Dense non-rigid structure-from-motion made easy - A spatial-temporal smoothness based solution

Yuchao Dai*, Huizhong Deng, Mingyi He

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    11 Citations (Scopus)

    Abstract

    This paper proposes a simple spatial-temporal smoothness based method for solving dense non-rigid structure-frommotion (NRSfM). First, we revisit the temporal smoothness and demonstrate that it can be extended to dense case directly. Second, we propose to exploit the spatial smoothness by resorting to the Laplacian of the 3D non-rigid shape. Third, to handle real world noise and outliers in measurements, we robustify the data term by using the L1 norm. In this way, our method could robustly exploit both spatial and temporal smoothness effectively and make dense non-rigid reconstruction easy. Our method is very easy to implement, which involves solving a series of least squares problems. Experimental results on both synthetic and real image dense NRSfM tasks show that the proposed method outperforms state-of-the-art dense non-rigid reconstruction methods.

    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
    PublisherIEEE Computer Society
    Pages4532-4536
    Number of pages5
    ISBN (Electronic)9781509021758
    DOIs
    Publication statusPublished - 2 Jul 2017
    Event24th IEEE International Conference on Image Processing, ICIP 2017 - Beijing, China
    Duration: 17 Sept 201720 Sept 2017

    Publication series

    NameProceedings - International Conference on Image Processing, ICIP
    Volume2017-September
    ISSN (Print)1522-4880

    Conference

    Conference24th IEEE International Conference on Image Processing, ICIP 2017
    Country/TerritoryChina
    CityBeijing
    Period17/09/1720/09/17

    Fingerprint

    Dive into the research topics of 'Dense non-rigid structure-from-motion made easy - A spatial-temporal smoothness based solution'. Together they form a unique fingerprint.

    Cite this