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Workshop on attention models in robotics: visual systems for better HRI

Published: 03 March 2014 Publication History

Abstract

Attention is a concept of human perception that enables human subjects to select the potentially relevant parts out of the huge amount of sensory data and that enables interactions with other human subjects by sharing attention with each other. These abilities are also of large interest for autonomous robots, therefore, interest in modeling concepts of human attention computationally has increased strongly in the robotics community during the last decade. Especially in human-robot interaction, the ability to detect what a human partner is attending to and to act in a similar way to enable intuitive communication, are important skills for a robotic system.
Still, there exists a gap in knowledge transfer between researchers in human attention and robotic researchers with their specific, often task-related, problems. Both communities can mutually benefit from each other by sharing ideas. In the workshop, researchers in visual and multi-modal attention can profit from the rapidly growing field of robotics, which offers new and challenging research questions with very concrete applicability to challenging problems. Robotic researchers can learn how to integrate attention to support natural and real-time HRI.

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  1. Workshop on attention models in robotics: visual systems for better HRI

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    cover image ACM Conferences
    HRI '14: Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction
    March 2014
    538 pages
    ISBN:9781450326582
    DOI:10.1145/2559636
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

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    Published: 03 March 2014

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    Author Tags

    1. joint attention
    2. multi-modal attention
    3. saliency
    4. visual attention
    5. visual search

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    HRI'14
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    Acceptance Rates

    HRI '14 Paper Acceptance Rate 32 of 132 submissions, 24%;
    Overall Acceptance Rate 268 of 1,124 submissions, 24%

    Upcoming Conference

    HRI '25
    ACM/IEEE International Conference on Human-Robot Interaction
    March 4 - 6, 2025
    Melbourne , VIC , Australia

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