Look and Talk: Seamless AI Assistant Interaction with Gaze-Triggered Activation
April 12, 2025 Β· Declared Dead Β· π NASA/ESA Conference on Adaptive Hardware and Systems
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Zhang Qing, Rekimoto Jun
arXiv ID
2504.09296
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
NASA/ESA Conference on Adaptive Hardware and Systems
Last Checked
5 months ago
Abstract
Engaging with AI assistants to gather essential information in a timely manner is becoming increasingly common. Traditional activation methods, like wake words such as Hey Siri, Ok Google, and Hey Alexa, are constrained by technical challenges such as false activations, recognition errors, and discomfort in public settings. Similarly, activating AI systems via physical buttons imposes strict interactive limitations as it demands particular physical actions, which hinders fluid and spontaneous communication with AI. Our approach employs eye-tracking technology within AR glasses to discern a user's intention to engage with the AI assistant. By sustaining eye contact on a virtual AI avatar for a specific time, users can initiate an interaction silently and without using their hands. Preliminary user feedback suggests that this technique is relatively intuitive, natural, and less obtrusive, highlighting its potential for integrating AI assistants fluidly into everyday interactions.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted