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Dynamic image-to-class warping for occluded face recognition

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Version 2 2024-06-05, 03:28
Version 1 2019-03-14, 12:19
journal contribution
posted on 2024-06-05, 03:28 authored by X Wei, Chang-Tsun LiChang-Tsun Li, Z Lei, D Yi, SZ Li
© 2014 IEEE. Face recognition (FR) systems in real-world applications need to deal with a wide range of interferences, such as occlusions and disguises in face images. Compared with other forms of interferences such as nonuniform illumination and pose changes, face with occlusions has not attracted enough attention yet. A novel approach, coined dynamic image-to-class warping (DICW), is proposed in this work to deal with this challenge in FR. The face consists of the forehead, eyes, nose, mouth, and chin in a natural order and this order does not change despite occlusions. Thus, a face image is partitioned into patches, which are then concatenated in the raster scan order to form an ordered sequence. Considering this order information, DICW computes the image-to-class distance between a query face and those of an enrolled subject by finding the optimal alignment between the query sequence and all sequences of that subject along both the time dimension and within-class dimension. Unlike most existing methods, our method is able to deal with occlusions which exist in both gallery and probe images. Extensive experiments on public face databases with various types of occlusions have confirmed the effectiveness of the proposed method.

History

Journal

IEEE transactions on information forensics and security

Volume

9

Pagination

2035-2050

Location

Piscataway, N.J.

Open access

  • Yes

ISSN

1556-6013

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2014, IEEE

Issue

12

Publisher

IEEE

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