Sensing techniques for mobile interaction
By K. Hinckley, Jeffrey S. Pierce, M. Sinclair, Eric Horvitz. ACM Symposium on User Interface Software and Technology, 2000
589 citations recorded by the source corpus.
We describe sensing techniques motivated by unique aspects of human-computer interaction with handheld devices in mobile settings. Special features of mobile interaction include changing orientation and position, changing venues, the use of computing as auxiliary to ongoing, real-world activities like talking to a colleague, and the general intimacy of use for such devices. We introduce and integrate a set of sensors into a handheld device, and demonstrate several new functionalities engendered by the sensors, such as recording memos when the device is held like a cell phone, switching between portrait and landscape display modes by holding the device in the desired orientation, automatically powering up the device when the user picks it up the device to start using it, and scrolling the display using tilt. We present an informal experiment, initial usability testing results, and user reactions to these techniques.
Subfields: Cognitive Neuroscience, Computer Vision and Pattern Recognition, Human-Computer Interaction
View Paper: https://www.semanticscholar.org/paper/1cfa915f1f86da52c92aff8d60cced0924b6a344
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Ka-Ping Yee
- K. Hinckley
- Anind K. Dey
- Eric Horvitz
- Michael S. Bernstein
- Ivan Poupyrev
- Chris Harrison
- Stephen Anthony Brewster
In Computer Vision and Pattern Recognition
- Anind K. Dey
- Eric Horvitz
- Gregory D. Abowd
- Shahram Izadi
- Johnson Apacible
- Ka-Ping Yee
- Luc Van Gool
- Jason I. Hong
In Human-Computer Interaction
- Ka-Ping Yee
- James A. Landay
- K. Hinckley
- Michael S. Bernstein
- Jason I. Hong
- Ivan Poupyrev
- Anind K. Dey
- Eric Horvitz
Citations in the corpus
- A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications (2001, background): “... or her vehicle's location on a map and possibly indicating nearby sites of interest (Abowd et al., 1997, Bederson, 1995, Davies et al., 1998, Feiner et al., 1997, Fels et al., 1998, McCarthy & Meidel, 1999, McCarthy & Anagost, 2000); presenting a choice of printers close to the user (Schilit, Ad”
- Models of attention in computing and communication (2003, methodology): “For example, sensing patterns of simple gestures such as the touching and lifting of a device in different settings can relay important information about attention that can be exploited in a number of exciting ways [7].”
- Reflective physical prototyping through integrated design, test, and analysis (2006, methodology): “To evaluate the expressiveness of d.tools’ visual language, we recreated prototypes for three existing devices — an Apple iPod Shuffle music player, the back panel of a Casio EX-Z40 digital camera, and Hinckley et al .’s Sensing PDA [19].”
- Peephole displays: pen interaction on spatially aware handheld computers (2003, methodology): “[9] have used tilt for scrolling through documents and lists.”
- Synchronous gestures for multiple persons and computers (2003, methodology): “In our architecture, a Context Server resides on each machine and handles all of the local sensor data [16], as well as all TCP/IP network communication with remote devices.”
- Ambient touch: designing tactile interfaces for handheld devices (2002, background): “There are many limitations and difficulties to overcome, well documented in interface literature [25, 29, 33, 36].”
- An Infrastructure Approach to Context-Aware Computing (2001, background): “For example, Hinckley, Pierce, Sinclair, and Horvitz (2000) modified a PDA to have tilt, touch, and proximity sensors.”
- SideSight: multi-"touch" interaction around small devices (2008, background): “Hinckley demonstrates the use of a single proximity sensor mounted on the front of the device to support coarse interaction [2].”
- Learning and reasoning about interruption (2003, background): “Beyond exploring new system events, appointment information, and enriched acoustical and visual features, we are investigating the discriminatory power of other sensors such as accelerometers, proximity, and motion detectors [4].”