A novel sub-shot segmentation method for user-generated video

Zhuo Lei, Qian Zhang, Chi Zheng, Guoping Qiu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

With the proliferation of the user-generated videos, temporal segmentation is becoming a challengeable problem. Traditional video temporal segmentation methods like shot detection are not able to work on unedited user-generated videos, since they often only contain one single long shot. We propose a novel temporal segmentation framework for user-generated video. It finds similar frames with a tree partitioning min-Hash technique, constructs sparse temporal constrained affinity sub-graphs, and finally divides the video into sub-shot-level segments with a dense-neighbor-based clustering method. Experimental results show that our approach outperforms all the other related works. Furthermore, it is indicated that the proposed approach is able to segment user-generated videos at an average human level.

Original languageEnglish
Title of host publicationNinth International Conference on Graphic and Image Processing, ICGIP 2017
EditorsHui Yu, Junyu Dong
PublisherSPIE
ISBN (Electronic)9781510617414
DOIs
Publication statusPublished - 2018
Event9th International Conference on Graphic and Image Processing, ICGIP 2017 - Qingdao, China
Duration: 14 Oct 201716 Oct 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10615
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference9th International Conference on Graphic and Image Processing, ICGIP 2017
Country/TerritoryChina
CityQingdao
Period14/10/1716/10/17

Keywords

  • Clustering
  • Min-Hash
  • User-Generated Video
  • Video Temporal Segmentation

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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