Abstract
Many existing methods for video summarisation are not suitable for on-line applications, where computational and memory constraints mean that feature extraction and frame selection must be simple and efficient. Our proposed method uses RGB moments to represent frames, and a control-chart procedure to identify shots from which keyframes are then selected. The new method produces summaries of higher quality than two state-of-the-art on-line video summarisation methods identified as the best among nine such methods in our previous study. The summary quality is measured against an objective ideal for synthetic data sets, and compared to user-generated summaries of real videos.
| Original language | English |
|---|---|
| Number of pages | 10 |
| Publication status | Published - 2018 |
| Event | International Joint Conference on Computer Vision and Pattern Recognition - Wellington, New Zealand Duration: 13 Dec 2018 → 15 Dec 2018 |
Conference
| Conference | International Joint Conference on Computer Vision and Pattern Recognition |
|---|---|
| Abbreviated title | CCVPR 2018 |
| Country/Territory | New Zealand |
| City | Wellington |
| Period | 13/12/18 → 15/12/18 |
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