Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/73852
Title: AveroBot: an audio-visual dataset for people re-identification and verification in human-robot interaction
Authors: Marras, Mirko
Marín-Reyes, Pedro A.
Lorenzo Navarro, José Javier 
Castrillón Santana, Modesto Fernando 
Fenu, Gianni
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Deep learning
Face-voice dataset
Human-robot interaction
People re-identification
People verification
Issue Date: 2019
Project: Identificación Automática de Oradores en Sesiones Parlamentarias Usando Características Audiovisuales. 
Conference: 8th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2019 
Abstract: Intelligent technologies have pervaded our daily life, making it easier for people to complete their activities. One emerging application is involving the use of robots for assisting people in various tasks (e.g., visiting a museum). In this context, it is crucial to enable robots to correctly identify people. Existing robots often use facial information to establish the identity of a person of interest. But, the face alone may not offer enough relevant information due to variations in pose, illumination, resolution and recording distance. Other biometric modalities like the voice can improve the recognition performance in these conditions. However, the existing datasets in robotic scenarios usually do not include the audio cue and tend to suffer from one or more limitations: most of them are acquired under controlled conditions, limited in number of identities or samples per user, collected by the same recording device, and/or not freely available. In this paper, we propose AveRobot, an audio-visual dataset of 111 participants vocalizing short sentences under robot assistance scenarios. The collection took place into a three-floor building through eight different cameras with built-in microphones. The performance for face and voice re-identification and verification was evaluated on this dataset with deep learning baselines, and compared against audio-visual datasets from diverse scenarios. The results showed that AveRobot is a challenging dataset for people re-identification and verification.
URI: http://hdl.handle.net/10553/73852
ISBN: 978-989-758-351-3
DOI: 10.5220/0007690902550265
Source: Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, p. 255-265 (2019)
Appears in Collections:Actas de congresos
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