New benchmark datasets and a character identification system on TV series

Zhuo Lei, Qian Zhang, Guoping Qiu

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

Abstract

Automatic character identification has been extensively studied in the past decades. However, most related works find characters only depending on their faces. One important reason is no dataset containing labels with all the occurrences of characters. Towards this end, we propose 3 datasets for character identification, which consist of 15 episodes (573 minutes). We label all the frames in which specified characters can be identified manually, regardless of whether faces or persons are detected. To the best of our knowledge, they are the first and largest datasets with all the occurrences of specified characters labelled for automatic character identification on TV material. Based on these datasets, we propose an automatic character identification system. Given a query image with a clear frontal face of a character, we can effectively utilize identified frames as new queries to explore remaining ones. In experiments, we show the average precision is substantially boosted in many cases.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages585-590
Number of pages6
ISBN (Electronic)9781538692141
DOIs
Publication statusPublished - Jul 2019
Event2019 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2019 - Shanghai, China
Duration: 8 Jul 201912 Jul 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2019

Conference

Conference2019 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2019
Country/TerritoryChina
CityShanghai
Period8/07/1912/07/19

Keywords

  • Identification
  • Re-ranking
  • TV
  • Track

ASJC Scopus subject areas

  • Media Technology
  • Computer Vision and Pattern Recognition

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