Abstract
Automatically predicting video highlight is an important task for media industry and streaming platform providers to save time and cost of manual video editing process. We propose a new ensemble model that combines multiple highlight detectors with each focusing on different parts of highlight events. Therefore, our model can capture more information-rich sections of events. Furthermore, the proposed model can extract improved features for highlight detection particularly when the train video set is small. We evaluate our model on e-sports and baseball videos.
| Translated title of the contribution | Subdivision Ensemble Model for Highlight Detection |
|---|---|
| Original language | Korean |
| Pages (from-to) | 620-628 |
| Number of pages | 9 |
| Journal | 방송공학회 논문지 |
| Volume | 25 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2020 |