2020 Vol.3 Jun. No.3

• Title: Face Recognition using Scalable Constraints Data Fusion
• Name: Fu yuanyuan
• Company: Department of Computer, Hunan City University ,CHINA
• Abstract:

  Face recognition is a biometric recognition technology, which becomes more and more important and includes face image acquisition, positioning, recognition preprocessing, identity identification and identity search. This paper uses Scalable Constraints Data Fusion methods to process face recognition problems. Firstly, Manifold alignment is about mapping several datasets into a global space, and is of great importance in learning the shared latent structure data fusion and multicue data matching. Secondly, we propose an algorithm to solve this problem via Local Tangent Space Alignment(LTSA). LTSA is used here as a method to find the inner manifold constraint of each dataset. A cost function to measure the quality of alignment is given by combining the inner manifold constraints of each dataset and the matching points constraints among different datasets. The effectiveness of our algorithm is validated by applying it to the problem of face image recognition.

• Keyword: Face recognition; Local tangent; Data fusion;
• DOI: 10.12250/jpciams2020030105
• Citation form: Fu yuanyuan.Face Recognition using Scalable Constraints Data Fusion[J]. Computer Informatization and Mechanical System, 2020, vol. 3, pp. 120-122.

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