Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-13783
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dc.contributor.authorStrohm, Florian-
dc.contributor.authorBâce, Mihai-
dc.contributor.authorBulling, Andreas-
dc.date.accessioned2023-11-29T10:46:42Z-
dc.date.available2023-11-29T10:46:42Z-
dc.date.issued2023de
dc.identifier.isbn979-8-4007-0132-0-
dc.identifier.urihttp://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-138026de
dc.identifier.urihttp://elib.uni-stuttgart.de/handle/11682/13802-
dc.identifier.urihttp://dx.doi.org/10.18419/opus-13783-
dc.description.abstractWe introduce an end-to-end interactive system for mental face reconstruction - the challenging task of visually reconstructing a face image a person only has in their mind. In contrast to existing methods that suffer from low usability and high mental load, our approach only requires the user to rank images over multiple iterations according to the perceived similarity with their mental image. Based on these rankings, our mental face reconstruction system extracts image features in each iteration, combines them into a joint feature vector, and then uses a generative model to visually reconstruct the mental image. To avoid the need for collecting large amounts of human training data, we further propose a computational user model that can simulate human ranking behaviour using data from an online crowd-sourcing study (N=215). Results from a 12-participant user study show that our method can reconstruct mental images that are visually similar to existing approaches but has significantly higher usability, lower perceived workload, and is faster. In addition, results from a third 22-participant lineup study in which we validated our reconstructions on a face ranking task show a identification rate of , which is in line with prior work. These results represent an important step towards new interactive intelligent systems that can robustly and effortlessly reconstruct a user’s mental image.en
dc.language.isoende
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/801708de
dc.relation.uridoi:10.1145/3586183.3606795de
dc.rightsinfo:eu-repo/semantics/openAccessde
dc.subject.ddc004de
dc.titleUsable and fast interactive mental face reconstructionen
dc.typeconferenceObjectde
ubs.fakultaetInformatik, Elektrotechnik und Informationstechnikde
ubs.institutInstitut für Visualisierung und Interaktive Systemede
ubs.konferenznameACM Symposium on User Interface Software and Technology (36th, 2023, San Francisco, Calif.)de
ubs.publikation.noppnyesde
ubs.publikation.sourceUIST '23 : proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology. New York, NY : ACM, 2023. - ISBN 979-8-4007-0132-0, Article no. 99de
ubs.publikation.typKonferenzbeitragde
Appears in Collections:05 Fakultät Informatik, Elektrotechnik und Informationstechnik

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