A framework for the registration of color images with 3D models

Borgeat, Louis; Poirier, Guillaume; Beraldin, Angelo; Godin, Guy; Massicotte, Philippe; Picard, Michel

doi:10.1109/icip.2009.5413988

Cited by 12 publications

(8 citation statements)

References 6 publications

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“…The classic photo-mapping approach requires users to manually define correspondences between the image and the 3D model, typically using a point-and-click interface [Dellepiane et al 2008], which are then refined through error minimization. Since this straightforward approach is tiring and time-consuming, research has focused on reducing or simplifying manual operations, for example, by assisting the user by showing possible feature matches between photos and the rendered model [Borgeat et al 2009] or by reducing the manual effort by exploiting both matches between image and geometry and correspondences between pixels in different images [Franken et al 2005]. These manual methods are robust but easily become hard to apply to large image sets.…”

Section: D/3d Registrationmentioning

confidence: 99%

A Fast and Robust Framework for Semiautomatic and Automatic Registration of Photographs to 3D Geometry

Pintus

Gobbetti

2015

J. Comput. Cult. Herit.

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We present a simple, fast, and robust complete framework for 2D/3D registration capable to align in a semiautomatic or completely automatic manner a large set of unordered images to a massive point cloud. Our method converts the hard to solve image-to-geometry registration task in a Structure-from-Motion (SfM) plus a 3D/3D alignment problem. We exploit a SfM framework that, starting just from an unordered image collection, computes an estimate of the camera parameters and a sparse 3D geometry deriving from matched image features. We then coarsely register this model to the given 3D geometry by estimating a global scale and absolute orientation using two solutions: a minimal user intervention or a stochastic global point set registration approach. A specialized sparse bundle adjustment (SBA) step, that exploits the correspondence between the sparse geometry and the fine input 3D model, is then used to refine intrinsic and extrinsic parameters of each camera. Output data is suitable for photo blending frameworks to produce seamless colored models. The effectiveness of the method is demonstrated on a series of synthetic and real-world 2D/3D Cultural Heritage datasets. ACM Reference Format:Ruggero Pintus and Enrico Gobbetti. 2015. A fast and robust framework for semiautomatic and automatic registration of photographs to 3D geometry. ACM J. Comput. Cult.

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Section: D/3d Registrationmentioning

confidence: 99%

A Fast and Robust Framework for Semiautomatic and Automatic Registration of Photographs to 3D Geometry

Pintus

Gobbetti

2015

J. Comput. Cult. Herit.

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“…Our approach assumes that color images are reliably registered to the 3D models. Obtaining this registration is an orthogonal problem for which a variety of solutions exists (e.g., Borgeat et al [2009], Pintus et al [2011c, Corsini et al [2012], and Pintus and Gobbetti [2014]). The results in this work have been obtained with the approach of Pintus and Gobbetti [2014].…”

Section: Related Workmentioning

confidence: 99%

Mont’e Scan

Bettio¹,

Pintus

Villanueva³

et al. 2015

J. Comput. Cult. Herit.

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We propose an approach for improving the digitization of shape and color of 3D artworks in a cluttered environment using 3D laser scanning and flash photography. To separate clutter from acquired material, semiautomated methods are employed to generate masks used to segment the range maps and the color photographs. This approach allows the removal of unwanted 3D and color data prior to the integration of acquired data in a 3D model. Sharp shadows generated by flash acquisition are easily handled by this masking process, and color deviations introduced by the flash light are corrected at the color blending step by taking into account the geometry of the object. The approach has been evaluated in a large-scale acquisition campaign of the Mont’e Prama complex. This site contains an extraordinary collection of stone fragments from the Nuragic era, which depict small models of prehistoric nuraghe (cone-shaped stone towers), as well as larger-than-life archers, warriors, and boxers. The acquisition campaign has covered 37 statues mounted on metallic supports. Color and shape were acquired at a resolution of 0.25mm, which resulted in more than 6,200 range maps (about 1.3G valid samples) and 3,817 photographs.

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“…NRCC developed efficient and robust algorithms for 3D image processing, management, and real-time visualization of multiGiga-triangle meshed models of large and complex sites 40 . These algorithms are part of Atelier3D.ca, a general framework developed for the acquisition, modeling, visualization, and analysis of very large, multi-scale 3D datasets built from data gathered with 3D and color sensors 41 . This suite of tools is compatible with Innovmetric Polyworks Modeler TM .…”

Section: Data Processingmentioning

confidence: 99%

Best practices for the 3D documentation of the Grotta dei Cervi of Porto Badisco, Italy

et al. 2011

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The Grotta dei Cervi is a Neolithic cave where human presence has left many unique pictographs on the walls of many of its chambers. It was closed for conservation reasons soon after its discovery in 1970. It is for these reasons that a 3D documentation was started. Two sets of high resolution and detailed three-dimensional (3D) acquisitions were captured in 2005 and 2009 respectively, along with two-dimensional (2D) images. From this information a textured 3D model was produced for most of the 300-m long central corridor. Carbon dating of the guano used for the pictographs and environmental monitoring (Temperature, Relative humidity, and Radon) completed the project. This paper presents this project, some results obtained up to now, the best practice that has emerged from this work and a description of the processing pipeline that deals with more than 27 billions 3D coordinates.KEY WORDS: 3d imaging, large 3d models, best practices, rock art, texture mapping

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A framework for the registration of color images with 3D models

Cited by 12 publications

References 6 publications

A Fast and Robust Framework for Semiautomatic and Automatic Registration of Photographs to 3D Geometry

A Fast and Robust Framework for Semiautomatic and Automatic Registration of Photographs to 3D Geometry

Mont’e Scan

Best practices for the 3D documentation of the Grotta dei Cervi of Porto Badisco, Italy

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