000130043 001__ 130043 000130043 005__ 20241125101149.0 000130043 0247_ $$2doi$$a10.1109/TVCG.2023.3247102 000130043 0248_ $$2sideral$$a133487 000130043 037__ $$aART-2023-133487 000130043 041__ $$aeng 000130043 100__ $$0(orcid)0000-0002-0073-6398$$aMartin, Daniel$$uUniversidad de Zaragoza 000130043 245__ $$aA study of change blindness in immersive environments 000130043 260__ $$c2023 000130043 5060_ $$aAccess copy available to the general public$$fUnrestricted 000130043 5203_ $$aHuman performance is poor at detecting certain changes in a scene, a phenomenon known as change blindness. Although the exact reasons of this effect are not yet completely understood, there is a consensus that it is due to our constrained attention and memory capacity: We create our own mental, structured representation of what surrounds us, but such representation is limited and imprecise. Previous efforts investigating this effect have focused on 2D images; however, there are significant differences regarding attention and memory between 2D images and the viewing conditions of daily life. In this work, we present a systematic study of change blindness using immersive 3D environments, which offer more natural viewing conditions closer to our daily visual experience. We devise two experiments; first, we focus on analyzing how different change properties (namely type, distance, complexity, and field of view) may affect change blindness. We then further explore its relation with the capacity of our visual working memory and conduct a second experiment analyzing the influence of the number of changes. Besides gaining a deeper understanding of the change blindness effect, our results may be leveraged in several VR applications such as redirected walking, games, or even studies on saliency or attention prediction. 000130043 536__ $$9info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEON$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 682080-CHAMELEON$$9info:eu-repo/grantAgreement/EC/H2020/956585/EU/Predictive Rendering In Manufacture and Engineering/PRIME$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 956585-PRIME$$9info:eu-repo/grantAgreement/ES/MICINN/PID2019-105004GB-I00 000130043 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/ 000130043 590__ $$a4.7$$b2023 000130043 592__ $$a2.056$$b2023 000130043 591__ $$aCOMPUTER SCIENCE, SOFTWARE ENGINEERING$$b14 / 132 = 0.106$$c2023$$dQ1$$eT1 000130043 593__ $$aComputer Graphics and Computer-Aided Design$$c2023$$dQ1 000130043 593__ $$aSoftware$$c2023$$dQ1 000130043 593__ $$aSignal Processing$$c2023$$dQ1 000130043 593__ $$aComputer Vision and Pattern Recognition$$c2023$$dQ1 000130043 594__ $$a10.4$$b2023 000130043 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000130043 700__ $$aSun, Xin 000130043 700__ $$0(orcid)0000-0002-7503-7022$$aGutierrez, Diego$$uUniversidad de Zaragoza 000130043 700__ $$0(orcid)0000-0003-0060-7278$$aMasia, Belen$$uUniversidad de Zaragoza 000130043 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf. 000130043 773__ $$g29, 5 (2023), 2446-2455$$pIEEE trans. vis. comput. graph.$$tIEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS$$x1077-2626 000130043 8564_ $$s16575699$$uhttps://zaguan.unizar.es/record/130043/files/texto_completo.pdf$$yPostprint 000130043 8564_ $$s3003737$$uhttps://zaguan.unizar.es/record/130043/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint 000130043 909CO $$ooai:zaguan.unizar.es:130043$$particulos$$pdriver 000130043 951__ $$a2024-11-22-12:06:04 000130043 980__ $$aARTICLE