Individual discriminative subspace for face recognition under uncontrolled conditions

Geng, Xin and Li, Ming 2007, Individual discriminative subspace for face recognition under uncontrolled conditions, in IVCNZ 2007 : Proceedings of Image and Vision Computing New Zealand, Image and Vision Computing NZ, [Hamilton, N.Z.], pp. 13-18.

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Title Individual discriminative subspace for face recognition under uncontrolled conditions
Author(s) Geng, Xin
Li, Ming
Conference name Image and Vision Computing New Zealand. Conference (2007: Hamilton, N.Z.)
Conference location Hamilton, N.Z.
Conference dates 5-7 December 2007
Title of proceedings IVCNZ 2007 : Proceedings of Image and Vision Computing New Zealand
Editor(s) Cree, Michael J.
Publication date 2007
Conference series Image and Vision Computing New Zealand Conference
Start page 13
End page 18
Publisher Image and Vision Computing NZ
Place of publication [Hamilton, N.Z.]
Keyword(s) face recognition
individual discriminative subspace
computer vision
image processing
Summary Most face recognition (FR) algorithms require the face images to satisfy certain restrictions in various aspects like view angle, illumination, occlusion, etc. But what is needed in general is the techniques that can recognize any face images recognizable by human beings. This paper provides one potential solution to this problem. A method named Individual Discriminative Subspace (IDS) is proposed for robust face recognition under uncontrolled conditions. IDS is the subspace where only the images from one particular person converge around the origin while those from others scatter. Each IDS can be used to distinguish one individual from others. There is no restriction on the face images fed into the algorithm, which makes it practical for real-life applications. In the experiments, IDS is tested on two large face databases with extensive variations and performs significantly better than 12 existing FR techniques.
Notes Reproduced with the specific permission of the copyright owner.
ISBN 9780473130084
0473130084
Language eng
Field of Research 080104 Computer Vision
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2007, Image and Vision Computing NZ
Persistent URL http://hdl.handle.net/10536/DRO/DU:30008096

Document type: Conference Paper
Collection: School of Engineering and Information Technology
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