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Ph.D de

Ph.D
Group : Human-Centered Computing

A Content-Aware Design Approach to Multiscale Navigation

Starts on 01/09/2010
Advisor : PUECH, Claude
[Emmanuel Pietriga, Olivier Chapuis]

Funding :
Affiliation : Université Paris-Sud
Laboratory : LRI

Defended on 20/12/2013, committee :
Encadrants :
Claude Puech, Professeur (Université Paris-Sud)
Emmanuel Pietriga, Chargé de Recherche, HDR (Inria Chile)

Rapporteurs :
Géry Casiez, Professeur (Université des Sciences et Technologies de Lille)
Sylvain Paris, Docteur (Adobe Research)

Examinateurs :
Jean-Daniel Fekete, Directeur de Recherche HDR (Inria)
Tamy Boubekeur, Professeur (ENST)
Christine Froidevaux, Professeur (Université Paris-Sud)

Research activities :

Abstract :
Computer screens are very small compared to the size of large information spaces that arise in many domains. The visualization of such datasets requires multiscale navigation capabilities, enabling users to switch between zoomed-in detailed views and zoomed-out contextual views of the data. Designing interfaces that allow users to quickly identify objects of interest, get detailed views of those objects, relate them and put them in a broader spatial context, raise challenging issues. Multi-scale interfaces have been the focus of much research effort over the last twenty years.

There are several design approaches to address multiscale navigation issues. In this thesis, we review and categorize these approaches according to their level of content awareness. We identify two main approaches: content-driven, which optimizes interfaces for navigation in specific content; and content-agnostic, that applies to any type of data. We introduce the content-aware design approach, which dynamically adapts the interface to the content. The latter design approach can be used to design multiscale navigation techniques both in 2D or 3D spaces. We introduce Arealens and Pathlens, two content-aware fisheye lenses that dynamically adapt their shape to the underlying content to better preserve the visual aspect of objects of interest. We describe the techniques and their implementation, and report on a controlled experiment that evaluates the usability of Arealens compared to regular fisheye lenses, showing clear performance improvements with the new technique for a multiscale visual search task. We introduce a new distortion-oriented presentation library enabling the design of fisheye lenses featuring several foci of arbitrary shapes. Then, we introduce Gimlens, a multi-view detail-in-context visualization technique that enables users to navigate complex 3D models by drilling holes into their outer layers to reveal objects that are buried into the scene. Gimlens adapts to the geometry of objects of interest so as to better manage visual occlusion problems, selection mechanism and coordination of lenses.

Ph.D. dissertations & Faculty habilitations
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DISTRIBUTED COMPUTING WITH LIMITED RESOURCES


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