Measuring Speaking Time from Privacy-Preserving Videos

Shun Maeda, Chunzhi Gu, Chao Zhang*

*この論文の責任著者

研究成果: 書籍の章/レポート/会議録会議への寄与査読

抄録

The ongoing pandemic caused by the COVID-19 virus is challenging many aspects of daily life such as restricting the conversation time. A vision-based face analyzing system is considerable for measuring and managing the person-wise speaking time, however, pointing a camera to people directly would be offensive and intrusive. In addition, privacy contents such as the identifiable face of the speakers should not be recorded during measuring. In this paper, we adopt a deep multimodal clustering method, called DMC, to perform unsupervised audiovisual learning for matching preprocessed audio with corresponding locations at videos. We set the camera above the speakers, and by feeding a pair of captured audio and visual data to a pre-trained DMC, a series of heatmaps that identify the location of the speaking people can be generated. Eventually, the speaking time measurement of each speaker can be achieved by accumulating the lasting speaking time of the corresponding heatmap.

本文言語英語
ホスト出版物のタイトルInternational Workshop on Advanced Imaging Technology, IWAIT 2022
編集者Masayuki Nakajima, Shogo Muramatsu, Jae-Gon Kim, Jing-Ming Guo, Qian Kemao
出版社SPIE
ISBN(電子版)9781510653313
DOI
出版ステータス出版済み - 2022
イベント2022 International Workshop on Advanced Imaging Technology, IWAIT 2022 - Hong Kong, 中国
継続期間: 2022/01/042022/01/06

出版物シリーズ

名前Proceedings of SPIE - The International Society for Optical Engineering
12177
ISSN(印刷版)0277-786X
ISSN(電子版)1996-756X

学会

学会2022 International Workshop on Advanced Imaging Technology, IWAIT 2022
国/地域中国
CityHong Kong
Period2022/01/042022/01/06

ASJC Scopus 主題領域

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学
  • コンピュータ サイエンスの応用
  • 応用数学
  • 電子工学および電気工学

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