Multi-resolution local probabilistic approach for low resolution face recognition

Shih Ming Huang, Yang Ting Chou, Szu Hua Wu, Jar-Ferr Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The low resolution problem in face recognition happens in video surveillance application and degrades the recognition rate dramatically. To overcome the low resolution problem, we introduce a novel face recognition method consisting of extracting multiresolution observation vectors, learning local similarity and making final decision based on top J local probabilities. There are two key contributions. One is to extract multiresolution local characteristics, and the other one is to select the top J local similarities automatically. The benefits of our method are to create multiresolution features and to exclude insignificant local features during recognition phase so that our method could achieve high recognition rate with a low resolution face image. The experimental results show that the proposed method reveals better performance for low resolution face recognition.

Original languageEnglish
Title of host publicationProceedings - 2011 International Conference on Intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011
Pages220-223
Number of pages4
DOIs
Publication statusPublished - 2011 Dec 1
Event2011 IEEE International conference on Intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011 - Wuhan, Hubei, China
Duration: 2011 Dec 142011 Dec 17

Publication series

NameProceedings - 2011 International Conference on Intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

Other

Other2011 IEEE International conference on Intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011
CountryChina
CityWuhan, Hubei
Period11-12-1411-12-17

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Biomedical Engineering

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