Mengya Yin , Xilin Zhou , Qunfeng Ji , Huairen Peng , Shize Yang , Chuancheng Li
{"title":"基于图像分析的地铁车站标识视觉显著性影响因素研究","authors":"Mengya Yin , Xilin Zhou , Qunfeng Ji , Huairen Peng , Shize Yang , Chuancheng Li","doi":"10.1016/j.cogsys.2025.101362","DOIUrl":null,"url":null,"abstract":"<div><div>Many studies have been conducted on the effects of color, light, and signage location on the visual saliency of underground signage. However, few studies have investigated the influence of indoor visual environments on the saliency of pedestrian signage. To explore the factors that influence the visual saliency of signage in metro stations, we developed a novel analysis method using a combination of saliency and focus maps. Then, questionnaires were utilized to unify the various formats of results from the saliency and focus maps. The factors that influence the visual saliency of signage were explored using the proposed method at selected sites and validated through virtual reality experiments. Additionally, this study proposes an image-analysis-based method that reveals the multilevel factors affecting pedestrian attention to signage in underground metro stations, including spatial interfaces, crowd flow, and ambient light. The results indicate that crowd flow has the greatest impact on pedestrian attention to signage. The study’s findings underscore the significance of considering pedestrian dynamics in the design of railway stations, which is crucial for delivering a high-quality subway experience.</div></div>","PeriodicalId":55242,"journal":{"name":"Cognitive Systems Research","volume":"92 ","pages":"Article 101362"},"PeriodicalIF":2.1000,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image-analysis-based method for exploring factors influencing the visual saliency of signage in metro stations\",\"authors\":\"Mengya Yin , Xilin Zhou , Qunfeng Ji , Huairen Peng , Shize Yang , Chuancheng Li\",\"doi\":\"10.1016/j.cogsys.2025.101362\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Many studies have been conducted on the effects of color, light, and signage location on the visual saliency of underground signage. However, few studies have investigated the influence of indoor visual environments on the saliency of pedestrian signage. To explore the factors that influence the visual saliency of signage in metro stations, we developed a novel analysis method using a combination of saliency and focus maps. Then, questionnaires were utilized to unify the various formats of results from the saliency and focus maps. The factors that influence the visual saliency of signage were explored using the proposed method at selected sites and validated through virtual reality experiments. Additionally, this study proposes an image-analysis-based method that reveals the multilevel factors affecting pedestrian attention to signage in underground metro stations, including spatial interfaces, crowd flow, and ambient light. The results indicate that crowd flow has the greatest impact on pedestrian attention to signage. The study’s findings underscore the significance of considering pedestrian dynamics in the design of railway stations, which is crucial for delivering a high-quality subway experience.</div></div>\",\"PeriodicalId\":55242,\"journal\":{\"name\":\"Cognitive Systems Research\",\"volume\":\"92 \",\"pages\":\"Article 101362\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Systems Research\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1389041725000427\",\"RegionNum\":3,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Systems Research","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1389041725000427","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Image-analysis-based method for exploring factors influencing the visual saliency of signage in metro stations
Many studies have been conducted on the effects of color, light, and signage location on the visual saliency of underground signage. However, few studies have investigated the influence of indoor visual environments on the saliency of pedestrian signage. To explore the factors that influence the visual saliency of signage in metro stations, we developed a novel analysis method using a combination of saliency and focus maps. Then, questionnaires were utilized to unify the various formats of results from the saliency and focus maps. The factors that influence the visual saliency of signage were explored using the proposed method at selected sites and validated through virtual reality experiments. Additionally, this study proposes an image-analysis-based method that reveals the multilevel factors affecting pedestrian attention to signage in underground metro stations, including spatial interfaces, crowd flow, and ambient light. The results indicate that crowd flow has the greatest impact on pedestrian attention to signage. The study’s findings underscore the significance of considering pedestrian dynamics in the design of railway stations, which is crucial for delivering a high-quality subway experience.
期刊介绍:
Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial.
The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition.
Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.