Name
Abstract | ||
|---|---|---|
We present a novel method to summarize unconstrained videos using salient montages (i.e., a “melange” of frames in the video as shown in Fig. 1), by finding “montageable moments” and identifying the salient people and actions to depict in each montage. Our method aims at addressing the increasing need for generating concise visualizations from the large number of videos being captured from portabl... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TPAMI.2016.2623699 | IEEE Transactions on Pattern Analysis and Machine Intelligence |
Keywords | Field | DocType |
Videos,Cameras,Tracking,Detectors,YouTube,Feature extraction,Electronic mail | Computer vision,Computer graphics (images),Computer science,Feature extraction,Video tracking,Artificial intelligence,Salient | Journal |
Volume | Issue | ISSN |
39 | 11 | 0162-8828 |
Citations | PageRank | References |
1 | 0.35 | 44 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Min Sun | 1 | 1083 | 59.15 |
| Ali Farhadi | 2 | 4492 | 190.40 |
| Ben Taskar | 3 | 3175 | 209.33 |
| Steven M. Seitz | 4 | 8729 | 495.13 |