Eye Features Research Articles

What is unique about the human eye? Comparative image analysis on the external eye morphology of human and nonhuman great apes

The gaze-signaling hypothesis and the related cooperative-eye hypothesis posit that humans have evolved special external eye morphology, including exposed white sclera (the white of the eye), to enhance the visibility of eye-gaze direction and thereby facilitate conspecific communication through joint-attentional interaction and ostensive communication. However, recent quantitative studies questioned these hypotheses based on new findings that certain features of human eyes are not necessarily unique among great ape species. Accordingly, there is currently a heated debate over whether external eye features of humans are distinct from those of other apes and how such distinguishable features contribute to the visibility of eye-gaze direction. The present study leveraged updated image analysis techniques to test the uniqueness of human eye features in facial images of great apes. Although many eye features were similar between humans and other great apes, a key difference was that humans have uniformly white sclera which creates clear visibility of both the eye outline and iris—the two essential features contributing to the visibility of eye-gaze direction. We then tested the robustness of the visibility of these features against visual noise, such as shading and distancing, and found that both eye features remain detectable in the human eye, while eye outline becomes barely detectable in other species under these visually challenging conditions. Overall, we identified that humans have unique external eye morphology among other great apes, which ensures the robustness of eye-gaze signals in various visual conditions. Our results support and also critically update the central premises of the gaze-signaling hypothesis.

A novel drowsiness detection model using composite features of head, eye, and facial expression

A novel drowsiness detection model using composite features of head, eye, and facial expression

Identification of tropical cyclones via deep convolutional neural network based on satellite cloud images

Abstract. Tropical cyclones (TCs) are one of the most destructive natural disasters. For the prevention and mitigation of TC-induced disasters, real-time monitoring and prediction of TCs is essential. At present, satellite cloud images (SCIs) are utilized widely as a basic data source for such studies. Although great achievements have been made in this field, there is a lack of concern about on the identification of TC fingerprints from SCIs, which is usually involved as a prerequisite step for follow-up analyses. This paper presents a methodology which identifies TC fingerprints via deep convolutional neural network (DCNN) techniques based on SCIs of more than 200 TCs over the northwestern Pacific basin. In total, two DCNN models have been proposed and validated, which are able to identify the TCs from not only single TC-featured SCIs but also multiple TC-featured SCIs. Results show that both models can reach 96 % of identification accuracy. As the TC intensity strengthens, the accuracy becomes better. To explore how these models work, heat maps are further extracted and analyzed. Results show that all the fingerprint features are focused on clouds during the testing process. For the majority of the TC images, the cloud features in TC's main parts, i.e., eye, eyewall, and primary rainbands, are most emphasized, reflecting a consistent pattern with the subjective method.

When it pays off to take a look: Infants learn to follow an object's motion with their gaze-Especially if it features eyes.

Social cues and instrumental learning are two aspects potentially fostering early gaze following. We systematically investigated the influence of social features (schematic eyes vs. reverse-contrast eyes) and gaze-contingent reinforcement (elicited vs. not elicited) on 4-month-olds' learning to attend to gaze-cued objects. In 4 experiments, we tested infants' (N=74) gaze following of a turning block with schematic or reverse-contrast eyes. In Experiments 1 and 2, infants could elicit an attractive animation in a training phase via interactive eye tracking by following the turning of the block. Experiments 3 and 4 were yoked controls without contingent reinforcement. Infants did not spontaneously follow the motion of the block. Four-month-olds always followed the block after training when it featured schematic eyes. When the block featured reverse-contrast eyes, the training phase only affected infants' looking behavior without reinforcement. While speaking to a certain degree of plasticity, findings stress the importance of eyes for guiding infants' attention.

Research on a Real-Time Driver Fatigue Detection Algorithm Based on Facial Video Sequences

The research on driver fatigue detection is of great significance to improve driving safety. This paper proposes a real-time comprehensive driver fatigue detection algorithm based on facial landmarks to improve the detection accuracy, which detects the driver’s fatigue status by using facial video sequences without equipping their bodies with other intelligent devices. A tasks-constrained deep convolutional network is constructed to detect the face region based on 68 key points, which can solve the optimization problem caused by the different convergence speeds of each task. According to the real-time facial video images, the eye feature of the eye aspect ratio (EAR), mouth aspect ratio (MAR) and percentage of eye closure time (PERCLOS) are calculated based on facial landmarks. A comprehensive driver fatigue assessment model is established to assess the fatigue status of drivers through eye/mouth feature selection. After a series of comparative experiments, the results show that this proposed algorithm achieves good performance in both accuracy and speed for driver fatigue detection.

Clinical and Multi-Mode Imaging Features of Eyes With Peripapillary Hyperreflective Ovoid Mass-Like Structures.

PurposeTo observe and analyze the clinical and multi-mode imaging features of eyes with PHOMS, and to introduce two cases of PHOMS which underwent multi-mode imaging.MethodsRetrospective clinical observational study. A total of 26 patients (37 eyes) with hyperreflective structures surrounded by hyporeflective edges around the optic discs who were examined and diagnosed at Shandong Eye Hospital between January 2019 and June 2021 were included in the study. Among these patients, 12 were male and 14 were female. Fifteen were monocular. The average age was 39 years. All patients underwent the following examinations: Best-corrected visual acuity (BCVA), intraocular pressure examinations, slit-lamp anterior segment examinations, indirect ophthalmoscopy, visual field examinations, fundus color photography, fundus autofluorescence (FAF), optical coherence tomography (OCT), and optical coherence tomography angiography (OCTA). Some of the patients were examined with fundus fluorescein angiography (FFA). Clinical data and imaging characteristics from the OCT, OCTA, and FFA were analyzed retrospectively.ResultsWe found the hyperreflective structures surrounded by hyporeflective edges around the optic discs in 37 eyes. EDI-OCT results revealed hyperreflective structures surrounded by hyporeflective edges around the optic discs in all eyes. Typical hyperreflexia lesions occurred around the optic disc, located subretinally and above Bruch's membrane. OCTA revealed that the highly reflective perioptic material also had vascular structures.ConclusionEDI-OCT of PHOMS showed hyperreflective structures surrounded by hyporeflective edges around all of the optic discs. Infra-red photography showed temporal hyperreflexia. These characteristics can be seen in a variety of diseases and may be a relatively common feature revealed by EDI-OCT scanning. These characteristics may also be seen in elderly patients as well as children. PHOMS may be found in optic disc drusen (ODD), tilted disc syndrome (TDS), optic neuritis, ischemic optic neuropathy, and in white dot syndromes. Few patients may be developed into macular neovascularization (MNV). In order to improve the accuracy and robustness of the conclusions and provide better clinical guidance, we need to conduct more comprehensive research in the subsequent clinical work.

Retinal microvasculature features in patients with Behcet\u2019s disease: a systematic review and meta-analysis

This meta-analysis aimed to analyze retinal microvasculature features in eyes with Behçet’s disease (BD) using optical coherence tomography angiography (OCTA). Electronic databases, including PubMed, Web of Science, Embase, and Cochrane Library, were comprehensively searched for published studies comparing retinal microvasculature characteristics between eyes with BD and controls. Continuous variables were calculated using the mean difference (MD) with 95% confidence interval (CI). Review Manager software (version 5.30) was used to conduct statistical analysis. A total of 13 eligible studies involving 599 eyes with BD and 622 control eyes were included in the meta-analysis. The pooled results showed that the macular whole enface superficial and deep vessel density (VD) values measured by OCTA were significantly lower in eyes with BD than in control eyes (superficial VD: MD = − 3.05, P < 0.00001; deep VD: MD = − 4.05, P = 0.0004). The foveal superficial and deep VD values were also significantly lower in the BD group than in the control group (superficial VD: MD = − 1.50, P = 0.009; deep VD: MD = − 4.25, − = 0.03). Similarly, the analysis revealed a significant reduction in the parafoveal superficial and deep VD in eyes with BD than in control eyes (superficial VD: MD = − 3.68, P < 0.00001; deep VD: MD = − 4.95, P = 0.0007). In addition, the superficial and deep foveal avascular zones (FAZs) were significantly larger in patients with BD than in controls (superficial FAZ: MD = 0.06, P = 0.02; deep FAZ: MD = 0.12, P = 0.03). The present meta-analysis found that macular whole enface VD, foveal VD, and parafoveal VD were lower in eyes with BD, and the FAZ was larger in patients with BD. The findings suggest that OCTA can assist clinicians in diagnosing and monitoring the status of patients with BD.

(Retracted) Estimation of human age by features of face and eyes based on multilevel feature convolutional neural network

Age estimation can be effectively used in security, human–computer interaction, entertainment, and audio-visual fields. However, current face-based age recognition algorithms are not highly accurate due to factors, such as face makeup and plastic surgery. Among the various feature points of a human face, the eyes are the most difficult part to be modified. And with the changes of age, the lens, cornea, and vitreous of eyes will also change accordingly. Therefore, we believe that paying attention to the local feature of the eye can improve the accuracy of age estimation to a certain extent. The multilevel feature convolutional neural network (MLFCNN) is proposed, which values eyes features and combines them with face features to jointly estimate human age. MLFCNN performs two rounds of estimation based on extracted features. First, the age range of the sample is estimated as the age group, and then on this basis, the fine age of the sample is further estimated. Field tests show that the mean absolute error of MLFCNN is 2.87, which is lower than other network models tested. When the MLFCNN estimated age did not differ more than 4 years from the actual age of the sample, the network predictions were considered correct (i.e., the tolerable age error was 4). The age estimation accuracy of MLFCNN under this condition was 91.14%. And 98.32% accuracy can be reached when the tolerable age error is 6. Ablation experiments verify that the fusion of ocular features and facial features can improve the performance of the age estimation network. In addition, it can still maintain a good performance under small training dataset.

Multimodal imaging in retinal artery macroaneurysms

AbstractPurposeTo describe multimodal imaging features in eyes with retinal artery macroaneurysms (RAM).MethodsA retrospective case series of 4 eyes diagnosed with RAM. All patients underwent a detailed ophthalmic examination, fundus photography, fluorescein angiography, swept source optical coherence tomography (SS‐OCT) and swept source optical coherence tomography angiography (SS‐OCTA).ResultsAll patients were females with a mean age of 57‐year‐old. There was a history of systemic hypertension in 3 patients. An acute vision loss was reported in 2 cases. The best corrected visual acuity at presentation ranged between +1.7 and +0.1 LogMar. RAM was single and unilateral in all cases. The RAM were seen in the temporal half of the retina in all cases and were localized in the superior temporal arcade in 2 cases and in the inferior temporal arcade in 2 cases. Fluorescein angiography allowed for the visualization of the RAM in 3 cases. SS‐OCT visualized the RAM in all cases and their consequences on the surrounding area and on the macula. SS‐OCTA allowed observation of blood flow in each layer of the RAM. En face OCT permitted delineation of the macroaneurysm wall in 2 cases.ConclusionsRetinal artery macroaneurysm is an acquired rare vascular disease that may mimic a variety of other conditions. Multimodal imaging approach is very useful for planning and assessing therapy.

Ocular Manifestations in Patients Diagnosed with Rosacea: A Cross-sectional Study from a Tertiary Care Centre in Northern India

Introduction: Rosacea is a chronic inflammatory disease that affects the facial skin with eye involvement being underdiagnosed. Aim: To study the prevalence of ocular rosacea in patients of rosacea in a tertiary care centre. Materials and Methods: The present study was a cross-sectional study conducted at two tertiary level hospitals from January 2020 to December 2021. Cases of rosacea diagnosed were referred from the Departments of dermatology to the Departments of ophthalmology for ocular evaluation. A total of 400 patients were included in study in a multicentric setting. For ophthalmic evaluation, Ocular Surface Disease Index (OSDI) questionnaire was used. Results: Total 29 cases (7.25%) had ocular rosacea, out of 400 dermatological confirmed cases of rosacea. Amongst confirmed ocular rosacea, 12 (41.4%) were males and 17 (58.6%) were females. Most manifestations were noted in 41 to 60 years age with an average age of 52.2 years. Most of the cases presented with multiple symptoms and signs- 19 presented with features of dry eyes,16 had features of conjunctivitis, 6 had blepharitis, and 7 had recurrent chalazions. Conclusion: Ocular rosacea is a diagnostic enigma to clinicians as it is underdiagnosed because of overlapping sign and symptoms. This study emphasises ocular examination in all cases of rosacea.

An Effective Foveated 360° Image Assessment Based on Graph Convolution Network

Virtual reality (VR) has been adopted in various fields such as entertainment, education, healthcare, and the military, due to its ability to provide an immersive experience to users. However, 360° images, one of the main components in VR systems, have bulky sizes and thus require effective transmitting and rendering solutions. One of the potential solutions is to use foveated technologies, that take advantage of the foveation feature of the human eyes. Foveated technologies can significantly reduce the data required for transmission and computation complexity in rendering. However, understanding the impact of foveated 360° images on human quality perception is still limited. This paper addresses the above problems by proposing an accurate machine-learning-based quality assessment model for foveated 360° images. The proposed model is proven to outperform the three cutting-edge machine-learning-based models, which apply deep learning techniques and 25 traditional-metric-based models (or analytical-function-based-models), which utilize analytical functions. It is also expected that our model helps to evaluate and improve 360° content streaming and rendering solutions to further reduce data sizes while ensuring user experience. Also, this model could be used as a building block to construct quality assessment methods for 360° videos, that are reserved for our future work. The source code is available at https://github.com/telagment/FoVGCN.

Fatigue detection based on facial feature correction and fusion

Fatigue driving has always been a major hidden danger that threatens traffic safety. The introduction of fatigue monitoring technology can greatly reduce traffic accidents caused by fatigue driving and produce huge social effects. At present, in the field of vision-based fatigue driving research, the extraction of the driver’s eye or mouth features is often used for judgment. However, the criterion is single and the post-processing is insufficient, and the interference of factors such as noise can easily cause misjudgement and reduce the recognition rate. In order to improve the accuracy of parameter extraction and solve the problem of low recognition rate of a single parameter, this paper proposes a feature extraction algorithm based on Euler angle correction, and adds a multi-feature fusion decision method to enhance the applicability of the algorithm. Experiments prove that the algorithm has higher accuracy after modification and fusion.

Gaze-Based Biometrics From Free Observation of Moving Elements

The recent COVID-19 outbreak has highlighted the importance of contactless authentication methods, such as those based on eye or gaze features. These techniques have the advantage that they can also be used by people wearing mouth and nose masks, which would make traditional face recognition approaches difficult to apply. Moreover, they can be used in addition to traditional authentication solutions, such as those based on passwords or PINs. In this work, we propose a study on gaze-based soft biometrics exploiting simple animations as visual stimuli. Specifically, we consider four animations in which small squares move according to different patterns and trajectories. No preliminary calibration of the eye tracking device is required. The collected data were analyzed using machine learning algorithms for both identification and verification tasks. The obtained results are particularly interesting in the verification case, that is the natural application of a soft biometric system, with accuracy scores always higher than 80% and Equal Error Rate (EER) values often lower than 10%.

Research on the Estimation of Gaze Location for Head-eye Coordination Movement

Abstract Sight is the main source for humans to obtain information from the outside world. Due to the structure of the human eye [1], the range of human sight is limited. For this reason, people need to constantly move their line of sight when observing the surrounding environment and the target, and the movement of the sight is based on the coordinated movement of the head and the eye[2]. Therefore, the key issue for gaze research is how to correctly establish the relationship between head-eye movement and gaze movement. Taking the simulated flight environment as the research background, this paper collects a large number of head-eye images through the designed “three-camera and eight-light source” head-eye data acquisition platform, and proposes a gaze estimation method based on the combination of appearance and features, which effectively combines The relationship of head-eye coordination movement. Then, the ResNet-18 deep residual network structure and the traditional BP neural network structure are used to complete the effective fusion of the head pose and human eye features in the process of capturing the sight target, so as to realize the accurate estimation of the sight drop point, and its average accuracy up to 89.9%.

A CNN-based Human Activity Recognition System Combining a Laser Feedback Interferometry Eye Movement Sensor and an IMU for Context-aware Smart Glasses

Smart glasses are considered the next breakthrough in wearables. As the successor of smart watches and smart ear wear, they promise to extend reality by immersive embedding of content in the user's field of view. While advancements in display technology seems to fulfill this promises, interaction concepts are derived from established wearable concepts like touch interaction or voice interaction, preventing full immersion as they require the user to frequently interact with the glasses. To minimize interactions, we propose to add context-awareness to smart glasses through human activity recognition (HAR) by combining head- and eye movement features to recognize a wide range of activities. To measure eye movements in unobtrusive way, we propose laser feedback interferometry (LFI) sensors. These tiny low power sensors are highly robust to ambient light. We combine LFI sensors and an IMU to collect eye and head movement features from 15 participants performing 7 cognitive and physical activities, leading to a unique data set. To recognize activities we propose a 1D-CNN model and apply transfer learning to personalize the classification, leading to an outstanding macro-F1 score of 88.15 % which outperforms state of the art methods. Finally, we discuss the applicability of the proposed system in a smart glasses setup.

Clinical Features of the Fellow Eyes of Children with Unilateral Facial Port-Wine Stains and Ipsilateral Glaucoma

Purpose: To investigate the clinical features of non-affected fellow eyes in patients with unilateral facial port-wine stain (PWS) and ipsilateral secondary glaucoma.Methods: We performed a retrospective analysis of the medical records of 35 patients with unilateral facial PWS glaucoma and those of controls (35 subjects without both facial PWS and glaucoma) between September 1996 and May 2020. We noted patients’ age at the glaucoma diagnosis (for unilateral facial PWS glaucoma patients) or at the initial examination (for controls), cup-to-disc ratio (CDR), and intraocular pressure (IOP). We compared the clinical features between the glaucoma-free eyes in patients with unilateral facial PWS glaucoma and the controls.Results: The mean age at the glaucoma diagnosis for unilateral facial PWS glaucoma patients was 0.56 ± 0.99 years (range, 0.08-4). The mean IOP of the glaucoma-free eyes was 16.68 ± 5.73 mmHg (range, 9-22.9), and the mean CDR was 0.37 ± 0.14 (range, 0.15-0.80) at glaucoma diagnosis. The mean IOP of the glaucoma-free eyes was 14.14 ± 6.29 mmHg (range, 8.1-26.7), and the mean CDR was 0.37 ± 0.12 (range, 0.26-0.82) at final examination. When comparing glaucoma-free eyes of the unilateral facial PWS glaucoma patients with the control group (mean age, 11.2 ± 7.4 years), the mean CDR was significantly greater (0.37 ± 0.12 vs. 0.30 ± 0.08; p = 0.014) but there was no significant difference in the mean IOP (14.14 ± 6.29 mmHg vs. 14.57 ± 2.49 mmHg; p = 0.712).Conclusions: The glaucoma-free eyes of unilateral facial PWS glaucoma patients showed greater CDR compared to the non-facial PWS and non-glaucoma controls. Additional longitudinal studies are needed to investigate the clinical course of those eyes, whether the risk of developing glaucoma is increased.

Correlation of Volume of Macular Edema with Retinal Tomography Features in Diabetic Retinopathy Eyes.

Optical coherence tomography (OCT) enables the detection of macular edema, a significant pathological outcome of diabetic retinopathy (DR). The aim of the study was to correlate edema volume with the severity of diabetic retinopathy and response to treatment with intravitreal injections (compared to baseline). Diabetic retinopathy (DR; n = 181) eyes were imaged with OCT (Heidelberg Engineering, Germany). They were grouped as responders (a decrease in thickness after intravitreal injection of Bevacizumab), non-responders (persistent edema or reduced decrease in thickness), recurrent (recurrence of edema after injection), and treatment naïve (no change in edema at follow-up without any injection). The post-treatment imaging of eyes was included for all groups, except for the treatment naïve group. All eyes underwent a 9 × 6 mm raster scan to measure the edema volume (EV). Central foveal thickness (CFT), central foveal volume (CFV), and total retinal volume (TRV) were obtained from the early treatment diabetic retinopathy study (ETDRS) map. The median EV increased with DR severity, with PDR having the greatest EV (4.01 mm3). This correlated positively with TRV (p < 0.001). Median CFV and CFT were the greatest in severe NPDR. Median EV was the greatest in the recurrent eyes (4.675 mm3) and lowest (1.6 mm3) in the treatment naïve group. Responders and non-responders groups had median values of 3.65 and 3.93 mm3, respectively. This trend was not observed with CFV, CFT, and TRV. A linear regression yielded threshold values of CFV (~0.3 mm3), CFT (~386 µm), and TRV (~9.06 mm3), above which EV may be detected by the current scanner. In this study, EV provided a better distinction between the response groups when compared to retinal tomography parameters. The EV increased with disease severity. Thus, EV can be a more precise parameter to identify subclinical edema and aid in better treatment planning.

Evaluation of ocular biometric parameters in keratoconic eyes relative to healthy myopic eyes.

To assess the biometric features of keratoconic eyes using the Lenstar LS900 and Pentacam systems relative to healthy myopic eyes. Seventy-three eyes of keratoconic subjects and 83 eyes of control subjects were enrolled. To evaluate the reproducibility of the Lenstar and Pentacam devices' measurements, keratometric readings [in flattest meridian (Kf), in steepest meridian (Ks), and mean (Km)], central corneal thickness (CCT), and anterior chamber depth (ACD) were obtained using both systems. Axial length and lens thickness (LT) were measured by the Lenstar. The compatibility between the two devices was investigated using the Bland-Altman statistical method. Axial length was longer in the myopic group than in eyes with keratoconus (24.94 ± 0.7 and 23.88 ± 0.96 mm, respectively, p < 0.001). LT and vitreous depth were also higher in the myopic group, although ACD values were similar. Compared to the Lenstar, the Pentacam measured the ACD and CCT values higher in the myopia group [with a difference of 0.07 ± 0.12 mm (p <0.001) and 4.47 ± 11.33 µm (p = 0.001), respectively] and measured the CCT values higher in the keratoconus group. Pentacam found all keratometry values significantly lower than Lenstar in the keratoconus group. Axial length was longer in the myopic eyes due to the differences starting from the lens and extending to the posterior segment. Lenstar and Pentacam can be used interchangeably for Km, Kf, and ACD in the myopic group and only for ACD in the keratoconus group.

A retrospective review of transcutaneous and transconjunctival dual approach—A technique for mini-invasive double eyelid blepharoplasty with blepharoptosis correction

Many Oriental eyes feature single eyelid fold and ptotic eyelid. Performing the double eyelid blepharoplasty (DEB) in a minimally invasive manner with simultaneous blepharoptosis correction (BPC) is important to achieve an aesthetic pleasing outcome. To demonstrate an effective mini-invasive transcutaneous and transconjunctival dual approach technique for simultaneous DEB and BPC. Furthermore, to compare the outcome of BPC in dual approach, transcutaneous procedure and transconjunctival procedure. This is a retrospective study reviewing 159 eyelids that underwent mini-invasive DEB with BPC from November 2018 to May 2019, including the technical description and the surgical outcomes. To investigate the efficacy, the pre- and postoperative margin reflex distance 1 (MRD1) and levator function (LF) corresponding to the different surgical procedures and preoperative severity was analyzed. Statistically, the dual approach group has significant improvement in MRD1 and LF (47 eyelids, p<0.05) corresponding to patients with ptosis of any severity. Under the same tucking amount, dual approach can achieve 1.6±0.7 mm of MRD1 improvement, which is nearly twice the amount compare with transconjunctival approach alone. No revision nor complication noted in the dual approach group by 6-month follow-up. The dual approach technique is a method with a wide range of applications, effective, and low revision rate that simultaneously correct blepharoptosis and create a double eyelid.

Evaluation of the Virtual Economic Effect of Tourism Product Emotional Marketing Based on Virtual Reality.

Rapid development of Internet technology has led to great changes in all fields of life. Tourism industry has also gone to the Internet with the change of the times. Regarding the application of Internet technology in tourism, in fact, virtual tourism products are directly used to promote economic development. Online tourism stores have all kinds of tourism information in the database, realize network roaming, provide convenient information services for both the supply and demand of tourism, and can realize the rapid and stable sustainable development of tourism. This article mainly studies the evaluation of the virtual economic effect of emotional marketing of tourism products based on virtual reality (VR), the meaning algorithm of VR, etc., analyzes the virtual economy of tourism products based on VR, and helps tourism enterprises to grasp the needs of tourism consumers more accurately, so as to design products and services that are more in line with the demands of tourism consumers, the process of ultimately improving the user value. This study mainly uses the VR method, VR platform eye map processing, VR eye map regional detection and feature extraction method, and VR tourism product emotional marketing related experiments, to study the evaluation of the virtual economic effect of tourism product emotional marketing based on VR. The economic performance information of the virtual tourism industry is equivalent to the amount of these indicators, and the impact of the comprehensive evaluation on the economic performance of virtual tourism is quite equal. The results show that from 2017 to 2020, the virtual economic revenue of VR tourism product emotional marketing increased from 50 million to 1 billion. However, people give more importance to the tourism experience brought by virtual tourism products, and the reasonable consumption structure of virtual tourism hinders the improvement of tourism economic benefits. To promote the rationalization of the consumption structure of virtual tourism, the basic industry of tourism consumption is developed and the necessary design and processing is increased, in order to increase the supply of tourism products and to enrich tourism consumption.