A Probabilistic Fusion Methodology for Face Recognition
<p/> <p>We propose a novel probabilistic framework that combines information acquired from different facial features for robust face recognition. The features used are the entire face, the edginess image of the face, and the eyes. In the training stage, individual feature spaces are cons...
Main Authors: | Rao K Srinivasa, Rajagopalan AN |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2005-01-01
|
Series: | EURASIP Journal on Advances in Signal Processing |
Subjects: | |
Online Access: | http://dx.doi.org/10.1155/ASP.2005.2772 |
Similar Items
-
Face Recognition Performance Improvement using a Similarity Score of Feature Vectors based on Probabilistic Histograms
by: SRIKOTE, G., et al.
Published: (2016-08-01) -
Fusion of deep and shallow features for face recognition
by: Zhao Shuhuan
Published: (2020-02-01) -
RGB-D FACE RECOGNITION USING LBP-DCT ALGORITHM
by: Sunil Kumar B L, et al.
Published: (2021-09-01) -
Recognition of identical twins using fusion of various facial feature extractors
by: Ayman Afaneh, et al.
Published: (2017-12-01) -
A Kernel-Based Probabilistic Collaborative Representation for Face Recognition
by: Jeng-Shyang Pan, et al.
Published: (2020-01-01)