Publication Type

Conference Proceeding Article

Publication Date

7-2016

Abstract

It is common that users are interested in finding video segments, which contain further information about the video contents in a segment of interest. To facilitate users to find and browse related video contents, video hyperlinking aims at constructing links among video segments with relevant information in a large video collection. In this study, we explore the effectiveness of various video features on the performance of video hyperlinking, including subtitle, metadata, content features (i.e., audio and visual), surrounding context, as well as the combinations of those features. Besides, we also test different search strategies over different types of queries, which are categorized according to their video contents. Comprehensive experimental studies have been conducted on the dataset of TRECVID 2015 video hyperlinking task. Results show that (1) text features play a crucial role in search performance, and the combination of audio and visual features cannot provide improvements; (2) the consideration of contexts cannot obtain better results; and (3) due to the lack of training examples, machine learning techniques cannot improve the performance.

Keywords

Video hyperlinking, Video search

Discipline

Computer Sciences | Databases and Information Systems

Research Areas

Data Management and Analytics

Publication

SIGIR '16: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval: Pisa, Italy, July 17-21, 2016

First Page

1069

Last Page

1072

ISBN

9781450342902

Identifier

10.1145/2911451.2914765

Publisher

ACM

City or Country

New York

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1145/2911451.2914765

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