Video Preview Generation Based on Playback Records
Document Type
Conference Proceeding
Publication Date
11-1-2020
Abstract
A video preview is formed by joining a subset of video snippets from a source video. It is expected to be expressive to help enrich users' experience and hence increase the views of the full video. However, it is challenging to identify suitable video snippets to compose such video previews in support of user recommendation of full-length videos. In this paper, we formulate this problem as an optimization problem to maximize the total playback popularity of video segments based on the analysis of a large amount of users' playback records. We design an algorithm for this problem and provide proof of optimality. Furthermore, we conduct an experiment using real industrial data and recruit volunteers to assess the quality of generated video previews. The experimental results show the feasibility and applicability of our methods.
Identifier
85099786188 (Scopus)
ISBN
[9781728185774]
Publication Title
Proceedings of IEEE ACS International Conference on Computer Systems and Applications Aiccsa
External Full Text Location
https://doi.org/10.1109/AICCSA50499.2020.9316530
e-ISSN
21615330
ISSN
21615322
Volume
2020-November
Grant
2019C03138
Recommended Citation
Shen, Xuewen; He, Songlin; Yu, Dingguo; and Tang, Zhiyan, "Video Preview Generation Based on Playback Records" (2020). Faculty Publications. 4866.
https://digitalcommons.njit.edu/fac_pubs/4866
