Reconstructing a whole face image from a partially damaged or occluded image by multiple matching

Bon Woo Hwang, Seong Whan Lee

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Citations (Scopus)

    Abstract

    The problem we address in this paper is, given a facial image that is partially occluded or damaged by noise, to reconstruct a whole face, A key process for the reconstruction is to obtain the correspondences between the input image and the reference face. We present a method that matches an input image with multiple example images that are generated from a morphable face model. From the matched feature points, shape and texture of the full face are inferred by the non-iterative data completion algorithm. Compared with single matching with the particular "reference face", this multiple matching method increases the robustness of the matching. The experimental results of applying the algorithm to face images that are contaminated by Gaussian noise and those which are partially occluded show that the reconstructed faces are plausible and similar to the original ones.

    Original languageEnglish
    Title of host publicationAdvances in Biometrics - International Conference, ICB 2007, Proceedings
    PublisherSpringer Verlag
    Pages692-701
    Number of pages10
    ISBN (Print)9783540745488
    DOIs
    Publication statusPublished - 2007
    Event2007 International Conference on Advances in Biometrics, ICB 2007 - Seoul, Korea, Republic of
    Duration: 2007 Aug 272007 Aug 29

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume4642 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other2007 International Conference on Advances in Biometrics, ICB 2007
    Country/TerritoryKorea, Republic of
    CitySeoul
    Period07/8/2707/8/29

    Keywords

    • Data completion
    • Face reconstruction
    • Morphable face model
    • SIFT feature

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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