Lower Resolution Face Recognition in Surveillance Systems Using Discriminant Correlation Analysis

Mohammad Haghighat, Mohamed Abdel-Mottaleb

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

34 Scopus citations

Abstract

Due to large distances between surveillance cameras and subjects, the captured images usually have low resolution in addition to uncontrolled poses and illumination conditions that adversely affect the performance of face recognition algorithms. In this paper, we present a low-resolution face recognition technique based on Discriminant Correlation Analysis (DCA). DCA analyzes the correlation of the features in high-resolution and low-resolution images and aims to find projections that maximize the pair-wise correlations between the two feature sets and at the same time, separate the classes within each set. This makes it possible to project the features extracted from high-resolution and low-resolution images into a common space, in which we can apply matching. The proposed method is computationally efficient and can be applied to challenging real-time applications such as recognition of several faces appearing in a crowded frame of a surveillance video. Extensive experiments performed on low-resolution surveillance images from the SCface database as well as FRGC database demonstrated the efficacy of our proposed approach in the recognition of low-resolution face images, which outperformed other state-of-the-art techniques.

Original languageEnglish (US)
Title of host publicationProceedings - 12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017 - 1st International Workshop on Adaptive Shot Learning for Gesture Understanding and Production, ASL4GUP 2017, Biometrics in the Wild, Bwild 2017, Heterogeneous Face Recognition, HFR 2017, Joint Challenge on Dominant and Complementary Emotion Recognition Using Micro Emotion Features and Head-Pose Estimation, DCER and HPE 2017 and 3rd Facial Expression Recognition and Analysis Challenge, FERA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages912-917
Number of pages6
ISBN (Electronic)9781509040230
DOIs
StatePublished - Jun 28 2017
Event12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017 - Washington, United States
Duration: May 30 2017Jun 3 2017

Other

Other12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017
CountryUnited States
CityWashington
Period5/30/176/3/17

ASJC Scopus subject areas

  • Media Technology
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Lower Resolution Face Recognition in Surveillance Systems Using Discriminant Correlation Analysis'. Together they form a unique fingerprint.

Cite this