A two-stage low complexity face recognition system for face images with alignment errors

Ching Yao Su, Jar-Ferr Yang

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

1 Citation (Scopus)

Abstract

Face recognition for images acquired from uncontrollable environment and target positions is a challenging task. These input images are first pre-processed and initially aligned by the face detection algorithm. However, there are still some residual geometric errors after the initial alignment by the face detection algorithm. If we don't take these errors into account, the recognition performance should be unacceptable. Although some iterative optimization algorithms can be used to fine-tune alignment during recognition, it increases computation load significantly. A two-stage face recognition system is proposed which comprises a block-based recognition algorithm to provide sufficient tolerance for geometric errors and then followed by a pixel-based recognition algorithm which only needs to evaluate a candidate subset from the previous stage. From simulation results, we find that this proposed system can reduce the average computation complexity about 69% and achieve promising performance.

Original languageEnglish
Title of host publication2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013
Pages2131-2134
Number of pages4
DOIs
Publication statusPublished - 2013 Sep 9
Event2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013 - Beijing, China
Duration: 2013 May 192013 May 23

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Other

Other2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013
CountryChina
CityBeijing
Period13-05-1913-05-23

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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