78274 20200113145614.0 doi 10.1109/TVCG.2018.2793599 sideral 105423 ART-2018-105423 eng Sitzmann, V. Saliency in VR: How do people explore virtual environments? 2018 Access copy available to the general public Unrestricted Understanding how people explore immersive virtual environments is crucial for many applications, such as designing virtual reality (VR) content, developing new compression algorithms, or learning computational models of saliency or visual attention. Whereas a body of recent work has focused on modeling saliency in desktop viewing conditions, VR is very different from these conditions in that viewing behavior is governed by stereoscopic vision and by the complex interaction of head orientation, gaze, and other kinematic constraints. To further our understanding of viewing behavior and saliency in VR, we capture and analyze gaze and head orientation data of 169 users exploring stereoscopic, static omni-directional panoramas, for a total of 1980 head and gaze trajectories for three different viewing conditions. We provide a thorough analysis of our data, which leads to several important insights, such as the existence of a particular fixation bias, which we then use to adapt existing saliency predictors to immersive VR conditions. In addition, we explore other applications of our data and analysis, including automatic alignment of VR video cuts, panorama thumbnails, panorama video synopsis, and saliency-basedcompression. info:eu-repo/grantAgreement/ES/MINECO/TIN2016-78753-P This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 682080-CHAMELEON info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEON info:eu-repo/grantAgreement/ES/MINECO/TIN2016-79710-P info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 3.78 2018 COMPUTER SCIENCE, SOFTWARE ENGINEERING 11 / 107 = 0.103 2018 Q1 T1 0.957 2018 Computer Graphics and Computer-Aided Design 2018 Q1 Software 2018 Q1 Signal Processing 2018 Q1 Computer Vision and Pattern Recognition 2018 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion (orcid)0000-0002-7796-3177 Serrano, A. Universidad de Zaragoza Pavel, A. Agrawala, M. (orcid)0000-0002-7503-7022 Gutierrez, D. Universidad de Zaragoza (orcid)0000-0003-0060-7278 Masia, B. Universidad de Zaragoza Wetzstein, G. 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 24, 4 (2018), 1633-1642 IEEE trans. vis. comput. graph. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 1077-2626 8367324 http://zaguan.unizar.es/record/78274/files/texto_completo.pdf Postprint 120151 http://zaguan.unizar.es/record/78274/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:78274 articulos driver 2020-01-13-14:52:37 ARTICLE