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finger

fat finger

In Proceedings of UIST 2009
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Ripples: utilizing per-contact visualizations to improve user interaction with touch displays (p. 3-12)

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We present Ripples, a system which enables visualizations around each contact point on a touch display and, through these visualizations, provides feedback to the user about successes and errors of their touch interactions. Our visualization system is engineered to be overlaid on top of existing applications without requiring the applications to be modified in any way, and functions independently of the application's responses to user input. Ripples reduces the fundamental problem of ambiguity of feedback when an action results in an unexpected behaviour. This ambiguity can be caused by a wide variety of sources. We describe the ambiguity problem, and identify those sources. We then define a set of visual states and transitions needed to resolve this ambiguity, of use to anyone designing touch applications or systems. We then present the Ripples implementation of visualizations for those states, and the results of a user study demonstrating user preference for the system, and demonstrating its utility in reducing errors.

finger input

In Proceedings of UIST 2008
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Scratch input: creating large, inexpensive, unpowered and mobile finger input surfaces (p. 205-208)

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We present Scratch Input, an acoustic-based input technique that relies on the unique sound produced when a fingernail is dragged over the surface of a textured material, such as wood, fabric, or wall paint. We employ a simple sensor that can be easily coupled with existing surfaces, such as walls and tables, turning them into large, unpowered and ad hoc finger input surfaces. Our sensor is sufficiently small that it could be incorporated into a mobile device, allowing any suitable surface on which it rests to be appropriated as a gestural input surface. Several example applications were developed to demonstrate possible interactions. We conclude with a study that shows users can perform six Scratch Input gestures at about 90% accuracy with less than five minutes of training and on wide variety of surfaces.

In Proceedings of UIST 2009
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Abracadabra: wireless, high-precision, and unpowered finger input for very small mobile devices (p. 121-124)

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We present Abracadabra, a magnetically driven input technique that offers users wireless, unpowered, high fidelity finger input for mobile devices with very small screens. By extending the input area to many times the size of the device's screen, our approach is able to offer a high C-D gain, enabling fine motor control. Additionally, screen occlusion can be reduced by moving interaction off of the display and into unused space around the device. We discuss several example applications as a proof of concept. Finally, results from our user study indicate radial targets as small as 16 degrees can achieve greater than 92% selection accuracy, outperforming comparable radial, touch-based finger input.

finger orientation

In Proceedings of UIST 2009
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Detecting and leveraging finger orientation for interaction with direct-touch surfaces (p. 23-32)

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Current interactions on direct-touch interactive surfaces are often modeled based on properties of the input channel that are common in traditional graphical user interfaces (GUI) such as x-y coordinate information. Leveraging additional information available on the surfaces could potentially result in richer and novel interactions. In this paper we specifically explore the role of finger orientation. This property is typically ignored in touch-based interactions partly because of the ambiguity in determining it solely from the contact shape. We present a simple algorithm that unambiguously detects the directed finger orientation vector in real-time from contact information only, by considering the dynamics of the finger landing process. Results of an experimental evaluation show that our algorithm is stable and accurate. We then demonstrate how finger orientation can be leveraged to enable novel interactions and to infer higher-level information such as hand occlusion or user position. We present a set of orientation-aware interaction techniques and widgets for direct-touch surfaces.

finger tracking with computer vision

In Proceedings of UIST 2004
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Visual tracking of bare fingers for interactive surfaces (p. 119-122)