NDLI: Prediction of user's grasping intentions based on eye-hand coordination

Content Provider	IEEE Xplore Digital Library
Author	Carrasco, M. Clady, X.
Copyright Year	2010
Description	Author affiliation: Institut des Systèmes Intelligents et de Robotique (ISIR), Université Pierre et Marie Curie-UPMC, CNRS UMR 2777, France (Clady, X.) \|\| Escuela de Ingeniería Informática, Facultad de Ingeniería, Universidad Diego Portales, Av. Ejército 441, Santiago, Chile (Carrasco, M.)
Abstract	Eye-hand coordination is a primordial reach-to-grasp action performed by a human hand when reaching for an object. This paper proposes the use of a visual sensor which allows the simultaneous analysis of hand and eye motions in order to recognize the reach-to-grasp movement, i.e. to predict the grasping gesture. This solution fuses two viewpoints taken from the user's perspective. First, by using an eye-tracker device attached to the user's head; and second, by utilizing a wearable camera attached to the user's hand. The information from these two viewpoints is used to characterize multiple hand movements in conjunction with eye-gaze movements through a Hidden-Markov Model framework. In various experiments, we show that combining these two sources of information allows the prediction of a reach-to-grasp movement as well as the desired object.
Starting Page	4631
Ending Page	4637
File Size	1079561
Page Count	7
File Format	PDF
ISBN	9781424466740
ISSN	21530866
e-ISBN	9781424466764
DOI	10.1109/IROS.2010.5650024
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-18
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Hidden Markov models Cameras Humans Vectors Video sequences Robots object recognition Visual system gesture recognition eye-hand coordination reach-to-grasp movement
Content Type	Text
Resource Type	Article

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