The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
LensGesture: augmenting mobile interactions with back-of-device finger gestures
Abstract
We present LensGesture, a pure software approach for augmenting mobile interactions with back-of-device finger gestures. LensGesture detects full and partial occlusion as well as the dynamic swiping of fingers on the camera lens by analyzing image sequences captured by the built-in camera in real time. We report the feasibility and implementation of LensGesture as well as newly supported interactions. Through offline benchmarking and a 16-subject user study, we found that 1) LensGesture is easy to learn, intuitive to use, and can serve as an effective supplemental input channel for today's smartphones; 2) LensGesture can be detected reliably in real time; 3) LensGesture based target acquisition conforms to Fitts' Law and the information transmission rate is 0.53 bits/sec; and 4) LensGesture applications can improve the usability and the performance of existing mobile interfaces.
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Other novel techniques include lens gestures, multistroked gesture, ambiguous keyboard input, effect of key size, and five-key text-entry technique.
“Some other novel techniques include lens gestures [117], multistroked gesture [118], ambiguous keyboard input [119,120], effect of key size [115], and five-key text-entry technique [121].”
From Usability Studies on Mobile User Interface Design Patterns: A Systematic Literature Review (2017) · cites this paper as [117]
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Barrier pointing: using physical edges to assist target acquisition on mobile device touch screens
Froehlich, J., Wobbrock, J. O., & Kane, S. K. (2007) · Proceedings of the 9th international ACM SIGACCESS conference on Computers and accessibility · doi:10.1145/1296843.1296849 · Cited by 74
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Usability Studies on Mobile User Interface Design Patterns: A Systematic Literature Review
Punchoojit, L., & Hongwarittorrn, N. (2017) · Advances in Human-Computer Interaction · doi:10.1155/2017/6787504 · Cited by 235
Metadata
- Authors
- Xiao, X., Han, T., & Wang, J.
- Affiliations
- University of Pittsburgh (US)
- ORCID
- Venue
- Proceedings of the 15th ACM on International conference on multimodal interaction
- Publisher
- ACM
- Published
- 2013-12-09
- Pages
- 287-294
- OpenAlex
- W2040896124
- Cited by
- 52
- References
- 1
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 1 · 2022: 1 · 2021: 4 · 2020: 3 · 2019: 5 · 2018: 10 · 2017: 8 · 2016: 7 · 2015: 7 · 2014: 2
- FWCI
- 4.21
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION (publishedVersion)
- Funders
- Samsung
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Interactive and Immersive Displays
- Physical Sciences › Computer Science › Human-Computer Interaction › Hand Gesture Recognition Systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Keywords
- finger gestures, mobile interaction, occlusion detection, real-time gesture recognition, smartphone input, target acquisition, Fitts' law, information transfer rate
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