Ph.D
Group : Human-Centered Computing

Increasing the expressive power of gesture-based interaction on mobile devices

Starts on 01/10/2014
Advisor : MACKAY, Wendy

Funding :
Affiliation : Université Paris-Saclay
Laboratory : LRI - HCC

Defended on 13/12/2017, committee :

Research activities :

Abstract :
Current mobile interfaces let users directly manipulate the objects displayed on the screen with simple stroke gestures, e.g. tap on soft buttons or menus or pinch to zoom. To access a larger command space, the users are often forced to go through long steps, making the interaction cumbersome and inefficient. More complex gestures offer a powerful way to access information quickly and to perform a command more efficiently [5]. However, they are more difficult to learn and control. Gesture typing [78] is an interesting alternative to input text: it lets users draw a gesture on soft keyboards to enter text, from the first until the final letter in a word. In this thesis, I increase the expressive power of mobile interaction by leveraging the gesture’s shape and dynamics and the screen space to produce rich output, to invoke commands, and to facilitate appropriation in different contexts of use. I design "Expressive Keyboard" that transforms the gesture variations into rich output, and demonstrate several applications in the context of textbased communication. As well, I propose "CommandBoard", a gesture keyboard that lets users efficiently select commands from a large command space while supporting the transition from novices to experts. I demonstrate different applications of "CommandBoard", each offers users a choice, based on their cognitive and motor skills, as well as the size and organization of the current command set. Altogether, these techniques give users more expressive power by leveraging human’s motor control and cognitive ability to learn, to control, and to appropriate.

CAUSAL LEARNING FOR DIAGNOSTIC SUPPORT


CAUSAL UNCERTAINTY QUANTIFICATION UNDER PARTIAL KNOWLEDGE AND LOW DATA REGIMES


MICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACES
The topic of this habilitation is the study of very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. For several years, together with my collaborators, I have been studying human perception, interaction, and analysis with micro visualizations in multiple contexts. In this document I bring together three of my research streams related to micro visualizations: data glyphs, where my joint research focused on studying the perception of small-multiple micro visualizations, word-scale visualizations, where my joint research focused on small visualizations embedded in text-documents, and small mobile data visualizations for smartwatches or fitness trackers. I consider these types of small visualizations together under the umbrella term ``micro visualizations.'' Micro visualizations are useful in multiple visualization contexts and I have been working towards a better understanding of the complexities involved in designing and using micro visualizations. Here, I define the term micro visualization, summarize my own and other past research and design guidelines and outline several design spaces for different types of micro visualizations based on some of the work I was involved in since my PhD.