International Journal of Human-Computer Studies - Special issue: Fitts law 50 years later: Applications and contributions from human-computer interaction
A probabilistic approach to modeling two-dimensional pointing
ACM Transactions on Computer-Human Interaction (TOCHI)
Camera phone based motion sensing: interaction techniques, applications and performance study
UIST '06 Proceedings of the 19th annual ACM symposium on User interface software and technology
Target acquisition with camera phones when used as magic lenses
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Pose tracking from natural features on mobile phones
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
Revisiting peephole pointing: a study of target acquisition with a handheld projector
MobileHCI '12 Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services
Playing it real: magic lens and static peephole interfaces for games in a public space
MobileHCI '12 Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services
Proceedings of the 20th ACM international conference on Multimedia
PaperTab: an electronic paper computer with multiple large flexible electrophoretic displays
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Mobile pointing task in the physical world: balancing focus and performance while disambiguating
Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services
Handheld Augmented Reality: Effect of registration jitter on cursor-based pointing techniques
Proceedings of the 25ième conférence francophone on l'Interaction Homme-Machine
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Rohs and Oulasvirta (2008) proposed a two-component Fitts' law model for target acquisition with magic lenses in mobile augmented reality (AR) with 1) a physical pointing phase, in which the target can be directly observed on the background surface, and 2) a virtual pointing phase, in which the target can only be observed through the device display. The model provides a good fit (R2=0.88) with laboratory data, but it is not known if it generalizes to real-world AR tasks. In the present outdoor study, subjects (N=12) did building-selection tasks in an urban area. The differences in task characteristics to the laboratory study are drastic: targets are three-dimensional and they vary in shape, size, z-distance, and visual context. Nevertheless, the model yielded an R2 of 0.80, and when using effective target width an R2 of 0.88 was achieved.