Fine-grained Video Retrieval using Query Phrases - Waseda-Meisei TRECVID 2017 AVS System - Waseda-Meisei T

Kazuya Ueki, Koji Hirakawa, Kotaro Kikuchi, Tetsunori Kobayash

研究成果: Conference contribution

抄録

In this paper, a joint team from Waseda University and Meisei University (team name: Waseda-Meisei) report their efforts on the ad-hoc video search (AVS) task for the TRECVID benchmark, which is conducted annually by the National Institute of Standards and Technology (NIST). For the AVS task, a system is required to perform a fine-grained search of target videos from a large-scale video database using a query phrase including multiple keywords, such as objects, persons, scenes, and actions. The system we submitted has the following two characteristics. First, to improve the coverage rate of classes corresponding to keywords in query phrases, we prepared a large number of classifiers that can detect objects, persons, scenes, and actions, which were trained using various image and video datasets. Second, when choosing a concept classifier corresponding to a keyword, we introduced a mechanism that allows us to select additional concept classifiers by incorporating natural language processing techniques. We submitted multiple systems with these characteristics to the TRECVID 2017 AVS task and one of our systems ranked the highest among all the submitted systems from 22 teams.

本文言語English
ホスト出版物のタイトル2018 24th International Conference on Pattern Recognition, ICPR 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ページ3322-3327
ページ数6
ISBN(電子版)9781538637883
DOI
出版ステータスPublished - 2018 11 26
イベント24th International Conference on Pattern Recognition, ICPR 2018 - Beijing, China
継続期間: 2018 8 202018 8 24

出版物シリーズ

名前Proceedings - International Conference on Pattern Recognition
2018-August
ISSN(印刷版)1051-4651

Other

Other24th International Conference on Pattern Recognition, ICPR 2018
国/地域China
CityBeijing
Period18/8/2018/8/24

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識

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