before the experience.

[0150] Real-time monitoring: During the experience, blood oxygen saturation is recorded regularly (such as every 5 minutes).

[0151] Note: Make sure your fingers are warm to avoid poor blood circulation affecting the measurement.

[0152] 4. Data Analysis

[0153] Heart rate variability:

[0154] Calculate the relative rate of change of heart rate.

[0155] Formula: Heart rate change rate = (experienced heart rate - baseline heart rate) / baseline heart rate × 100%

[0156] Temperature changes:

[0157] Calculate the difference in body temperature before and after the experience.

[0158] Formula: Body temperature change = body temperature after experience - baseline body temperature

[0159] Blood oxygen changes:

[0160] Observe whether the blood oxygen saturation decreases significantly.

[0161] Load Assessment:

[0162] Compare the changes in physiological indicators with the normal range to assess the user's physiological load.

[0163] Combined with subjective feelings, determine whether there is excessive load or fatigue.

[0164] 4. Fatigue analysis

[0165] 4.1. Time-based subjective fatigue assessment

[0166] method:

[0167] During the experience, users are asked to fill out a fatigue questionnaire at regular intervals (such as 15 minutes).

[0168] Questionnaire design:

[0169] Using a visual analogue scale (VAS), 0 indicated no fatigue at all and 10 indicated extreme fatigue.

[0170] Example question: What is your current level of fatigue?

[0171] Data Analysis:

[0172] Plot the change of fatigue over time.

[0173] Calculate the fatigue growth rate and evaluate the rate of fatigue accumulation.

[0174] 4.2 Changes in User Experiment Accuracy over Time

[0175] method:

[0176] Divide the user space cognition experiment into multiple time periods (such as one period every 30 minutes).

[0177] Record the experimental accuracy in each time period.

[0178] Data Analysis:

[0179] Compare the accuracy over different time periods to see if there is a downward trend.

[0180] Use linear regression or trend analysis to assess changes in accuracy over time.

[0181] 4.3 Changes of physiological signals over time

[0182] method:

[0183] Continuously monitor physiological signals and record them regularly (e.g., every 5 minutes).

[0184] Indicator analysis:

[0185] Heart rate variability (HRV): This measures fluctuations in your heart rate over time. Decreased HRV is often associated with increased fatigue.

[0186] Temperature trend: Observe whether the body temperature continues to rise, which may be related to fatigue and stress response.

[0187] Data Analysis:

[0188] Time series analysis methods were used to assess trends and rates of change in physiological indicators.

[0189] Combined with subjective fatigue, the correlation between changes in physiological indicators and fatigue is verified.

[0190] 5. Interactive modal verification experiment

[0191] 5.1 Purpose

[0192] This experiment aims to verify the user's operation efficiency and accuracy in multiple interaction modes such as touch, somatosensory, gesture, voice and eye movement by designing standardized interaction tasks. The experiment covers typical interaction scenarios such as object movement in three-dimensional space, object resetting, perspective movement, perspective zooming and object ranging, and comprehensively evaluates the performance of each interaction mode to provide objective data support for subsequent system optimization and technology selection.

[0193] 5.2 Experimental Design

[0194] Experimental scene setup

[0195] Scene design: The experiment was conducted in a virtual environment containing multiple three-dimensional objects with different shapes, colors and sizes, randomly distributed in the scene. The background of the scene was a simple neutral color to reduce visual interference.

[0196] Interactive equipment: According to the interactive mode of the experimental design, use the corresponding hardware equipment (such as touch screen, somatosensory camera, gesture recognition sensor, voice recognition equipment and eye tracking equipment) for testing.

[0197] Task description: The experimental task includes the following five parts, each task targets a specific interactive function to cover the common operational needs of users.

[0198] Experimental Procedure

[0199] Task 1: Movement of objects in three-dimensional space

[0200] Task description: The user needs to select and drag the target object in the virtual scene to move it to the specified location. The task will indicate the target location and require the user to complete the operation as accurately as possible.

[0201] Operation requirements: Users need to use different interaction modes (touch, somatosensory, gesture, voice, eye movement) to move objects and try to complete the task in the shortest time.

[0202] Data recording: record task completion time and operation error (deviation between target position and actual position).

[0203] Task 2: Object repositioning

[0204] Task description: The user needs to restore the randomly moved object to its original position. The scene will indicate the object's original position.

[0205] Operation requirements: Users need to use different interaction modes to select objects and complete the reset operation to minimize the operation steps and time.

[0206] Data logging: records the task time of the reset operation.

[0207] Task 3: View Movement

[0208] Task description: The user needs to adjust the perspective of the virtual camera through the interactive mode in order to observe a specific target object in the scene. The task requires the user to pan the perspective to the specified position and maintain a frontal perspective of the target object.

[0209] Operation requirements: The user moves the viewing angle by dragging the screen with touch, somatosensory movements, gesture control, voice commands or eye tracking.

[0210] Data recording: Record the time when the view moves.

[0211] Task 4: Zooming the view

[0212] Task description: The user needs to adjust the zoom level of the virtual camera to zoom in or out on the target object so that it fills the field of view.

[0213] Operation requirements: Users use different interaction modes (such as two-finger zoom, somatosensory gestures, voice commands "zoom in / out", eye movement gaze point zoom) to perform zoom operations.

[0214] Data logging: Records the zoom operation time.

[0215] Task 5: Object Distance Measurement

[0216] Task description: The user needs to estimate and measure the distance between two objects in the scene. The objects to be measured will be marked in the scene, and the user needs to select the object and give the measurement result.

[0217] Operation requirements: Users can complete distance measurement operations through touch and click, somatosensory selection, gesture selection, voice selection, and eye movement selection.

[0218] Data recording: record measurement time and number of operation errors.

[0219] 5.3 Data Collection and Analysis

[0220] Data Collection:

[0221] During the experiment, each participant's task performance in all interaction modes will be recorded. Sample data includes task completion time, operation error, and number of incorrect operations.

[0222] In each interaction mode, data from at least 10 users were collected to ensure that the sample size was sufficient for effective statistical analysis.

[0223] Data Analysis:

[0224] Efficiency analysis: The average completion time and standard deviation of each task in different interaction modes were calculated to evaluate the operational efficiency of each mode. Analysis of variance (ANOVA) was used to detect time differences between different modes.

[0225] Accuracy analysis: Count the operation errors and the number of incorrect operations, calculate the error rate and average error value, and compare the accuracy performance of each interaction mode.

[0226] User preference analysis: Combined with the user's subjective feedback in the questionnaire, evaluate the user's preference for different interaction modes, and analyze the consistency between subjective evaluation and experimental data.

[0227] Correlation analysis: Use the Pearson correlation coefficient or regression analysis to evaluate the correlation between task completion time, operation error, and user subjective experience indicators (such as satisfaction and comfort).

[0228] Comprehensive performance scoring: Build a multi-dimensional performance scoring model, comprehensively consider factors such as efficiency, accuracy, and user satisfaction, and score and rank the overall performance of each interaction mode.

[0229] Experimental conclusion: Through experimental data analysis, we can identify the advantages and disadvantages of each interaction mode, provide a reference for the design and optimization of the interactive system, and provide scientific support for the selection of interaction methods in different application scenarios.

[0230] 6. Comprehensive evaluation and comparison

[0231] 6.1 Data Summary

[0232] Stereoscopic rendering module

[0233] Subjective indicators: immersion, three-dimensionality, embodiment, comfort, satisfaction, and fatigue.

[0234] Objective indicators: spatial cognition experiment accuracy, reaction time, spatial error, and physiological signal changes.

[0235] Multimodal interaction module

[0236] Subjective indicators: include the user's immersion, comfort, satisfaction, and fatigue in different interaction modes. Users evaluate the experience of each interaction mode through questionnaire scoring, with scores ranging from 1 (very poor) to 5 (very good).

[0237] Objective indicators: include the accuracy and efficiency of users in interactive tasks.

[0238] Accuracy: Based on the correctness of the user's operation in the experimental task, the error rate and error size are calculated.

[0239] Efficiency: Count the user's operation efficiency based on the task completion time, and record the average time and standard deviation.

[0240] 6.2 Statistical Analysis

[0241] Stereoscopic rendering module

[0242] Multivariate analysis:

[0243] Use multivariate statistical methods (such as principal component analysis and factor analysis) to find the main factors that affect user experience.

[0244] Comparison between systems:

[0245] Compare the performance of different stereoscopic presentation systems on various indicators and identify their advantages and disadvantages.

[0246] Correlation analysis:

[0247] Analyze the correlation between subjective experience indicators and objective measurement indicators to understand the relationship between subjective feelings and physiological reactions.

[0248] Multimodal interaction module

[0249] Comparison between modalities:

[0250] The performance of the five interaction modes of touch, somatosensory, gesture, voice and eye movement was compared in terms of accuracy, efficiency, immersion and comfort. Analysis of variance (ANOVA) was used to test the differences between the modes and determine the advantages and disadvantages of different interaction modes.

[0251] 6.3 Results Interpretation

[0252] Strengths Identification:

[0253] Identify systems that excel in certain metrics and learn about their technical features and user feedback.

[0254] Problem discovery:

[0255] Identify problems in the user experience, such as lack of comfort, increased fatigue, etc., to provide a basis for system improvements.

[0256] Improvement suggestions:

[0257] Based on the evaluation results, optimization solutions for different stereoscopic presentation systems and interactive systems are proposed to improve user experience and system performance.

[0258] 7. Overview of implementation steps

[0259] Preparation stage:

[0260] Determine the 3D presentation system, interactive equipment, and experimental scene required for the experiment, and configure the relevant hardware and software environment.

[0261] Recruit subjects and obtain informed consent.

[0262] Questionnaire design and testing:

[0263] Prepare user questionnaires and conduct pre-experimental verification.

[0264] Experimental execution:

[0265] According to the designed experimental process, the subjects were asked to experience different stereoscopic presentation systems and five interactive modes: touch, somatosensory, gesture, voice and eye movement, and complete all designed stereoscopic presentation and interactive tasks.

[0266] Collect questionnaires, spatial cognition experimental data, physiological signals, and operational data.

[0267] Data processing: organize and clean experimental data, remove outliers and invalid data, and perform normalization.

[0268] Data Analysis: Use appropriate statistical methods to analyze data and draw graphs.

[0269] Reporting of results: Write a lab report describing your findings and conclusions.

[0270] Improvement feedback: Feedback the results to the relevant technical teams to guide system improvements.

[0271] The above descriptions are only some preferred embodiments of the present disclosure and the explanation of the technical principles used above. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above invention concept. For example, the above features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. An evaluation method for comparing different projection display and interaction technologies, comprising: Creating a user questionnaire in a preset format, wherein the user questionnaire in the preset format includes: a plurality of key experience indicators, and the user questionnaire in the preset format is a questionnaire after the user fills in the initial experience data in a preset format; Notifying the user to perform multiple scene interactions in the three-dimensional virtual environment to obtain an interaction data set; Determining cognitive data of the user in the three-dimensional virtual environment to obtain user cognitive data; Collecting physiological signal data of the user in the three-dimensional virtual environment to obtain user physiological data; Integrating the interaction data set, the user physiological data, the user cognitive data and the preset format user questionnaire to obtain an integrated data set; The integrated data set is scored in multiple dimensions to optimize the stereoscopic presentation system.

2. The method according to claim 1, wherein: The notifying the user to perform multiple scene interactions in the three-dimensional virtual environment to obtain an interaction data set includes: Notify the user to drag the target object to a preset position in the three-dimensional virtual environment to obtain the position of the target object; In response to determining that the user dragging is completed, determining the dragging time and position dragging error of the user; Notify the user to reset the moved object to the initial marked position in the three-dimensional virtual environment to obtain the position of the object after the move; In response to determining that the user reset is complete, determining a reset time for the user; Notify the user to adjust the azimuth viewing angle of the virtual camera at a designated position in the three-dimensional virtual environment, wherein the azimuth viewing angle is a frontal viewing angle for observing the target object; In response to determining that the user adjustment is completed, determining an adjustment time; Notifying the user to zoom the virtual camera according to a preset zoom level; In response to determining that the user zooming is completed, determining a zooming time; Notify the user to measure the distance between the position of the target object and the position of the moved object according to a preset number of times; In response to determining that the user measurement is completed, determining a measurement time and a number of measurement errors; The dragging time, the position dragging error, the resetting time, the adjusting time, the zooming time, the measuring time and the number of measuring errors are combined into an interactive data set.

3. The method according to claim 1, wherein: Determining the cognitive data of the user in the three-dimensional virtual environment to obtain the user cognitive data includes: Notifying the user to view the spatial position relationship of objects in the three-dimensional virtual environment according to a preset time length; In response to determining that the user has finished viewing, informing the user to draw the spatial position relationship of the objects to obtain a drawn spatial position diagram of the objects; Determining the accuracy of the drawn object space position map to obtain a user accuracy rate; Determining the completion time of the drawn object space position diagram to obtain a user completion time; Determining the error distance of the drawn object space position map to obtain a user error distance; Data analysis is performed on the user accuracy rate, the user completion time and the user error distance to obtain user cognition data.

4. The method according to claim 1, wherein: The step of integrating the interactive data set, the user physiological data, the user cognitive data and the preset format user questionnaire to obtain an integrated data set includes: Associating the interaction data set, the user physiological data, the user cognitive data and the preset format user questionnaire to obtain an associated data set; Performing data cleaning on the associated data set to obtain a cleaned data set; The cleaned data set is normalized to obtain a processed data set as an integrated data set.

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