| dc.date.accessioned | 2008-08-25T19:07:32Z | |
| dc.date.accessioned | 2018-11-26T22:25:27Z | |
| dc.date.available | 2008-08-25T19:07:32Z | |
| dc.date.available | 2018-11-26T22:25:27Z | |
| dc.date.issued | 1976-01 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/41948 | |
| dc.identifier.uri | http://repository.aust.edu.ng/xmlui/handle/1721.1/41948 | |
| dc.description | This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-75-C-0643. | en |
| dc.description.abstract | This paper shows how a good internal model of the subject viewed aids in the visual recognition and following of key parts. The role of knowledge driven top-down tools and methods is shown by recognizing a series of human figures drawn from Eadward Muybridge's collection of 1887. Knowledge of the subject's structure and actions are used to find the head, shoulder, elbow, hip, knees, and ankles of the subject. | en |
| dc.language.iso | en_US | en |
| dc.publisher | MIT Artificial Intelligence Laboratory | en |
| dc.title | Knowledge Driven Recognition of the Human Body | en |
| dc.type | Working Paper | en |
