Multi-resolution local probabilistic approach for low resolution face recognition

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

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

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.

原文English
主出版物標題Proceedings - 2011 International Conference on Intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011
頁面220-223
頁數4
DOIs
出版狀態Published - 2011 十二月 1
事件2011 IEEE International conference on Intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011 - Wuhan, Hubei, China
持續時間: 2011 十二月 142011 十二月 17

出版系列

名字Proceedings - 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
國家China
城市Wuhan, Hubei
期間11-12-1411-12-17

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Biomedical Engineering

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