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Jimmy Petit

dblp:257/8315 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
0000-0002-1188-5575ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Immersive interaction · 28% Wearable and physiological sensing · 28% Interaction techniques and input · 28%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Immersive interaction
augmented reality interaction
0.412020
Towards BCI-Based Interfaces for Augmented Reality: Feasibility, Design and Evaluation · IEEE Trans. Vis. Comput. Graph. 2020
Wearable and physiological sensing
brain-computer interface
0.412020
Towards BCI-Based Interfaces for Augmented Reality: Feasibility, Design and Evaluation · IEEE Trans. Vis. Comput. Graph. 2020
Interaction techniques and input
hands-free interaction
0.412020
Towards BCI-Based Interfaces for Augmented Reality: Feasibility, Design and Evaluation · IEEE Trans. Vis. Comput. Graph. 2020
User interface design and tools › interaction design
interaction design space
0.112020
Towards BCI-Based Interfaces for Augmented Reality: Feasibility, Design and Evaluation · IEEE Trans. Vis. Comput. Graph. 2020
Human-robot interaction › teleoperation
mobile robot teleoperation
0.112020
Towards BCI-Based Interfaces for Augmented Reality: Feasibility, Design and Evaluation · IEEE Trans. Vis. Comput. Graph. 2020

Methods — techniques the papers use, named apart from their topics

user study · 0.4steady-state visually evoked potential · 0.4EEG · 0.4
YearPublicationVenuePosition
2020 Towards BCI-Based Interfaces for Augmented Reality: Feasibility, Design and Evaluation
abstract
Brain-Computer Interfaces (BCIs) enable users to interact with computers without any dedicated movement, bringing new hands-free interaction paradigms. In this paper we study the combination of BCI and Augmented Reality (AR). We first tested the feasibility of using BCI in AR settings based on Optical See-Through Head-Mounted Displays (OST-HMDs). Experimental results showed that a BCI and an OST-HMD equipment (EEG headset and Hololens in our case) are well compatible and that small movements of the head can be tolerated when using the BCI. Second, we introduced a design space for command display strategies based on BCI in AR, when exploiting a famous brain pattern called Steady-State Visually Evoked Potential (SSVEP). Our design space relies on five dimensions concerning the visual layout of the BCI menu; namely: orientation, frame-of-reference, anchorage, size and explicitness. We implemented various BCI-based display strategies and tested them within the context of mobile robot control in AR. Our findings were finally integrated within an operational prototype based on a real mobile robot that is controlled in AR using a BCI and a HoloLens headset. Taken together our results (4 user studies) and our methodology could pave the way to future interaction schemes in Augmented Reality exploiting 3D User Interfaces based on brain activity and BCIs.
Hakim Si-Mohammed, Jimmy Petit, Camille Jeunet, Ferran Argelaguet, Fabien Spindler, Andéol Évain, Nicolas Roussel 0001, Géry Casiez, Anatole Lécuyer
IEEE Trans. Vis. Comput. Graph.2