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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bourbakis, N. Tsitsoulis, A. |
| Copyright Year | 2010 |
| Description | Author affiliation: ATR Center, Wright State University, Dayton OH, USA (Bourbakis, N.; Tsitsoulis, A.) |
| Abstract | The synergistic combination of single standing methods for the efficient and effective solution of complex problems represent the next level of research the last two decades in the area of computer vision and image understanding, due to their complicated challenges. Many of these combinations are based on the human researcher's experimental studies and most recently on a semi-automated or automated (small scale) efforts for discovering such combinations [1]. One of the successful approaches for the creation of such synergies is the use of formal language. Thus, this paper deals with one of the major challenges by developing a formal language to represent human body positions for later automated tracking, monitoring and interpreting of body motion (signatures) in a smart home environment. More specifically, the representation of the body positions is presented by using skin detection, image segmentation, face detection, and Local Global graphs and the formal modeling of the body positions is described by using a language called SOMA (the Greek word for the body)‥ |
| Starting Page | 266 |
| Ending Page | 268 |
| File Size | 2376182 |
| Page Count | 3 |
| File Format | |
| ISBN | 9781424465767 |
| ISSN | 05473578 |
| e-ISBN | 9781424465781 |
| DOI | 10.1109/NAECON.2010.5712958 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-07-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Skin Artificial neural networks Humans Image color analysis Image edge detection Face detection |
| Content Type | Text |
| Resource Type | Article |
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