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Expressive Face Recognition Using Optical Flow Approach

Published on None 2011 by K.Dhanalakshmi, S.Vanitha Sivagami
journal_cover_thumbnail
International Conference on VLSI, Communication & Instrumentation
Foundation of Computer Science USA
ICVCI - Number 12
None 2011
Authors: K.Dhanalakshmi, S.Vanitha Sivagami
cc465010-39e3-420d-b5c2-5cd531ba6cd8

K.Dhanalakshmi, S.Vanitha Sivagami . Expressive Face Recognition Using Optical Flow Approach. International Conference on VLSI, Communication & Instrumentation. ICVCI, 12 (None 2011), 6-9.

@article{
author = { K.Dhanalakshmi, S.Vanitha Sivagami },
title = { Expressive Face Recognition Using Optical Flow Approach },
journal = { International Conference on VLSI, Communication & Instrumentation },
issue_date = { None 2011 },
volume = { ICVCI },
number = { 12 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 6-9 },
numpages = 4,
url = { /proceedings/icvci/number12/2715-1466/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on VLSI, Communication & Instrumentation
%A K.Dhanalakshmi
%A S.Vanitha Sivagami
%T Expressive Face Recognition Using Optical Flow Approach
%J International Conference on VLSI, Communication & Instrumentation
%@ 0975-8887
%V ICVCI
%N 12
%P 6-9
%D 2011
%I International Journal of Computer Applications
Abstract

Face recognition system is one of the intensive research areas in computer vision and pattern recognition but many of which are focused on recognition of faces under various expressions involving many training sample per class. A constrained optical flow algorithm discussed in this paper recognizes facial images involving various expressions under the condition that one single training sample per class. This algorithm includes feature point labeling and optical flow computation to solve facial images under various expressions. In this paper, we propose the optical flow computation algorithm which computes intra person optical flow by combining the interperson and overall optical flow, and integrating with synthesized image in a probabilistic framework. Our experimental results confirm that the proposed face recognition system is more robust and recognizes the facial images under various expressions more accurately.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Opticalflow Synthesis Motion vector