Extraction of Read Text for Automatic Video Annotation
| Language | English |
|---|---|
| Type | Proceedings of International Conferences |
| Authors | Mizuki Matsubara, Joachim Folz, Takumi Toyama, Marcus Liwicki, Andreas Dengel, Koichi Kise |
| Title | Extraction of Read Text for Automatic Video Annotation |
| Journal | UbiComp/ISWC'15 Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers |
| Pages | pp.849-856 |
| Location | Osaka, Japan |
| Reviewed | Reviewed |
| Presentation type | Oral |
| Date | September 2015 |
| Research fields | Document Image Analysis |
| DOI | 10.1145/2800835.2804333 |
| Key | Matsubara2015_ISWC (id=1472) |
Abstract
This paper presents an automatic video annotation method which utilizes the user’s reading behaviour. Using a wearable eye tracker, we identify the video frames where the user reads a text document and extract the sentences that have been read by him or her. The extracted sentences are used to annotate video segments which are taken from the user’s egocentric perspective. An advantage of the proposed method is that we do not require training data, which is often used by a video annotation method. We examined the accuracy of the proposed annotation method with a pilot study where the experiment participants drew an illustration reading a tutorial. The method achieved 64:5% recall and 30:8% precision.
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