Implementation of Missing Data Imputation Schemes in Face Recognition Algorithm under Partial Occlusion
Date
2022
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Advances in Multimedia
Abstract
Face detection and recognition algorithms usually assume an image captured from a controlled environment. However, this is not
always the case, especially in crowd control under surveillance or footage from a crime scene, where partial occlusions are
unavoidable. Unfortunately, these occlusions have an adverse e ect on the performance of these classical recognition algorithms.
In this study, the performance of some selected data imputation schemes is evaluated on SVD/PCA frontal face recognition
algorithm. e experiment was done on two datasets: Ja e and MIT-CBCL, with immediate con rmation of the adverse e ect of
occlusion on the facial algorithm without implementing the imputation scheme. Further experimentation shows that IA is an ideal
missing data imputation scheme that works best with the SVD/PCA facial recognition algorithm.
Description
Research Article
Keywords
Data Imputation Schemes, n Face Recognition Algorithm, Partial Occlusion