Dynamic image-to-class warping for occluded face recognition

Xingjie Wei, Chang-Tsun Li, Zhen Lei, Dong Yi, Stan Z. Li

    Research output: Contribution to journalArticlepeer-review

    30 Citations (Scopus)
    3 Downloads (Pure)

    Abstract

    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.

    Original languageEnglish
    Article number6906281
    Pages (from-to)2035-2050
    Number of pages16
    JournalIEEE Transactions on Information Forensics and Security
    Volume9
    Issue number12
    Early online dateSep 2014
    DOIs
    Publication statusPublished - 01 Dec 2014

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