loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Fernando De la Torre ; Alvaro Collet ; Jeffrey F. Cohn and Takeo Kanade

Affiliation: Robotics Institute, Carnegie Mellon University, United States

ISBN: 978-972-8865-73-3

Keyword(s): Appearance Models, principal component analysis, Multi-band representation, learning filters.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Early Vision and Image Representation ; Feature Extraction ; Features Extraction ; Image and Video Analysis ; Image Registration ; Informatics in Control, Automation and Robotics ; Signal Processing, Sensors, Systems Modeling and Control ; Statistical Approach

Abstract: Appearance Models (AM) are commonly used to model appearance and shape variation of objects in images. In particular, they have proven useful to detection, tracking, and synthesis of people’s faces from video. While AM have numerous advantages relative to alternative approaches, they have at least two important drawbacks. First, they are especially prone to local minima in fitting; this problem becomes increasingly problematic as the number of parameters to estimate grows. Second, often few if any of the local minima correspond to the correct location of the model error. To address these problems, we propose Filtered Component Analysis (FCA), an extension of traditional Principal Component Analysis (PCA). FCA learns an optimal set of filters with which to build a multi-band representation of the object. FCA representations were found to be more robust than either grayscale or Gabor filters to problems of local minima. The effectiveness and robustness of the proposed algorithm is demon strated in both synthetic and real data. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.227.233.55

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
De la Torre F.; Collet A.; F. Cohn J.; Kanade T. and (2007). ROBUST APPEARANCE MATCHING WITH FILTERED COMPONENT ANALYSIS.In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 978-972-8865-73-3, pages 207-212. DOI: 10.5220/0002049202070212

@conference{visapp07,
author={Fernando {De la Torre} and Alvaro Collet and Jeffrey {F. Cohn} and Takeo Kanade},
title={ROBUST APPEARANCE MATCHING WITH FILTERED COMPONENT ANALYSIS},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2007},
pages={207-212},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002049202070212},
isbn={978-972-8865-73-3},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - ROBUST APPEARANCE MATCHING WITH FILTERED COMPONENT ANALYSIS
SN - 978-972-8865-73-3
AU - De la Torre, F.
AU - Collet, A.
AU - F. Cohn, J.
AU - Kanade, T.
PY - 2007
SP - 207
EP - 212
DO - 10.5220/0002049202070212

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.