Task-oriented function detection based on operational tasks

Yuchi Ishikawa, Haruya Ishikawa, Shuichi Akizuki, Masaki Yamazaki, Yasuhiro Taniguchi, Yoshimitsu Aoki

研究成果: Conference contribution

抄録

We propose novel representations for functions of an object, namely Task-oriented Function, which is improved upon the idea of Afforadance in the field of Robotics Vision. We also propose a convolutional neural network to detect task-oriented functions. This network takes as input an operational task as well as an RGB image and assign each pixel an appropriate label for every task. Task-oriented funciton makes it possible to descibe various ways to use an object because the outputs from the network differ depending on operational tasks. We introduce a new dataset for task-oriented function detection, which contains about 1200 RGB images and 6000 pixel-level annotations assuming five tasks. Our proposed method reached 0.80 mean IOU in our dataset.

本文言語English
ホスト出版物のタイトル2019 19th International Conference on Advanced Robotics, ICAR 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ635-640
ページ数6
ISBN(電子版)9781728124674
DOI
出版ステータスPublished - 2019 12月
イベント19th International Conference on Advanced Robotics, ICAR 2019 - Belo Horizonte, Brazil
継続期間: 2019 12月 22019 12月 6

出版物シリーズ

名前2019 19th International Conference on Advanced Robotics, ICAR 2019

Conference

Conference19th International Conference on Advanced Robotics, ICAR 2019
国/地域Brazil
CityBelo Horizonte
Period19/12/219/12/6

ASJC Scopus subject areas

  • 人工知能
  • 機械工学
  • 制御と最適化
  • モデリングとシミュレーション

フィンガープリント

「Task-oriented function detection based on operational tasks」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル