The Effects of Short Video-Sharing Services on Video Copy Detection
Rintaro Yanagi Yamato Okamoto Shuhei Yokoo Shin'ichi Satoh
The short video-sharing services that allow users to post 10-30 second videos
(e.g., YouTube Shorts and TikTok) have attracted a lot of attention in recent
years. However, conventional video copy detection (VCD) methods mainly focus on
general video-sharing services (e.g., YouTube and Bilibili), and the effects of
short video-sharing services on video copy detection are still unclear.
Considering that illegally copied videos in short video-sharing services have
service-distinctive characteristics, especially in those time lengths, the pros
and cons of VCD in those services are required to be analyzed. In this paper,
we examine the effects of short video-sharing services on VCD by constructing a
dataset that has short video-sharing service characteristics. Our novel dataset
is automatically constructed from the publicly available dataset to have
reference videos and fixed short-time-length query videos, and such automation
procedures assure the reproducibility and data privacy preservation of this
paper. From the experimental results focusing on segment-level and video-level
situations, we can see that three effects: "Segment-level VCD in short
video-sharing services is more difficult than those in general video-sharing
services", "Video-level VCD in short video-sharing services is easier than
those in general video-sharing services", "The video alignment component mainly
suppress the detection performance in short video-sharing services".