DocumentCode :
2182027
Title :
Modelling daily actions through hand-based spatio-temporal features
Author :
Mur, Olga ; Frigola, Manel ; Casals, Alicia
Author_Institution :
Institute for Bioengineering of Catalonia and Universitat Politècnica de Catalunya, BarcelonaTech, Spain
fYear :
2015
fDate :
27-31 July 2015
Firstpage :
478
Lastpage :
483
Abstract :
In this paper, we propose a new approach to domestic action recognition based on a set of features which describe the relation between poses and movements of both hands. These features represent a set of basic actions in a kitchen in terms of the mimics of the hand movements, without needing information of the objects present in the scene. They address specifically the intra-class dissimilarity problem, which occurs when the same action is performed in different ways. The goal is to create a generic methodology that enables a robotic assistant system to recognize actions related to daily life activities and then, be endowed with a proactive behavior. The proposed system uses depth and color data acquired from a Kinect-style sensor and a hand tracking system. We analyze the relevance of the proposed hand-based features using a state-space search approach. Finally, we show the effectiveness of our action recognition approach using our own dataset.
Keywords :
Histograms; Joints; Robot sensing systems; Thumb; Tracking; Human activity recognition; disable and elderly assistance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Robotics (ICAR), 2015 International Conference on
Conference_Location :
Istanbul, Turkey
Type :
conf
DOI :
10.1109/ICAR.2015.7251499
Filename :
7251499
Link To Document :
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