@phdthesis{Holz2013,
  author    = {Holz, Christian},
  title     = {3D from 2D touch},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-67796},
  school      = {Universit{\"a}t Potsdam},
  year      = {2013},
  abstract  = {While interaction with computers used to be dominated by mice and keyboards, new types of sensors now allow users to interact through touch, speech, or using their whole body in 3D space. These new interaction modalities are often referred to as "natural user interfaces" or "NUIs." While 2D NUIs have experienced major success on billions of mobile touch devices sold, 3D NUI systems have so far been unable to deliver a mobile form factor, mainly due to their use of cameras. The fact that cameras require a certain distance from the capture volume has prevented 3D NUI systems from reaching the flat form factor mobile users expect. In this dissertation, we address this issue by sensing 3D input using flat 2D sensors. The systems we present observe the input from 3D objects as 2D imprints upon physical contact. By sampling these imprints at very high resolutions, we obtain the objects' textures. In some cases, a texture uniquely identifies a biometric feature, such as the user's fingerprint. In other cases, an imprint stems from the user's clothing, such as when walking on multitouch floors. By analyzing from which part of the 3D object the 2D imprint results, we reconstruct the object's pose in 3D space. While our main contribution is a general approach to sensing 3D input on 2D sensors upon physical contact, we also demonstrate three applications of our approach. (1) We present high-accuracy touch devices that allow users to reliably touch targets that are a third of the size of those on current touch devices. We show that different users and 3D finger poses systematically affect touch sensing, which current devices perceive as random input noise. We introduce a model for touch that compensates for this systematic effect by deriving the 3D finger pose and the user's identity from each touch imprint. We then investigate this systematic effect in detail and explore how users conceptually touch targets. Our findings indicate that users aim by aligning visual features of their fingers with the target. We present a visual model for touch input that eliminates virtually all systematic effects on touch accuracy. (2) From each touch, we identify users biometrically by analyzing their fingerprints. Our prototype Fiberio integrates fingerprint scanning and a display into the same flat surface, solving a long-standing problem in human-computer interaction: secure authentication on touchscreens. Sensing 3D input and authenticating users upon touch allows Fiberio to implement a variety of applications that traditionally require the bulky setups of current 3D NUI systems. (3) To demonstrate the versatility of 3D reconstruction on larger touch surfaces, we present a high-resolution pressure-sensitive floor that resolves the texture of objects upon touch. Using the same principles as before, our system GravitySpace analyzes all imprints and identifies users based on their shoe soles, detects furniture, and enables accurate touch input using feet. By classifying all imprints, GravitySpace detects the users' body parts that are in contact with the floor and then reconstructs their 3D body poses using inverse kinematics. GravitySpace thus enables a range of applications for future 3D NUI systems based on a flat sensor, such as smart rooms in future homes. We conclude this dissertation by projecting into the future of mobile devices. Focusing on the mobility aspect of our work, we explore how NUI devices may one day augment users directly in the form of implanted devices.},
  language  = {en}
}
@phdthesis{Gustafson2013,
  author    = {Gustafson, Sean},
  title     = {Imaginary Interfaces},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-68960},
  school      = {Universit{\"a}t Potsdam},
  year      = {2013},
  abstract  = {The size of a mobile device is primarily determined by the size of the touchscreen. As such, researchers have found that the way to achieve ultimate mobility is to abandon the screen altogether. These wearable devices are operated using hand gestures, voice commands or a small number of physical buttons. By abandoning the screen these devices also abandon the currently dominant spatial interaction style (such as tapping on buttons), because, seemingly, there is nothing to tap on. Unfortunately this design prevents users from transferring their learned interaction knowledge gained from traditional touchscreen-based devices. In this dissertation, I present Imaginary Interfaces, which return spatial interaction to screenless mobile devices. With these interfaces, users point and draw in the empty space in front of them or on the palm of their hands. While they cannot see the results of their interaction, they obtain some visual and tactile feedback by watching and feeling their hands interact. After introducing the concept of Imaginary Interfaces, I present two hardware prototypes that showcase two different forms of interaction with an imaginary interface, each with its own advantages: mid-air imaginary interfaces can be large and expressive, while palm-based imaginary interfaces offer an abundance of tactile features that encourage learning. Given that imaginary interfaces offer no visual output, one of the key challenges is to enable users to discover the interface's layout. This dissertation offers three main solutions: offline learning with coordinates, browsing with audio feedback and learning by transfer. The latter I demonstrate with the Imaginary Phone, a palm-based imaginary interface that mimics the layout of a physical mobile phone that users are already familiar with. Although these designs enable interaction with Imaginary Interfaces, they tell us little about why this interaction is possible. In the final part of this dissertation, I present an exploration into which human perceptual abilities are used when interacting with a palm-based imaginary interface and how much each accounts for performance with the interface. These findings deepen our understanding of Imaginary Interfaces and suggest that palm-based Imaginary Interfaces can enable stand-alone eyes-free use for many applications, including interfaces for visually impaired users.},
  language  = {en}
}