The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
The generalized perceived input point model and how to double touch accuracy by extracting fingerprints
Abstract
It is generally assumed that touch input cannot be accurate because of the fat finger problem, i.e., the softness of the fingertip combined with the occlusion of the target by the finger. In this paper, we show that this is not the case. We base our argument on a new model of touch inaccuracy. Our model is not based on the fat finger problem, but on the perceived input point model. In its published form, this model states that touch screens report touch location at an offset from the intended target. We generalize this model so that it represents offsets for individual finger postures and users. We thereby switch from the traditional 2D model of touch to a model that considers touch a phenomenon in 3-space. We report a user study, in which the generalized model explained 67% of the touch inaccuracy that was previously attributed to the fat finger problem.
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Citations
Cites
SURF: Speeded Up Robust Features
Bay, H., Tuytelaars, T., & Van Gool, L. (2006) · Lecture Notes in Computer Science · doi:10.1007/11744023_32 · Cited by 14,955 · cited 1×
“RidgePad compares fingerprints using the generic image-matching algorithm SURF by Bay et al. [5].”
MethodShift: a technique for operating pen- based interfaces using touch
Vogel, D., & Baudisch, P. (2007) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240727 · Cited by 486
Self-citation
Cited by
Zhong, Y., Weber, A., Burkhardt, C., Weaver, P., & Bigham, J. P. (2015) · Proceedings of the 12th International Web for All Conference · doi:10.1145/2745555.2747277 · Cited by 42
Effects of Aging on Small Target Selection with Touch Input
Sultana, A., & Moffatt, K. (2019) · ACM Transactions on Accessible Computing · doi:10.1145/3300178 · Cited by 14
Li, Z., Zhao, M., Das, D., ZHAO, H., Ma, Y., Liu, W., Beaudouin-Lafon, M., Wang, F., Ramakrishnan, IV, & Bi, X. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517472 · Cited by 10
Modeling Gliding-based Target Selection for Blind Touchscreen Users
Ko, Y.-J., Putkonen, A., Aydin, A. S., Feiz, S., Wang, Y., Ashok, V., Ramakrishnan, IV, Oulasvirta, A., & Bi, X. (2021) · Proceedings of the 23rd International Conference on Mobile Human-Computer Interaction · doi:10.1145/3447526.3472022 · Cited by 3
Metadata
- Authors
- Holz, C., & Baudisch, P.
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2010-04-10
- Pages
- 581-590
- OpenAlex
- W2149344674
- Cited by
- 262
- References
- 2
- FWCI
- 20.83
- Type
- conference paper
- Language
- en
- Open access
- closed
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