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Techniques for seamless color registration and mapping on dense 3D models

Ruggero Pintus, Enrico Gobbetti, Marco Callieri, and Matteo Dellepiane

2017

Abstract

Today's most widely used 3D digitization approach is a combination of active geometric sensing, mainly using laser scanning, with active or passive color sensing, mostly using digital photography. Producing a seamless colored object, starting from a geometric representation and a set of photographs, is a data fusion problem requiring effective solutions for image-to-geometry registration, and color mapping and blending. This chapter provides a brief survey of the state-of-the-art solutions, ranging from manual approaches to fully scalable automated methods.

Reference and download information

Ruggero Pintus, Enrico Gobbetti, Marco Callieri, and Matteo Dellepiane. Techniques for seamless color registration and mapping on dense 3D models. Pages 355-376, Springer, 2017. http://dx.doi.org/10.1007/978-3-319-50518-3_17.

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Bibtex citation record

@InBook{Pintus:2017:TSC,
    author = {Ruggero Pintus and Enrico Gobbetti and Marco Callieri and Matteo Dellepiane},
    editor = {Nicola Masini and Francesco Soldovieri},
    title = {Techniques for seamless color registration and mapping on dense 3D models},
    booktitle = {Sensing the Past: From artifact to historical site},
    pages = {355--376},
    publisher = {Springer},
    year = {2017},
    isbn = {978-3-319-50518-3},
    abstract = { Today's most widely used 3D digitization approach is a combination of active geometric sensing, mainly using laser scanning, with active or passive color sensing, mostly using digital photography. Producing a seamless colored object, starting from a geometric representation and a set of photographs, is a data fusion problem requiring effective solutions for image-to-geometry registration, and color mapping and blending. This chapter provides a brief survey of the state-of-the-art solutions, ranging from manual approaches to fully scalable automated methods. },
    url = {http://vic.crs4.it/vic/cgi-bin/bib-page.cgi?id='Pintus:2017:TSC'},
}