@inproceedings{4f0305f2cc6d46f6a9df95697ae903d6,
title = "Pose estimation system of 3-D human face using nearest feature line in its eigenspace representation",
abstract = "In this paper, a pose estimation system is developed using a minimum distance calculation of projected unknown viewpoint of a spatial image into its eigenspace representation to the nearest line of the two known viewpoints in the same eigenspace representation. In order to have a higher recognition rate on determining the pose position of the unknown image, we developed FullyK-LT and SubsetK-LT methods. The developed system is performed to determine the pose position of 2-D images taken from the human model by gradually changing visual points, which is done by successively varying the camera position from -90 to +90 with an interval of 15 degree. The experimental results shown that the highest recognition rate of the system is about 57.5\% when using FullyK-LT method, and could be increased up to 93.8\% when using SubsetK-LT method.",
keywords = "Cameras, Computer science, Face detection, Face recognition, Humans, Image databases, Image recognition, Machine vision, Principal component analysis, Spatial databases",
author = "R. Sripomo and Putro, \{Benyamin Kusumo\}",
note = "Publisher Copyright: {\textcopyright} 2002 IEEE.; Asia-Pacific Conference on Circuits and Systems, APCCAS 2002 ; Conference date: 28-10-2002 Through 31-10-2002",
year = "2002",
doi = "10.1109/APCCAS.2002.1115210",
language = "English",
series = "IEEE Asia-Pacific Conference on Circuits and Systems, Proceedings, APCCAS",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "241--245",
booktitle = "Proceedings - APCCAS 2002",
address = "United States",
}