NDLI: Deformable model fitting with a mixture of local experts

Content Provider	IEEE Xplore Digital Library
Author	Saragih, J.M. Lucey, S. Cohn, J.F.
Copyright Year	2009
Description	Author affiliation: The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA (Saragih, J.M.; Lucey, S.; Cohn, J.F.)
Abstract	Local experts have been used to great effect for fitting deformable models to images. Typically, the best location in an image for the deformable model's landmarks are found through a locally exhaustive search using these experts. In order to achieve efficient fitting, these experts should afford an efficient evaluation, which often leads to forms with restricted discriminative capacity. In this work, a framework is proposed in which multiple simple experts can be utilized to increase the capacity of the detections overall. In particular, the use of a mixture of linear classifiers is proposed, the computational complexity of which scales linearly with the number of mixture components. The fitting objective is maximized using the expectation maximization (EM) algorithm, where approximations to the true objective are made in order to facilitate efficient and numerically stable fitting. The efficacy of the proposed approach is evaluated on the task of generic face fitting where performance improvement is observed over two existing methods.
Starting Page	2248
Ending Page	2255
File Size	893935
Page Count	8
File Format	PDF
ISBN	9781424444205
ISSN	15505499
DOI	10.1109/ICCV.2009.5459461
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-29
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Deformable models Shape Humans Face Robots Fitting Computational complexity Training data Robustness Biomedical imaging
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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