Eye-Landmarks Based Face Alignment In Non-Cooperative Face Biometrics

Journal Title: American journal of Engineering Research - Year 2018, Vol 7, Issue 10

Abstract

Current research in biometrics is being carried out with expectation of making a robust and reliable person identification system to be deployed in unconstrained and non-cooperative environment. However, these kinds of biometric systems predominantly suffer from various covariates (degradation factors). Among several covariates, misalignment is one of the critical issue that brings significant degradation in face recognition system. This is due to improper registration in intra-class samples as well as inter-class samples. In this paper we have proposed and analysed a face normalization technique to overcome the negative impacts of misalignment occurred during face detection. We used the database for experimentation that has a wellstructured deviation in pose angles of subjects along with unintentional random non-uniform illuminations which makes the dataset to be more suitable for evaluating algorithms more robustly. The proposed method is based on locating the landmarks of face and then cropping the face region proportional to the parameter obtained from estimated landmarks. This simple way of face normalization has been tested and validated on original face samples used in UBIPosePr dataset. Thus, the objectives of this paper are three-fold. 1) We have proposed the method of normalizing the face overcoming the scale of face that appears in image sample. 2) We experimented with actual face detection algorithms and found our normalization algorithm mitigates the misalignment problem. 3) A very robust and yet well-structured dataset has been used in our experimentation in order to study the behaviours of non-cooperative environment for face recognition system.

Authors and Affiliations

Nilesh Pawar

Keywords

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  • EP ID EP398566
  • DOI -
  • Views 63
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How To Cite

Nilesh Pawar (2018). Eye-Landmarks Based Face Alignment In Non-Cooperative Face Biometrics. American journal of Engineering Research, 7(10), 42-50. https://europub.co.uk/articles/-A-398566