Face posture estimation using eigen analysis on an IBR (image based rendered) database

Kuntal Sengupta, Philip Lee, Jun Ohya

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)103-117
Number of pages15
JournalPattern Recognition
Volume35
Issue number1
DOIs
Publication statusPublished - 2002 Jan
Externally publishedYes

Fingerprint

Teleconferencing
Virtual reality

Keywords

  • Database search
  • Eigen analysis
  • Pose estimation
  • Shape description

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Face posture estimation using eigen analysis on an IBR (image based rendered) database. / Sengupta, Kuntal; Lee, Philip; Ohya, Jun.

In: Pattern Recognition, Vol. 35, No. 1, 01.2002, p. 103-117.

Research output: Contribution to journalArticle

@article{5db00a29094a4292a71a7ebd7b3a7cc4,
title = "Face posture estimation using eigen analysis on an IBR (image based rendered) database",
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.",
keywords = "Database search, Eigen analysis, Pose estimation, Shape description",
author = "Kuntal Sengupta and Philip Lee and Jun Ohya",
year = "2002",
month = "1",
doi = "10.1016/S0031-3203(01)00045-0",
language = "English",
volume = "35",
pages = "103--117",
journal = "Pattern Recognition",
issn = "0031-3203",
publisher = "Elsevier Limited",
number = "1",

}

TY - JOUR

T1 - Face posture estimation using eigen analysis on an IBR (image based rendered) database

AU - Sengupta, Kuntal

AU - Lee, Philip

AU - Ohya, Jun

PY - 2002/1

Y1 - 2002/1

N2 - 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.

AB - 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.

KW - Database search

KW - Eigen analysis

KW - Pose estimation

KW - Shape description

UR - http://www.scopus.com/inward/record.url?scp=0036132156&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036132156&partnerID=8YFLogxK

U2 - 10.1016/S0031-3203(01)00045-0

DO - 10.1016/S0031-3203(01)00045-0

M3 - Article

AN - SCOPUS:0036132156

VL - 35

SP - 103

EP - 117

JO - Pattern Recognition

JF - Pattern Recognition

SN - 0031-3203

IS - 1

ER -