Effect of grasping uniformity on estimation of grasping region from gaze data

Pimwalun Witchawanitchanun, Zeynep Yucel, Akito Monden, Pattara Leelaprute

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study explores estimation of grasping region of objects from gaze data. Our study distinguishes from previous works by accounting for "grasping uniformity" of the objects. In particular, we consider three types of graspable objects: (i) with a well-defined graspable part (e.g. handle), (ii) without a grip but with an intuitive grasping region, (iii) without any grip or intuitive grasping region. We assume that these types define how "uniform" grasping region is across different graspers. In experiments, we use "Learning to grasp" data set and apply the method of [5] for estimating grasping region from gaze data. We compute similarity of estimations and ground truth annotations for the three types of objects regarding subjects (a) who perform free viewing and (b) who view the images with the intention of grasping. In line with many previous studies, similarity is found to be higher for non-graspers. An interesting finding is that the difference in similarity (between free viewing and motivated to grasp) is higher for type-iii objects; and comparable for type-i and ii objects. Based on this, we believe that estimation of grasping region from gaze data offers a larger potential to "learn" particularly grasping of type-iii objects.

Original languageEnglish
Title of host publicationHAI 2019 - Proceedings of the 7th International Conference on Human-Agent Interaction
PublisherAssociation for Computing Machinery, Inc
Pages265-267
Number of pages3
ISBN (Electronic)9781450369220
DOIs
Publication statusPublished - Sep 25 2019
Event7th International Conference on Human-Agent Interaction, HAI 2019 - Kyoto, Japan
Duration: Oct 6 2019Oct 10 2019

Publication series

NameHAI 2019 - Proceedings of the 7th International Conference on Human-Agent Interaction

Conference

Conference7th International Conference on Human-Agent Interaction, HAI 2019
CountryJapan
CityKyoto
Period10/6/1910/10/19

Keywords

  • Human-robot collaboration
  • Joint attention
  • Social robotics

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Software

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  • Cite this

    Witchawanitchanun, P., Yucel, Z., Monden, A., & Leelaprute, P. (2019). Effect of grasping uniformity on estimation of grasping region from gaze data. In HAI 2019 - Proceedings of the 7th International Conference on Human-Agent Interaction (pp. 265-267). (HAI 2019 - Proceedings of the 7th International Conference on Human-Agent Interaction). Association for Computing Machinery, Inc. https://doi.org/10.1145/3349537.3352787