Presentation 2018-03-18
Evaluation of the Shot Boundary Detection Method based on Unsupervised Learning from Video Big Data
Norio Katayama, Hiroshi Mo, Shin'ichi Satoh,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) Video data is a sequence of video frames and their temporal continuityis an essential property of video stream. In this paper, we present a framework of constructing video continuity model from large-scale video archives with unsupervised learning. Our method estimates the similarity distribution of continuous frame pairs by applying simple assumption on the minimum duration of continuous video segments and then determines discontinuous frame pairs as outliers. In order to verify the validity of the obtained model, the model is applied to the shot boundary detection. The results of experimental evaluation demonstrate the feasibility and the effectiveness of our method.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) shot boundary detection / unsupervised learning / video continuity model / video archive
Paper # BioX2017-53,PRMU2017-189
Date of Issue 2018-03-11 (BioX, PRMU)

Conference Information
Committee PRMU / BioX
Conference Date 2018/3/18(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Shinichi Sato(NII) / Kazuhiko Sumi(AGU)
Vice Chair Hironobu Fujiyoshi(Chubu Univ.) / Yoshihisa Ijiri(Omron) / Hiroshi Takano(Toyama Pref. Univ.) / Hitoshi Imaoka(NEC)
Secretary Hironobu Fujiyoshi(AIST) / Yoshihisa Ijiri(NAIST) / Hiroshi Takano(Shizuoka Univ.) / Hitoshi Imaoka(Fujitsu Labs.)
Assistant Masato Ishii(NEC) / Yusuke Sugano(Osaka Univ.) / Masatsugu Ichino(Univ. of Electro-Comm.) / Naoyuki Takada(Secom) / Norihiro Okui(KDDI Research)

Paper Information
Registration To Technical Committee on Pattern Recognition and Media Understanding / Technical Committee on Biometrics
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Evaluation of the Shot Boundary Detection Method based on Unsupervised Learning from Video Big Data
Sub Title (in English)
Keyword(1) shot boundary detection
Keyword(2) unsupervised learning
Keyword(3) video continuity model
Keyword(4) video archive
1st Author's Name Norio Katayama
1st Author's Affiliation National Institute of Informatics(NII)
2nd Author's Name Hiroshi Mo
2nd Author's Affiliation National Institute of Informatics(NII)
3rd Author's Name Shin'ichi Satoh
3rd Author's Affiliation National Institute of Informatics(NII)
Date 2018-03-18
Paper # BioX2017-53,PRMU2017-189
Volume (vol) vol.117
Number (no) BioX-513,PRMU-514
Page pp.pp.103-108(BioX), pp.103-108(PRMU),
#Pages 6
Date of Issue 2018-03-11 (BioX, PRMU)