Displays最新文献_第10页

Weighted ensemble deep learning approach for classification of gastrointestinal diseases in colonoscopy images aided by explainable AI 利用可解释人工智能辅助加权集合深度学习方法对结肠镜图像中的胃肠道疾病进行分类

IF 3.7 2区工程技术

Displays Pub Date : 2024-11-06 DOI: 10.1016/j.displa.2024.102874

Faruk Enes Oğuz , Ahmet Alkan

{"title":"Weighted ensemble deep learning approach for classification of gastrointestinal diseases in colonoscopy images aided by explainable AI","authors":"Faruk Enes Oğuz , Ahmet Alkan","doi":"10.1016/j.displa.2024.102874","DOIUrl":"10.1016/j.displa.2024.102874","url":null,"abstract":"<div><div>Gastrointestinal diseases are significant health issues worldwide, requiring early diagnosis due to their serious health implications. Therefore, detecting these diseases using artificial intelligence-based medical decision support systems through colonoscopy images plays a critical role in early diagnosis. In this study, a deep learning-based method is proposed for the classification of gastrointestinal diseases and colon anatomical landmarks using colonoscopy images. For this purpose, five different Convolutional Neural Network (CNN) models, namely Xception, ResNet-101, NASNet-Large, EfficientNet, and NASNet-Mobile, were trained. An ensemble model was created using class-based recall values derived from the validation performances of the top three models (Xception, ResNet-101, NASNet-Large). A user-friendly Graphical User Interface (GUI) was developed, allowing users to perform classification tasks and use Gradient-weighted Class Activation Mapping (Grad-CAM), an explainable AI tool, to visualize the regions from which the model derives information. Grad-CAM visualizations contribute to a better understanding of the model’s decision-making processes and play an important role in the application of explainable AI. In the study, eight labels, including anatomical markers such as z-line, pylorus, and cecum, as well as pathological findings like esophagitis, polyps, and ulcerative colitis, were classified using the KVASIR V2 dataset. The proposed ensemble model achieved a 94.125% accuracy on the KVASIR V2 dataset, demonstrating competitive performance compared to similar studies in the literature. Additionally, the precision and F1 score values of this model are equal to 94.168% and 94.125%, respectively. These results suggest that the proposed method provides an effective solution for the diagnosis of GI diseases and can be beneficial for medical education.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"85 ","pages":"Article 102874"},"PeriodicalIF":3.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Virtual reality in medical education: Effectiveness of Immersive Virtual Anatomy Laboratory (IVAL) compared to traditional learning approaches 医学教育中的虚拟现实技术：沉浸式虚拟解剖实验室（IVAL）与传统学习方法的效果比较

IF 3.7 2区工程技术

Displays Pub Date : 2024-11-06 DOI: 10.1016/j.displa.2024.102870

Mohammed Kadri , Fatima-Ezzahra Boubakri , Timothy Teo , Fatima-Zahra Kaghat , Ahmed Azough , Khalid Alaoui Zidani

{"title":"Virtual reality in medical education: Effectiveness of Immersive Virtual Anatomy Laboratory (IVAL) compared to traditional learning approaches","authors":"Mohammed Kadri , Fatima-Ezzahra Boubakri , Timothy Teo , Fatima-Zahra Kaghat , Ahmed Azough , Khalid Alaoui Zidani","doi":"10.1016/j.displa.2024.102870","DOIUrl":"10.1016/j.displa.2024.102870","url":null,"abstract":"<div><div>Immersive Virtual Anatomy Laboratory (IVAL) is an innovative learning tool that combines virtual reality and serious games elements to enhance anatomy education. This experimental study compares IVAL with traditional learning methods in terms of educational effectiveness and user acceptance. An experimental design was implemented with 120 undergraduate health-science students, randomly assigned to two groups: an experimental group using IVAL, and a control group following traditional learning methods. Data collection focused on quantitative measures such as pretest and posttest vocabulary assessment scores and task completion times, alongside qualitative measures obtained through a user experience questionnaire. This study utilizes the Technology Acceptance Model (TAM), incorporating variables such as Perceived Usefulness and Perceived Ease of Use. Results revealed significant improvements in the experimental group, with a 55.95% increase in vocabulary scores and an 18.75% reduction in task completion times compared to the control group. Qualitative data indicated that IVAL users reported greater Perceived Usefulness of the technology, improved Perceived Ease of Use, a more positive Attitude Towards Using IVAL, and stronger Behavioral Intention to continue using IVAL for anatomy learning. This study demonstrates that the integration of immersive virtual reality in the IVAL approach offers a promising method to enhance anatomy education. The findings provide insights into the effectiveness of immersive learning environments in improving learning outcomes and user acceptance. While further research is needed to explore long-term effects, this innovative approach not only enhances the effectiveness and enjoyment of anatomy learning but also provides valuable data on optimizing educational technology for improved learning outcomes.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"85 ","pages":"Article 102870"},"PeriodicalIF":3.7,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CIFTC-Net: Cross information fusion network with transformer and CNN for polyp segmentation CIFTC-Net：用于息肉分割的带有变压器和 CNN 的交叉信息融合网络

IF 3.7 2区工程技术

Displays Pub Date : 2024-11-02 DOI: 10.1016/j.displa.2024.102872

Xinyu Li , Qiaohong Liu , Xuewei Li , Tiansheng Huang , Min Lin , Xiaoxiang Han , Weikun Zhang , Keyan Chen , Yuanjie Lin

{"title":"CIFTC-Net: Cross information fusion network with transformer and CNN for polyp segmentation","authors":"Xinyu Li , Qiaohong Liu , Xuewei Li , Tiansheng Huang , Min Lin , Xiaoxiang Han , Weikun Zhang , Keyan Chen , Yuanjie Lin","doi":"10.1016/j.displa.2024.102872","DOIUrl":"10.1016/j.displa.2024.102872","url":null,"abstract":"<div><div>Polyp segmentation plays a crucial role in the early diagnosis and treatment of colorectal cancer, which is the third most common cancer worldwide. Despite remarkable successes achieved by recent deep learning-related works, accurate segmentation of polyps remains challenging due to the diversity in their shapes, sizes, appearances, and other factors. To address these problems, a novel cross information fusion network with Transformer and convolutional neural network (CNN) for polyp segmentation, named CIFTC-Net, is proposed to improve the segmentation performance of colon polyps. In particular, a dual-branch encoder with Pyramid Vision Transformer (PVT) and ResNet50 is employed to take full advantage of both the global semantic information and local spatial features to enhance the feature representation ability. To effectively fuse the two types of features, a new global–local feature fusion (GLFF) module is designed. Additionally, in the PVT branch, a multi-scale feature integration (MSFI) module is introduced to fuse multi-scale features adaptively. At the bottom of the model, a multi-scale atrous pyramid bridging (MSAPB) module is proposed to achieve rich and robust multi-level features and improve the segmentation accuracy. Experimental results on four public polyp segmentation datasets demonstrate that CIFTC-Net surpasses current state-of-the-art methods across various metrics, showcasing its superiority in segmentation accuracy, generalization ability, and handling of complex images.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"85 ","pages":"Article 102872"},"PeriodicalIF":3.7,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From hardware to software integration: A comparative study of usability and safety in vehicle interaction modes 从硬件到软件集成：车辆交互模式的可用性和安全性比较研究

IF 3.7 2区工程技术

Displays Pub Date : 2024-10-30 DOI: 10.1016/j.displa.2024.102869

Haibo Yin , Rui Li , Yingjie Victor Chen

{"title":"From hardware to software integration: A comparative study of usability and safety in vehicle interaction modes","authors":"Haibo Yin , Rui Li , Yingjie Victor Chen","doi":"10.1016/j.displa.2024.102869","DOIUrl":"10.1016/j.displa.2024.102869","url":null,"abstract":"<div><div>The increasing advancement of human–machine interaction (HMI) technology has brought the modes of vehicle HMI into focus, as they are closely related to driver and passenger safety and directly affect the travel experiences. This study compared the usability and safety of three vehicle HMI modes: hardware interaction (HI), hardware and software interaction (HSI), and software interaction (SI). The evaluation comprised two dimensions: usability and safety. Sixty participants’ performance on these tasks was evaluated at two driving speeds (30 km/h and 60 km/h). The results of the nonparametric tests indicated significant differences between the three interaction modes: (1) HI was the highest safety-oriented interaction mode with participants had the highest average vehicle speed and maximum acceleration measured at 60 km/h and the lowest glance frequency at both speeds; (2) HSI was the most usable interaction mode. Participants had the shortest task-completion time measured at 60 km/h and the highest score on the NASA-TLX and SUS scales taken for both speeds; (3) SI was the lowest secure and usable in-vehicle interaction mode. Participants had the longest task-completion time at 60 km/h, the highest error frequency under 30 and 60 km/h and the highest glance frequency, the longest total glance duration and the longest average glance time. In conclusion, HI and HSI were more secure and usable in-vehicle interaction modes than SI. From a theoretical exploration perspective, this paper elaborates on some exploratory thoughts and innovative ideas for practical application to the screen HMI mode selection and design in intelligent vehicle cabins.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"85 ","pages":"Article 102869"},"PeriodicalIF":3.7,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cross-coupled prompt learning for few-shot image recognition 交叉耦合提示学习用于少镜头图像识别

IF 3.7 2区工程技术

Displays Pub Date : 2024-10-30 DOI: 10.1016/j.displa.2024.102862

Fangyuan Zhang , Rukai Wei , Yanzhao Xie , Yangtao Wang , Xin Tan , Lizhuang Ma , Maobin Tang , Lisheng Fan

{"title":"Cross-coupled prompt learning for few-shot image recognition","authors":"Fangyuan Zhang , Rukai Wei , Yanzhao Xie , Yangtao Wang , Xin Tan , Lizhuang Ma , Maobin Tang , Lisheng Fan","doi":"10.1016/j.displa.2024.102862","DOIUrl":"10.1016/j.displa.2024.102862","url":null,"abstract":"<div><div>Prompt learning based on large models shows great potential to reduce training time and resource costs, which has been progressively applied to visual tasks such as image recognition. Nevertheless, the existing prompt learning schemes suffer from either inadequate prompt information from a single modality or insufficient prompt interaction between multiple modalities, resulting in low efficiency and performance. To address these limitations, we propose a <u>C</u>ross-<u>C</u>oupled <u>P</u>rompt <u>L</u>earning (CCPL) architecture, which is designed with two novel components (i.e., Cross-Coupled Prompt Generator (CCPG) module and Cross-Modal Fusion (CMF) module) to achieve efficient interaction between visual and textual prompts. Specifically, the CCPG module incorporates a cross-attention mechanism to automatically generate visual and textual prompts, each of which will be adaptively updated using the self-attention mechanism in their respective image and text encoders. Furthermore, the CMF module implements a deep fusion to reinforce the cross-modal feature interaction from the output layer with the Image–Text Matching (ITM) loss function. We conduct extensive experiments on 8 image datasets. The experimental results verify that our proposed CCPL outperforms the SOTA methods on few-shot image recognition tasks. The source code of this project is released at: <span><span>https://github.com/elegantTechie/CCPL</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"85 ","pages":"Article 102862"},"PeriodicalIF":3.7,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing arbitrary style transfer like an artist 像艺术家一样评估任意的风格转换

IF 3.7 2区工程技术

Displays Pub Date : 2024-10-28 DOI: 10.1016/j.displa.2024.102859

Hangwei Chen, Feng Shao, Baoyang Mu, Qiuping Jiang

{"title":"Assessing arbitrary style transfer like an artist","authors":"Hangwei Chen, Feng Shao, Baoyang Mu, Qiuping Jiang","doi":"10.1016/j.displa.2024.102859","DOIUrl":"10.1016/j.displa.2024.102859","url":null,"abstract":"<div><div>Arbitrary style transfer (AST) is a distinctive technique for transferring artistic style into content images, with the goal of generating stylized images that approximates real artistic paintings. Thus, it is natural to develop a quantitative evaluation metric to act like an artist for accurately assessing the quality of AST images. Inspired by this, we present an artist-like network (AL-Net) which can analyze the quality of the stylized images like an artist from the fine knowledge of artistic painting (e.g., aesthetics, structure, color, texture). Specifically, the AL-Net consists of three sub-networks: an aesthetic prediction network (AP-Net), a content preservation prediction network (CPP-Net), and a style resemblance prediction network (SRP-Net), which can be regarded as specialized feature extractors, leveraging professional artistic painting knowledge through pre-training by different labels. To more effectively predict the final overall quality, we apply transfer learning to integrate the pre-trained feature vectors representing different painting elements into overall vision quality regression. The loss determined by the overall vision label fine-tunes the parameters of AL-Net, and thus our model can establish a tight connection with human perception. Extensive experiments on the AST-IQAD dataset validate that the proposed method achieves the state-of-the-art performance.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"85 ","pages":"Article 102859"},"PeriodicalIF":3.7,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The role of image realism and expectation in illusory self-motion (vection) perception in younger and older adults 图像逼真度和期望值在年轻人和老年人的虚幻自我运动（向量）感知中的作用

IF 3.7 2区工程技术

Displays Pub Date : 2024-10-28 DOI: 10.1016/j.displa.2024.102868

Brandy Murovec , Julia Spaniol , Behrang Keshavarz

{"title":"The role of image realism and expectation in illusory self-motion (vection) perception in younger and older adults","authors":"Brandy Murovec , Julia Spaniol , Behrang Keshavarz","doi":"10.1016/j.displa.2024.102868","DOIUrl":"10.1016/j.displa.2024.102868","url":null,"abstract":"<div><div>Research on the illusion of self-motion (vection) has primarily focused on younger adults, with few studies including older adults. In light of documented age differences in bottom-up and top-down perception and attention, the current study examined the impact of stimulus properties (speed), cognitive factors (expectancy), and a combination of both (stimulus realism) on vection in younger (18–35 years) and older (65+ years) adults. Participants were led to believe through manipulation of the study instructions that they were either likely or unlikely to experience vection before they were exposed to a rotating visual stimulus aimed to induce circular vection. Realism was manipulated by disrupting the global consistency of the visual stimulus comprised of an intact 360° panoramic photograph, resulting in two images (intact, scrambled). The speed of the stimulus was varied (faster, slower). Vection was measured using self-ratings of onset latency, duration, and intensity. Results showed that intact images produced more vection than scrambled images, especially at faster speeds. In contrast, expectation did not significantly impact vection. Overall, these patterns were similar across both age groups, although younger adults reported earlier vection onsets than older adults at faster speeds. These findings suggest that vection results from an interplay of stimulus-driven and cognitive factors in both younger and older adults.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"85 ","pages":"Article 102868"},"PeriodicalIF":3.7,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DCMR: Degradation compensation and multi-dimensional reconstruction based pre-processing for video coding DCMR：基于降级补偿和多维重建的视频编码预处理

IF 3.7 2区工程技术

Displays Pub Date : 2024-10-24 DOI: 10.1016/j.displa.2024.102866

Mengfan Lv, Xiwu Shang, Jiajia Wang, Guoping Li, Guozhong Wang

{"title":"DCMR: Degradation compensation and multi-dimensional reconstruction based pre-processing for video coding","authors":"Mengfan Lv, Xiwu Shang, Jiajia Wang, Guoping Li, Guozhong Wang","doi":"10.1016/j.displa.2024.102866","DOIUrl":"10.1016/j.displa.2024.102866","url":null,"abstract":"<div><div>The rapid growth of video data poses a serious challenge to the limited bandwidth. Video coding pre-processing technology can remove coding noise without changing the architecture of the codec. Therefore, it can improve the coding efficiency while ensuring a high degree of compatibility with existing codec. However, the existing pre-processing methods have the problem of feature redundancy, and lack an effective mechanism to recover high-frequency details. In view of these problems, we propose a Degradation Compensation and Multi-dimensional Reconstruction (DCMR) pre-processing method for video coding to improve compression efficiency. Firstly, we develop a degradation compensation model, which aims at filtering the coding noise in the original video and relieving the frame quality degradation caused by transmission. Secondly, we construct a lightweight multi-dimensional feature reconstruction network, which combines residual learning and feature distillation. It aims to enhance and refine the key features related to coding from both spatial and channel dimensions while suppressing irrelevant features. In addition, we design a weighted guided image filter detail enhancement convolution module, which is specifically used to recover the high-frequency details lost in the denoising process. Finally, we introduce an adaptive discrete cosine transform loss to balance coding efficiency and quality. Experimental results demonstrate that compared with the original codec H.266/VVC, the proposed DCMR can achieve BD-rate (VMAF) and BD-rate (MOS) gains by 21.62% and 12.99% respectively on VVC, UVG, and MCL-JCV datasets.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"85 ","pages":"Article 102866"},"PeriodicalIF":3.7,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142551869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

BGFlow: Brightness-guided normalizing flow for low-light image enhancement BGFlow：用于弱光图像增强的亮度引导归一化流程

IF 3.7 2区工程技术

Displays Pub Date : 2024-10-23 DOI: 10.1016/j.displa.2024.102863

Jiale Chen, Qiusheng Lian, Baoshun Shi

{"title":"BGFlow: Brightness-guided normalizing flow for low-light image enhancement","authors":"Jiale Chen, Qiusheng Lian, Baoshun Shi","doi":"10.1016/j.displa.2024.102863","DOIUrl":"10.1016/j.displa.2024.102863","url":null,"abstract":"<div><div>Low-light image enhancement poses significant challenges due to its ill-posed nature. Recently, deep learning-based methods have attempted to establish a unified mapping relationship between normal-light images and their low-light versions but frequently struggle to capture the intricate variations in brightness conditions. As a result, these methods often suffer from overexposure, underexposure, amplified noise, and distorted colors. To tackle these issues, we propose a brightness-guided normalizing flow framework, dubbed BGFlow, for low-light image enhancement. Specifically, we recognize that low-frequency sub-bands in the wavelet domain carry significant brightness information. To effectively capture the intricate variations in brightness within an image, we design a transformer-based multi-scale wavelet-domain encoder to extract brightness information from the multi-scale features of the low-frequency sub-bands. The extracted brightness feature maps, at different scales, are then injected into the brightness-guided affine coupling layer to guide the training of the conditional normalizing flow module. Extensive experimental evaluations demonstrate the superiority of BGFlow over existing deep learning-based approaches in both qualitative and quantitative assessments. Moreover, we also showcase the exceptional performance of BGFlow on the underwater image enhancement task.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"85 ","pages":"Article 102863"},"PeriodicalIF":3.7,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142551870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic assessment of visual fatigue during video watching: Validation of dynamic rating based on post-task ratings and video features 视频观看过程中视觉疲劳的动态评估：基于任务后评级和视频特征的动态评级验证

IF 3.7 2区工程技术

Displays Pub Date : 2024-10-19 DOI: 10.1016/j.displa.2024.102861

Sanghyeon Kim, Uijong Ju

{"title":"Dynamic assessment of visual fatigue during video watching: Validation of dynamic rating based on post-task ratings and video features","authors":"Sanghyeon Kim, Uijong Ju","doi":"10.1016/j.displa.2024.102861","DOIUrl":"10.1016/j.displa.2024.102861","url":null,"abstract":"<div><div>People watching video displays for long durations experience visual fatigue and other symptoms associated with visual discomfort. Fatigue-reduction techniques are often applied but may potentially degrade the immersive experience. To appropriately adjust fatigue-reduction techniques, the changes in visual fatigue over time should be analyzed which is crucial for the appropriate adjustment of fatigue-reduction techniques. However, conventional methods used for assessing visual fatigue are inadequate because they rely entirely on post-task surveys, which cannot easily determine dynamic changes. This study employed a dynamic assessment method for evaluating visual fatigue in real-time. Using a joystick, participants continuously evaluated subjective fatigue whenever they perceived changes. A Simulator Sickness Questionnaire (SSQ) validated the results, which indicated significant correlations between dynamic assessments and the SSQ across five items associated with symptoms associated with visual discomfort. Furthermore, we explored the potential relationship between dynamic visual fatigue and objective video features, e.g., optical flow and the V-values of the hue/saturation value (HSV) color space, which represent the motion and brightness of the video. The results revealed that dynamic visual fatigue significantly correlated with both the optical flow and the V-value. Moreover, based on machine learning models, we determined that the changes in visual fatigue can be predicted based on the optical flow and V-value. Overall, the results validate that dynamic assessment methods can form a reliable baseline for real-time prediction of visual fatigue.</div></div>","PeriodicalId":50570,"journal":{"name":"Displays","volume":"85 ","pages":"Article 102861"},"PeriodicalIF":3.7,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0