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Interactive multiple object learning with scanty human supervision

Autor
Villamizar, M.A.; Garrell, A.; Sanfeliu, A.; Moreno-Noguer, F.
Tipus d'activitat
Article en revista
Revista
Computer vision and image understanding
Data de publicació
2016-08
Volum
149
Pàgina inicial
51
Pàgina final
64
DOI
https://doi.org/10.1016/j.cviu.2016.03.010 Obrir en finestra nova
Projecte finançador
Aerial robotic system integrating multiple arms and advanced manipulation capabilities for inspection and maintenance
FP7-ICT2009-6-269959 - IntellAct: Intelligent observation and execution of Actions and manipulations ViSen: Visual Sense, Tagging visual data with semantic descriptions
Interacción, aprendizaje y cooperación robot-humano en areas urbanas
RobInstruct: Instructing robots using natural communication skills - TIN2014-58178-R
Robot-Int-Coop: Robot-Human Interaction, Cooperation and Learning in Urban Areas
Repositori
http://hdl.handle.net/2117/102900 Obrir en finestra nova
URL
http://www.sciencedirect.com/science/article/pii/S1077314216300042 Obrir en finestra nova
Resum
We present a fast and online human-robot interaction approach that progressively learns multiple object classifiers using scanty human supervision. Given an input video stream recorded during the human robot interaction, the user just needs to annotate a small fraction of frames to compute object specific classifiers based on random ferns which share the same features. The resulting methodology is fast (in a few seconds, complex object appearances can be learned), versatile (it can be applied to...
Citació
Villamizar, M.A., Garrell, A., Sanfeliu, A., Moreno-Noguer, F. Interactive multiple object learning with scanty human supervision. "Computer vision and image understanding", Agost 2016, vol. 149, p. 51-64.
Paraules clau
Human-robot interaction, Interactive learning, Object recognition, Online classifier, human-robot interaction, recognition
Grup de recerca
ROBiri - Grup de Robòtica de l'IRI
VIS - Visió Artificial i Sistemes Intel.ligents