VHDL described finger tracking system for real-time human-machine interaction

Iturbe, Xabier; Altuna, Ander; Olano, Aitor; Martinez, Imanol

doi:10.1109/icses.2008.4673385

Cited by 5 publications

(1 citation statement)

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“…Probably the most germane of these is the work of Iturbe et al [18] which uses finger movement to control a virtual input system in which a user's finger is modeled as a straight line and its movement is used to determine the button being pointed to by the user. Unfortunately, their approach quickly fails for small mobile devices where the fingers need to bend in order to reach the keys.…”

Section: Related Workmentioning

confidence: 99%

Seeing double

Heinly

White

et al. 2013

Proceedings of the 2013 ACM SIGSAC Conference on Computer &Amp; Communications Security - CCS '13

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Of late, threats enabled by the ubiquitous use of mobile devices have drawn much interest from the research community. However, prior threats all suffer from a similar, and profound, weaknessnamely the requirement that the adversary is either within visual range of the victim (e.g., to ensure that the pop-out events in reflections in the victim's sunglasses can be discerned) or is close enough to the target to avoid the use of expensive telescopes. In this paper, we broaden the scope of the attacks by relaxing these requirements and show that breaches of privacy are possible even when the adversary is around a corner. The approach we take overcomes challenges posed by low image resolution by extending computer vision methods to operate on small, high-noise, images. Moreover, our work is applicable to all types of keyboards because of a novel application of fingertip motion analysis for key-press detection. In doing so, we are also able to exploit reflections in the eyeball of the user or even repeated reflections (i.e., a reflection of a reflection of the mobile device in the eyeball of the user). Our empirical results show that we can perform these attacks with high accuracy, and can do so in scenarios that aptly demonstrate the realism of this threat.

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Section: Related Workmentioning

confidence: 99%