Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0031-3203(01)00045-0
Title: Face posture estimation using eigen analysis on an IBR (image based rendered) database
Authors: Sengupta, K. 
Lee, P.
Ohya, J.
Keywords: Database search
Eigen analysis
Pose estimation
Shape description
Issue Date: Jan-2002
Source: Sengupta, K., Lee, P., Ohya, J. (2002-01). Face posture estimation using eigen analysis on an IBR (image based rendered) database. Pattern Recognition 35 (1) : 103-117. ScholarBank@NUS Repository. https://doi.org/10.1016/S0031-3203(01)00045-0
Abstract: In this paper, we present a novel representation of the human face for estimating the orientation of the human head in a two dimensional intensity image. The method combines the use of the much familiar eigenvalue based dissimilarity measure with image based rendering. There are two main components of the algorith described here: The offline hierarchical image database generation and organization, and the online pose estimation stage. The synthetic images of the subject's face are automatically generated offline, for a large set of pose parameter values, using an affine coordinate based image reprojection technique. The resulting database is formally called as the IBR (or image based rendered) database. This is followed by the hierarchical organization of the database, which is driven by the eigenvalue based dissimilarity measure between any two synthetic image pair. This hierarchically organized database is a detailed, yet structured, representation of the subject's face. During the pose estimation of a subject in an image, the eigenvalue based measure is invoked again to search the synthetic (IBR) image closest to the real image. This approach provides a relatively easy first step to narrow down the search space for complex feature detection and tracking algorithms in potential applications like virtual reality and video-teleconferencing applications. © 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Source Title: Pattern Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/55996
ISSN: 00313203
DOI: 10.1016/S0031-3203(01)00045-0
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