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dc.contributor.authorFeick, Martin
dc.contributor.authorTang, Xuxin
dc.contributor.authorGarcia-Martin, Raul
dc.contributor.authorLuchianov, Alexandru
dc.contributor.authorHuang, Roderick
dc.contributor.authorXiao, Chang
dc.contributor.authorSiu, Alexa
dc.contributor.authorDogan, Mustafa Doga
dc.date.accessioned2025-08-29T19:57:39Z
dc.date.available2025-08-29T19:57:39Z
dc.date.issued2025-04-25
dc.identifier.isbn979-8-4007-1394-1
dc.identifier.urihttps://hdl.handle.net/1721.1/162594
dc.descriptionCHI ’25, Yokohama, Japanen_US
dc.description.abstractHybrid paper interfaces leverage augmented reality to combine the desired tangibility of paper documents with the affordances of interactive digital media. Typically, virtual content can be embedded through direct links (e.g., QR codes); however, this impacts the aesthetics of the paper print and limits the available visual content space. To address this problem, we present Imprinto, an infrared inkjet watermarking technique that allows for invisible content embeddings only by using off-the-shelf IR inks and a camera. Imprinto was established through a psychophysical experiment, studying how much IR ink can be used while remaining invisible to users regardless of background color. We demonstrate that we can detect invisible IR content through our machine learning pipeline, and we developed an authoring tool that optimizes the amount of IR ink on the color regions of an input document for machine and human detectability. Finally, we demonstrate several applications, including augmenting paper documents and objects.en_US
dc.publisherACM|CHI Conference on Human Factors in Computing Systemsen_US
dc.relation.isversionofhttps://doi.org/10.1145/3706598.3713286en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAssociation for Computing Machineryen_US
dc.titleImprinto: Enhancing Infrared Inkjet Watermarking for Human and Machine Perceptionen_US
dc.typeArticleen_US
dc.identifier.citationMartin Feick, Xuxin Tang, Raul Garcia-Martin, Alexandru Luchianov, Roderick Wei Xiao Huang, Chang Xiao, Alexa Siu, and Mustafa Doga Dogan. 2025. Imprinto: Enhancing Infrared Inkjet Watermarking for Human and Machine Perception. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI '25). Association for Computing Machinery, New York, NY, USA, Article 447, 1–18.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.identifier.mitlicensePUBLISHER_POLICY
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2025-08-01T08:05:38Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2025-08-01T08:05:39Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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