A Thumb Tip Wearable Device Consisting of Multiple Cameras to Measure Thumb Posture

Naoto Ienaga, Wataru Kawai, Koji Fujita, Natsuki Miyata, Yuta Sugiura, Hideo Saito

研究成果: Conference contribution

抄録

Today, cameras have become smaller and cheaper and can be utilized in various scenes. We took advantage of that to develop a thumb tip wearable device to estimate joint angles of a thumb as measuring human finger postures is important in terms of human-computer interface and to analyze human behavior. The device we developed consists of three small cameras attached at different angles so the cameras can capture the four fingers. We assumed that the appearance of the four fingers would change depending on the joint angles of the thumb. We made a convolutional neural network learn a regression relationship between the joint angles of the thumb and the images taken by the cameras. In this paper, we captured the keypoint positions of the thumb with a USB sensor device and calculated the joint angles to construct a dataset. The root mean squared error of the test data was 6.23° and 4.75° .

本文言語English
ホスト出版物のタイトルComputer Vision – ACCV 2018 Workshops - 14th Asian Conference on Computer Vision, 2018, Revised Selected Papers
編集者Gustavo Carneiro, Shaodi You
出版社Springer Verlag
ページ31-38
ページ数8
ISBN(印刷版)9783030210731
DOI
出版ステータスPublished - 2019
イベント14th Asian Conference on Computer Vision, ACCV 2018 - Perth, Australia
継続期間: 2018 12 22018 12 6

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11367 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference14th Asian Conference on Computer Vision, ACCV 2018
国/地域Australia
CityPerth
Period18/12/218/12/6

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

フィンガープリント

「A Thumb Tip Wearable Device Consisting of Multiple Cameras to Measure Thumb Posture」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