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Publications

Publications by Daniel Mendes

2020

Collaborative Tabletops for Blind People: The Effect of Auditory Design on Workspace Awareness

Authors
Mendes, D; Reis, S; Guerreiro, J; Nicolau, H;

Publication
Proc. ACM Hum. Comput. Interact.

Abstract
Interactive tabletops offer unique collaborative features, particularly their size, geometry, orientation and, more importantly, the ability to support multi-user interaction. Although previous efforts were made to make interactive tabletops accessible to blind people, the potential to use them in collaborative activities remains unexplored. In this paper, we present the design and implementation of a multi-user auditory display for interactive tabletops, supporting three feedback modes that vary on how much information about the partners' actions is conveyed. We conducted a user study with ten blind people to assess the effect of feedback modes on workspace awareness and task performance. Furthermore, we analyze the type of awareness information exchanged and the emergent collaboration strategies. Finally, we provide implications for the design of future tabletop collaborative tools for blind users. © 2020 ACM.

2020

Evaluating Animated Transitions between Contiguous Visualizations for Streaming Big Data

Authors
Pereira, T; Moreira, J; Mendes, D; Goncalves, D;

Publication
2020 IEEE VISUALIZATION CONFERENCE - SHORT PAPERS (VIS 2020)

Abstract

2020

Incidental Visualizations: Pre-Attentive Primitive Visual Tasks

Authors
Moreira, J; Mendes, D; Gonçalves, D;

Publication
AVI '20: International Conference on Advanced Visual Interfaces, Island of Ischia, Italy, September 28 - October 2, 2020

Abstract
In InfoVis design, visualizations make use of pre-attentive features to highlight visual artifacts and guide users' perception into relevant information during primitive visual tasks. These are supported by visual marks such as dots, lines, and areas. However, research assumes our pre-attentive processing only allows us to detect specific features in charts. We argue that a visualization can be completely perceived pre-attentively and still convey relevant information. In this work, by combining cognitive perception and psychophysics, we executed a user study with six primitive visual tasks to verify if they could be performed pre-attentively. The tasks were to find: horizontal and vertical positions, length and slope of lines, size of areas, and color luminance intensity. Users were presented with very simple visualizations, with one encoded value at a time, allowing us to assess the accuracy and response time. Our results showed that horizontal position identification is the most accurate and fastest task to do, and the color luminance intensity identification task is the worst. We believe our study is the first step into a fresh field called Incidental Visualizations, where visualizations are meant to be seen at-a-glance, and with little effort. © 2020 ACM.

2021

A Novel Tool for Immersive Authoring of Experiential Learning in Virtual Reality

Authors
Cassola, F; Pinto, M; Mendes, D; Morgado, L; Coelho, A; Paredes, H;

Publication
2021 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES ABSTRACTS AND WORKSHOPS (VRW 2021)

Abstract

2021

A Tool for Collaborative Anatomical Dissection

Authors
Roberto Zorzal, E; Sousa, M; Mendes, D; Figueiredo Paulo, S; Rodrigues, P; Jorge, J; Lopes, DS;

Publication
Human–Computer Interaction Series - Digital Anatomy

Abstract

2021

Immersive Authoring of Virtual Reality Training

Authors
Cassola, F; Pinto, M; Mendes, D; Morgado, L; Coelho, A; Paredes, H;

Publication
2021 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES ABSTRACTS AND WORKSHOPS (VRW 2021)

Abstract
The use of VR in industrial training contributes to reduce costs and risks, supporting more frequent and diversified use of experiential learning activities, an approach with proven results. In this work, we present an innovative immersive authoring tool for experiential learning in VR-based training. It enables a trainer to structure an entire VR training course in an immersive environment, defining its sub-components, models, tools, and settings, as well as specifying by demonstration the actions to be performed by trainees. The trainees performing the immersive training course have their actions recorded and matched to the ones specified by the trainer. © 2021 IEEE.

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