People Recognition in Image Sequences by Supervised Learning
| dc.date.accessioned | 2004-10-20T21:03:31Z | |
| dc.date.accessioned | 2018-11-24T10:23:26Z | |
| dc.date.available | 2004-10-20T21:03:31Z | |
| dc.date.available | 2018-11-24T10:23:26Z | |
| dc.date.issued | 2000-06-01 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1721.1/7230 | |
| dc.identifier.uri | http://repository.aust.edu.ng/xmlui/handle/1721.1/7230 | |
| dc.description.abstract | We describe a system that learns from examples to recognize people in images taken indoors. Images of people are represented by color-based and shape-based features. Recognition is carried out through combinations of Support Vector Machine classifiers (SVMs). Different types of multiclass strategies based on SVMs are explored and compared to k-Nearest Neighbors classifiers (kNNs). The system works in real time and shows high performance rates for people recognition throughout one day. | en_US |
| dc.format.extent | 4611797 bytes | |
| dc.format.extent | 373760 bytes | |
| dc.language.iso | en_US | |
| dc.title | People Recognition in Image Sequences by Supervised Learning | en_US |
Files in this item
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|---|---|---|---|
| AIM-1688.pdf | 373.7Kb | application/pdf | View/ |
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