A Robotic Framework for Making Eye Contact with Humans
July 13, 2020 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Mohammed Moshiul Hoque
arXiv ID
2007.06531
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.RO
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Meeting eye contact is the essential prerequisite skill of a human to initiate any conversation with others. However, it is not an easy task for a robot to meet eye contact with a human if they are not facing each other initially or the human is intensely engaged his or her task. If the robot would like to start communication with a particular person, it should turn its gaze to that person first. However, only such a turning action alone is not always enough to set up eye contact. Sometimes, the robot should perform some strong actions so that it can capture the human's attention toward it. In this paper, we proposed a computational model for robots that can proactively capture human attention and makes eye contact with him or her. Evaluation experiments by using a robotic head reveal the effectiveness of the proposed model in different viewing situations.
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