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Denis Broggini

dblp:218/7258 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2018
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

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
Interaction techniques and input · 77% Human-robot interaction · 23%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interaction techniques and input › input sensing › gesture recognition
IMU-based gesture recognition		 0.312018
Learning to Detect Pointing Gestures From Wearable IMUs · AAAI 2018

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

1d convolutional neural network · 0.3
YearPublicationVenuePosition
2018 Learning to Detect Pointing Gestures From Wearable IMUs
abstract
We propose a learning-based system for detecting when a user performs a pointing gesture, using data acquired from IMU sensors, by means of a 1D convolutional neural network. We quantitatively evaluate the resulting detection accuracy, and discuss an application to a human-robot interaction task where pointing gestures are used to guide a quadrotor landing.
Denis Broggini, Boris Gromov, Alessandro Giusti, Luca Maria Gambardella
 AAAI1