Português English
Contato

Proposta de Tese de Jorge Alberto Wagner Filho


Detalhes do Evento


Aluno: Jorge Alberto Wagner Filho
Orientadora: Profa. Dra. Luciana Porcher Nedel

Coorientador: Prof. Dr. Wolfgang Stuerzlinger

 

Título: Designing and Evaluating Immersive Analytics Environments for Spatio-Temporal Data

Linha de Pesquisa: Interação Humano-Computador, Realidade Virtual e Aumentada

 

Data: 29/11/2021
Horário: 18h30min.
Esta banca ocorrerá excepcionalmente de forma totalmente remota. Interessados em assistir a defesa poderão acessar a sala virtual através do link: https://nyu.zoom.us/j/97413567418

 

Banca Examinadora:
– Prof. Dr. Claudio T. Silva (NYU – New York University)
– Prof. Dr. Bernhard Jenny (Monash University)
– Prof. Dr. Bruce H. Thomas (UniSA – University of South Australia)

Presidente da Banca: Profa. Dra. Luciana Porcher Nedel

Abstract: In this work, I hypothesize that immersive and stereoscopic Virtual Reality (VR) environments, coupled with natural embodied interaction, will better support the visual exploration of three-dimensional spatio-temporal data representations. The research challenge in this thesis is to investigate this hypothesis and identify the most efficient design choices for visualization, interaction, and collaboration in such environments through iterative user evaluations. To this end, my first step was to design an immersive prototype based on the Space-Time Cube visual representation and validate it in comparison to a desktop-based baseline. While user performance in the controlled study was similar in both conditions for the majority of tasks, large differences were observed in subjective metrics and interaction patterns. The immersive version received higher usability scores and user preference, and was rated to have a lower mental workload, without causing discomfort in 25-minute-long VR sessions. Considering that the design space for user interfaces for Immersive Analytics applications is vast and lacks clear guidelines, I then investigated the effects of two relevant factors, exploration mode and frame of reference, while also varying visualization scale and physical movement demand. To isolate each factor, I implemented nine different conditions. Then I analyzed the results in terms of performance and qualitative measures and correlated with participants’ spatial abilities. While egocentric room-scale exploration significantly reduced mental workload, exocentric exploration improved performance in some tasks. Combining navigation and manipulation made tasks easier by reducing workload, temporal demand, and physical effort. To also account for interaction factors, in another experiment I then evaluated two standard techniques, virtual hands, with actions such as grabbing and stretching, and virtual ray pointers, with actions assigned to controller buttons, and a third option: seamlessly integrating both and allowing the user to alternate between them without explicit switches. No significant differences were found between hands and ray-casting in task performance, workload, or interactivity patterns. Yet, 60% of the participants preferred the mixed mode and benefited from it by choosing the best alternative for each low-level task. In the next phases of this work, I will investigate visualization design factors and perform evaluations with real-world data.

Keywords: Immersive analytics. space-time cube. trajectory visualization.