Kinect-based automatic 3D high-resolution face modeling

Qi Sun, Yanlong Tang, Ping Hu, Jingliang Peng

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

    Abstract

    Microsoft Kinect can be used to capture both depth and color information and has been increasingly used for 3D modeling purposes. However, prior facial modeling methods either are computationally intensive or they generate rough results limited by the low resolution and instability of Kinect. In this paper, we propose a novel scheme for automatically and efficiently constructing a life-like textured 3D high-resolution model for the face of any user in front of a Kinect. Specifically, this scheme is composed of a sequence of steps including head region segmentation, depth and color image registration, resolution enhancement and 3D model fairing. Compared to prior methods, our scheme has a set of distinctive advantages. It can be robust even when the user is in a noisy environment; all the processes are automatic, which means that users need not interactively select feature points, and the energy optimization step is more efficient for fast processing of large-scale dynamic images.

    Original languageEnglish (US)
    Title of host publicationProceedings of 2012 International Conference on Image Analysis and Signal Processing, IASP 2012
    Pages382-385
    Number of pages4
    DOIs
    StatePublished - 2012
    Event2012 4th International Conference on Image Analysis and Signal Processing, IASP 2012 - Hangzhou, China
    Duration: Nov 9 2012Nov 11 2012

    Publication series

    NameProceedings of 2012 International Conference on Image Analysis and Signal Processing, IASP 2012

    Conference

    Conference2012 4th International Conference on Image Analysis and Signal Processing, IASP 2012
    CountryChina
    CityHangzhou
    Period11/9/1211/11/12

    Keywords

    • Kinect
    • face modeling
    • super-resolution

    ASJC Scopus subject areas

    • Computer Graphics and Computer-Aided Design
    • Computer Vision and Pattern Recognition
    • Signal Processing

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