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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Petersen, N. Stricker, D. |
| Copyright Year | 2012 |
| Description | Author affiliation: DFKI GmbH, Germany (Petersen, N.; Stricker, D.) |
| Abstract | We present a robust real-time capable and simple framework for segmenting video sequences and live-streams of manual workflows into the comprising single tasks. Using classifiers trained on these segments we can follow a user that is performing the workflow in real-time as well as learn task variants from additional video examples. Our proposed method neither requires object detection nor high-level features. Instead we propose a novel measure derived from image distance that evaluates image properties jointly without prior segmentation. Our method can cope with repetitive and free-hand activities and the results are in many cases comparable or equal to manual task segmentation. One important application of our method is the automatic creation of a step-by-step task documentation from a video demonstration. The entire process to automatically create a fully functional augmented reality manual will be explained in detail and results are shown. |
| Starting Page | 237 |
| Ending Page | 246 |
| File Size | 5384996 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781467346603 |
| e-ISBN | 9781467346627 |
| e-ISBN | 9781467346610 |
| DOI | 10.1109/ISMAR.2012.6402562 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-11-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Motion segmentation Robustness Manuals Augmented reality Training Current measurement |
| Content Type | Text |
| Resource Type | Article |
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