RT Conference Proceedings
T1 Multi-modal data fusion for people perception in the social robot haru
A1 Ragel de la Torre, Ricardo
A1 Rey Arcenegui, Rafael
A1 Páez, Álvaro
A1 Ponce Chulani, Javier
A1 Nakamura, Keisuke
A1 Caballero, Fernando
A1 Merino, Luis
A1 Gómez, Randy
K1 Social Robotics
K1 Data Fusion
K1 Human-Robot Interaction
AB This article presents a people perception software architecture and its implementation, focused on the information of interest from the point of view of a social robot. The key modules employed to get the different people features, such as the body parts location, the face and hands information, and the speech, from a set of possible devices and configurations are described. The association and combination of these features using a temporal and geometric fusion system are explained in detail. A high-level interface for Human-Robot interaction using the resulting information from the fused people is proposed. The paper presents experimental results evaluating the relevant aspects of the system.
PB Springer Nature
YR 2023
FD 2023-02-01
LK https://hdl.handle.net/10433/23695
UL https://hdl.handle.net/10433/23695
LA en
NO R Ragel, R Rey, Á Páez, J Ponce, K Nakamura, F Caballero, L Merino and R Gómez. "Multi-modal Data Fusion for People Perception in the Social Robot Haru", International Conference on Social Robotics, 174-187, 2022
NO This work is partially supported by Programa Operativo FEDER Andalucia 2014-2020, Consejeria de Economía y Conocimiento (DeepBot, PY20\_00817) and the project PLEC2021-007868, funded by MCIN/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR.
NO Proyectos de investigaciónProyecto DeepBot (PY20_00817)Proyecto NHoA (PLEC2021-007868)
NO Departamento de Deporte e Informática
DS RIO
RD May 10, 2026