{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1390588744671490048.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.2197/ipsjjip.34.75"}},{"identifier":{"@type":"URI","@value":"https://www.jstage.jst.go.jp/article/ipsjjip/34/0/34_75/_pdf"}}],"dc:title":[{"@language":"en","@value":"Mobile-AeroText: Air Writing Recognition of Japanese Hiragana for Practical Touchless Text Input"}],"dc:language":"en","description":[{"type":"abstract","notation":[{"@language":"en","@value":"<p>This study proposes an air-handwriting recognition technique that enables seamless, touchless text input in environments such as public displays, in-vehicle systems, and AR glasses. By leveraging intuitive handwriting, the approach expands the design space for human-computer interaction in contexts where physical keyboards or touchscreens are impractical. It offers potential privacy advantages by eliminating the need for voice or touch input, and promotes inclusivity by supporting arbitrary vocabulary without relying on predefined lexicons or prior training. The proposed system, Mobile-AeroText, employs a single-stage object detection network based on GELAN. It transforms fingertip trajectories into binary images while simultaneously detecting and recognizing character regions, enabling robust word-level recognition without explicit boundary gestures. In an evaluation with 25 participants and 1, 600 words, Mobile-AeroText achieved a word recognition rate of 91.44%, a character recognition rate of 95.86%, and an average latency of 417 milliseconds on a CPU. Subjective assessments yielded a System Usability Scale score of 78.5 and a NASA-TLX score of 33.6, indicating high usability and low cognitive load. Overall, this study presents a practical “write-anywhere” input method that addresses a fundamental challenge in human-computer interaction: enabling expressive, accessible, and low-burden text input in scenarios where traditional methods are unavailable or limited.</p>"}],"abstractLicenseFlag":"disallow"}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1410588744671490049","@type":"Researcher","foaf:name":[{"@language":"en","@value":"Nakamura Yudai"}],"jpcoar:affiliationName":[{"@language":"en","@value":"Faculty of Science and Technology, Keio University"}]},{"@id":"https://cir.nii.ac.jp/crid/1410588744671490048","@type":"Researcher","foaf:name":[{"@language":"en","@value":"Miwa Hiroyoshi"}],"jpcoar:affiliationName":[{"@language":"en","@value":"School of Engineering, Kwansei Gakuin University"}]}],"publication":{"publicationIdentifier":[{"@type":"EISSN","@value":"18826652"}],"prism:publicationName":[{"@language":"en","@value":"Journal of Information Processing"},{"@language":"en","@value":"Journal of Information Processing"}],"dc:publisher":[{"@language":"en","@value":"Information Processing Society of Japan"},{"@language":"ja","@value":"一般社団法人 情報処理学会"}],"prism:publicationDate":"2026","prism:volume":"34","prism:number":"0","prism:startingPage":"75","prism:endingPage":"83"},"reviewed":"false","url":[{"@id":"https://www.jstage.jst.go.jp/article/ipsjjip/34/0/34_75/_pdf"}],"availableAt":"2026","foaf:topic":[{"@id":"https://cir.nii.ac.jp/all?q=air%20handwriting%20recognition","dc:title":"air handwriting recognition"},{"@id":"https://cir.nii.ac.jp/all?q=deep%20learning","dc:title":"deep learning"},{"@id":"https://cir.nii.ac.jp/all?q=human-computer%20interaction","dc:title":"human-computer interaction"}],"relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1360023717931051392","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information"}]},{"@id":"https://cir.nii.ac.jp/crid/1360025437249147520","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Guided Image Synthesis via Initial Image Editing in Diffusion Model"}]},{"@id":"https://cir.nii.ac.jp/crid/1360302864793038464","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"An End-to-End Air Writing Recognition Method Based on Transformer"}]},{"@id":"https://cir.nii.ac.jp/crid/1360302871490221568","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Quantifying user research"}]},{"@id":"https://cir.nii.ac.jp/crid/1360307539069820288","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Text writing in the air"}]},{"@id":"https://cir.nii.ac.jp/crid/1360307542287468032","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Trajectory-Based Air-Writing Character Recognition Using Convolutional Neural Network"}]},{"@id":"https://cir.nii.ac.jp/crid/1360307542767869312","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Visual interface system by character handwriting gestures in the air"}]},{"@id":"https://cir.nii.ac.jp/crid/1360589013688648704","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Character Recognition in Air-Writing Based on Network of Radars for Human-Machine Interface"}]},{"@id":"https://cir.nii.ac.jp/crid/1360870489023474176","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"A New Writing Experience: Finger Writing in the Air Using a Kinect Sensor"}]},{"@id":"https://cir.nii.ac.jp/crid/1360870489828653440","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Finger in Camera Speaks Everything: Unconstrained Air-Writing for Real-World"}]},{"@id":"https://cir.nii.ac.jp/crid/1360870489973461248","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"3D Space Handwriting Recognition with Ligature Model"}]},{"@id":"https://cir.nii.ac.jp/crid/1363107369442861568","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@value":"Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research"}]},{"@id":"https://cir.nii.ac.jp/crid/1390282763118080256","@type":"Article","relationType":["references"],"jpcoar:relatedTitle":[{"@language":"en","@value":"Quantitative Analyses on Effects from Constraints in Air-Writing"}]}],"dataSourceIdentifier":[{"@type":"JALC","@value":"oai:japanlinkcenter.org:2015011415"},{"@type":"CROSSREF","@value":"10.2197/ipsjjip.34.75"}]}