Show simple item record

dc.contributor.authorYang, Kailun
dc.contributor.authorHu, Xinxin
dc.contributor.authorBergasa Pascual, Luis Miguel 
dc.contributor.authorRomera Carmena, Eduardo 
dc.contributor.authorHuang, Xiao
dc.contributor.authorSun, Dongming
dc.contributor.authorWang, Kaiwei
dc.identifier.bibliographicCitationYang, K., Hu, X., Bergasa, L.M., Romera, E., Huang, X., Sun, D. & Wang K. 2019, "Can we PASS beyond the Field of View? Panoramic Annular Semantic Segmentation for real-world surrounding perception", in 2019 IEEE Intelligent Vehicles Symposium (IV), Paris, France, 9-12 June 2019, pp. 446-453.
dc.description2019 IEEE Intelligent Vehicles Symposium (IV), Paris, France, 9-12 June 2019en
dc.description.abstractPixel-wise semantic segmentation unifies distinct scene perception tasks in a coherent way, and has catalyzed notable progress in autonomous and assisted navigation, where a whole surrounding perception is vital. However, current mainstream semantic segmenters are normally benchmarked against datasets with narrow Field of View (FoV), and most visionbased navigation systems use only a forward-view camera. In this paper, we propose a Panoramic Annular Semantic Segmentation (PASS) framework to perceive the entire surrounding based on a compact panoramic annular lens system and an online panorama unfolding process. To facilitate the training of PASS models, we leverage conventional FoV imaging datasets, bypassing the effort entailed to create dense panoramic annotations. To consistently exploit the rich contextual cues in the unfolded panorama, we adapt our real-time ERF-PSPNet to predict semantically meaningful feature maps in different segments and fuse them to fulfill smooth and seamless panoramic scene parsing. Beyond the enlarged FoV, we extend focal length-related and style transfer-based data augmentations, to robustify the semantic segmenter against distortions and blurs in panoramic imagery. A comprehensive variety of experiments demonstrates the qualified robustness of our proposal for realworld surrounding understanding.en
dc.description.sponsorshipMinisterio de Economía y Competitividades_ES
dc.description.sponsorshipComunidad de Madrides_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights© 2019 IEEE
dc.titleCan we PASS beyond the Field of View? Panoramic Annular Semantic Segmentation for real-world surrounding perceptionen
dc.contributor.affiliationUniversidad de Alcalá. Departamento de Electrónicaes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//TRA2015-70501-C2-1-R/ES/VEHICULO INTELIGENTE PARA PERSONAS MAYORES/en
dc.relation.projectIDinfo:eu-repo/grantAgreement/CAM//P2018%2FNMT-4331/ES/Madrid Robotics Digital Innovation Hub/RoboCity2030-DIH-CMen
dc.identifier.publicationtitle2019 IEEE Intelligent Vehicles Symposium (IV)

Files in this item


This item appears in the following Collection(s)

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Este ítem está sujeto a una licencia Creative Commons.