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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sener, Ozan Zamir, Amir R. Savarese, Silvio Saxena, Ashutosh |
| Copyright Year | 2015 |
| Abstract | Human communication typically has an underlying structure. This is reflected in the fact that in many user generated videos, a starting point, ending, and certain objective steps between these two can be identified. In this paper, we propose a method for parsing a video into such semantic steps in an unsupervised way. The proposed method is capable of providing a semantic "storyline" of the video composed of its objective steps. We accomplish this utilizing both visual and language cues in a joint generative model. The proposed method can also provide a textual description for each of identified semantic steps and video segments. We evaluate this method on a large number of complex YouTube videos and show results of unprecedented quality for this new and impactful problem. |
| Starting Page | 4480 |
| Ending Page | 4488 |
| File Size | 15934471 |
| Page Count | 9 |
| File Format | |
| ISSN | 23807504 |
| e-ISBN | 9781467383912 |
| DOI | 10.1109/ICCV.2015.509 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-12-07 |
| Publisher Place | Chile |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Visualization Proposals Semantics YouTube Atomic measurements Conferences Computer vision |
| Content Type | Text |
| Resource Type | Article |
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