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

Miguel Carrasco, Xavier Clady

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

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.

Original languageEnglish
Title of host publicationIEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings
Pages4631-4637
Number of pages7
DOIs
StatePublished - 2010
Event23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Taipei, Taiwan, Province of China
Duration: 18 Oct 201022 Oct 2010

Publication series

NameIEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings

Conference

Conference23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010
Country/TerritoryTaiwan, Province of China
CityTaipei
Period18/10/1022/10/10

Keywords

  • Eye-hand coordination
  • Gesture recognition
  • Object recognition
  • Reach-to-grasp movement
  • Visual system

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