2011
Other
Metadata Only Access
Enhancement of LDR videos using HDR devices
Banterle Francesco, Dellepiane Matteo, Scopigno Roberto
In this paper, we present a novel technique for enhancing the dynamic range of LDR videos using HDR videos or photographs. In particular our technique can be used for two setups. In the first one, the two devices shares the same capturing lens. In the second setup, devices are coupled in a stereo rig.
Banterle Francesco, Dellepiane Matteo, Scopigno Roberto
In this paper, we present a novel technique for enhancing the dynamic range of LDR videos using HDR videos or photographs. In particular our technique can be used for two setups. In the first one, the two devices shares the same capturing lens. In the second setup, devices are coupled in a stereo rig.
See at:
CNR IRIS 
2011
Contribution to conference
Restricted
High dynamic range images for enhancing low dynamic range content
Banterle Francesco, Dellepiane Matteo, Scopigno Roberto
This poster presents a practical system for enhancing the quality of Low Dynamic Range (LDR) videos using High Dynamic Range (HDR) background images. Our technique relies on the assumption that the HDR information is static in the video footage. This assumption can be valid in many scenarios where moving subjects are the main focus of the footage and do not have to interact with moving light sources or highly reflective objects. Another valid scenario is teleconferencing via webcams, where the background is typically over-exposed, not allowing the users to perceive correctly the environment where the communication is happening.DOI: 10.1145/2073304.2073351
Project(s): 3D-COFORM
Metrics:
Banterle Francesco, Dellepiane Matteo, Scopigno Roberto
This poster presents a practical system for enhancing the quality of Low Dynamic Range (LDR) videos using High Dynamic Range (HDR) background images. Our technique relies on the assumption that the HDR information is static in the video footage. This assumption can be valid in many scenarios where moving subjects are the main focus of the footage and do not have to interact with moving light sources or highly reflective objects. Another valid scenario is teleconferencing via webcams, where the background is typically over-exposed, not allowing the users to perceive correctly the environment where the communication is happening.DOI: 10.1145/2073304.2073351
Project(s): 3D-COFORM
Metrics:
See at:
dl.acm.org | doi.org | CNR IRIS | CNR IRIS
2011
Other
Metadata Only Access
Tone mapping for stereo and multi-view HDR content
Banterle Francesco, Callieri Marco, Dellepiane Matteo, Scopigno Roberto
In this paper, we present a novel technique for tone mapping which tackles stereo and multi-view HDR content. Stereo and multi-view image processing is not a trivial task in order to avoid inconsistencies in colors and on the whole appearance in the final results. Our method, for minimizing inconsistencies which appear if images are processed separately, leverages on filtering stereo images in the disparity space. We show that this filtering minimize inconsistencies allowing a pleasant fruition of the stereo content on LDR displays. Finally, we show how to extend this method to multi-view images.
Banterle Francesco, Callieri Marco, Dellepiane Matteo, Scopigno Roberto
In this paper, we present a novel technique for tone mapping which tackles stereo and multi-view HDR content. Stereo and multi-view image processing is not a trivial task in order to avoid inconsistencies in colors and on the whole appearance in the final results. Our method, for minimizing inconsistencies which appear if images are processed separately, leverages on filtering stereo images in the disparity space. We show that this filtering minimize inconsistencies allowing a pleasant fruition of the stereo content on LDR displays. Finally, we show how to extend this method to multi-view images.
See at:
CNR IRIS
2011
Conference article
Restricted
Enhancement of low dynamic range videos using highdynamic range backgrounds
Banterle F, Dellepiane M, Scopigno R
In this paper, we present a practical system for enhancing the quality of Low Dynamic Range (LDR) videos using High Dynamic Range (HDR) background images. Our technique relies on the assumption that the HDR information is static in the video footage. This assumption can be valid in many scenarios where moving subjects are the main focus of the footage and do not have to interact with moving light sources or highly reflective objects. Another valid scenario is teleconferencing via webcams, where the background is typically over-exposed, not allowing the users to perceive correctly the environment where the communication is happening.Project(s): 3D-COFORM
Banterle F, Dellepiane M, Scopigno R
In this paper, we present a practical system for enhancing the quality of Low Dynamic Range (LDR) videos using High Dynamic Range (HDR) background images. Our technique relies on the assumption that the HDR information is static in the video footage. This assumption can be valid in many scenarios where moving subjects are the main focus of the footage and do not have to interact with moving light sources or highly reflective objects. Another valid scenario is teleconferencing via webcams, where the background is typically over-exposed, not allowing the users to perceive correctly the environment where the communication is happening.Project(s): 3D-COFORM
See at:
CNR IRIS | CNR IRIS | vcg.isti.cnr.it
2011
Contribution to book
Open Access
Modelli digitali 3D per il supporto al restauro: riassemblaggio digitale e ricostruzione virtuale
Callieri M, Dellepiane M, Scopigno R
The participation of CNR in the Madonna di Pietranico restoration project was not limited to the creation of the 3D models of the fragments and of the reconstructed statue for documentation purposes. The goal was more challenging - to analyze and develop new methods to assist the work of art historians and restorers in the various phases throughout the process of analysis of the condition of the statue and during the restoration work. The 3D model played a pivotal role in achieving these objectives and was often a key element in an individual phase. It was used to compare hypotheses for the reconstruction of the various fragments, to create a virtual re-composed statue from re-assembled fragments and even to analyze hypotheses on the original coloring.
Callieri M, Dellepiane M, Scopigno R
The participation of CNR in the Madonna di Pietranico restoration project was not limited to the creation of the 3D models of the fragments and of the reconstructed statue for documentation purposes. The goal was more challenging - to analyze and develop new methods to assist the work of art historians and restorers in the various phases throughout the process of analysis of the condition of the statue and during the restoration work. The 3D model played a pivotal role in achieving these objectives and was often a key element in an individual phase. It was used to compare hypotheses for the reconstruction of the various fragments, to create a virtual re-composed statue from re-assembled fragments and even to analyze hypotheses on the original coloring.
2011
Other
Restricted
A low-cost time-critical obstacle avoidance system for the visually impaired
Bernabei D, Ganovelli F, Di Benedetto M, Dellepiane M, Scopigno R
We present a low cost system for unassisted mobility of blind people built with off-the-shelf technology. Our system takes as input the depth maps produced by the Kinectic device coupled with the data from its accelerometer to provide a registered point based 3D representation of the scene in front of the user. We developed a time-critical framework to analyze the scene and classify the ground and still or moving obstacles and provide the user with a constant and reliable feedback.
Bernabei D, Ganovelli F, Di Benedetto M, Dellepiane M, Scopigno R
We present a low cost system for unassisted mobility of blind people built with off-the-shelf technology. Our system takes as input the depth maps produced by the Kinectic device coupled with the data from its accelerometer to provide a registered point based 3D representation of the scene in front of the user. We developed a time-critical framework to analyze the scene and classify the ground and still or moving obstacles and provide the user with a constant and reliable feedback.
2011
Software
Metadata Only Access
Visual computing library
Cignoni P, Ganovelli F, Ponchio F, Pietroni N, Corsini M, Ranzuglia G, Di Benedetto M, Tarini M, Dellepiane M
The VCG library is a portable C++ templated library for manipulation, processing and displaying with OpenGL polygon meshes. The library, released under the GPL license is the result of the collaborative efforts of the Visual Computing Lab ( VCGLab ) of the ISTI - institute of the Italian National Research Council. The new release includes new data structures to handle half edges and generic polygonal meshes and includes the Eigen2 library for math support.
Cignoni P, Ganovelli F, Ponchio F, Pietroni N, Corsini M, Ranzuglia G, Di Benedetto M, Tarini M, Dellepiane M
The VCG library is a portable C++ templated library for manipulation, processing and displaying with OpenGL polygon meshes. The library, released under the GPL license is the result of the collaborative efforts of the Visual Computing Lab ( VCGLab ) of the ISTI - institute of the Italian National Research Council. The new release includes new data structures to handle half edges and generic polygonal meshes and includes the Eigen2 library for math support.
See at:
CNR IRIS
2011
Journal article
Restricted
Multiscale acquisition and presentation of very large artifacts: the case of portalada
Callieri Marco, Chica Antoni, Dellepiane Matteo, Besora Isaac, Corsini Massimiliano, Moyes Jordi, Ranzuglia Guido, Scopigno Roberto, Brunet Pere
The dichotomy between full detail representation and the efficient management of data digitization is still a big issue in the context of the acquisition and visualization of 3D objects, especially in the field of the cultural heritage. Modern scanning devices enable very detailed geometry to be acquired, but it is usually quite hard to apply these technologies to large artifacts. In this article we present a project aimed at virtually reconstructing the impressive (7×11 m.) portal of the Ripoll Monastery, Spain. The monument was acquired using triangulation laser scanning technology, producing a dataset of 2212 range maps for a total of more than 1 billion triangles. All the steps of the entire project are described, from the acquisition planning to the final setup for dissemination to the public. We show how time-of-flight laser scanning data can be used to speed-up the alignment process. In addition we show how, after creating a model and repairing imperfections, an interactive and immersive setup enables the public to navigate and display a fully detailed representation of the portal. This article shows that, after careful planning and with the aid of state-of-the-art algorithms, it is now possible to preserve and visualize highly detailed information, even for very large surfaces.Source: ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE, vol. 3 (issue 4), pp. 14-20
DOI: 10.1145/1957825.1957827
Metrics:
Callieri Marco, Chica Antoni, Dellepiane Matteo, Besora Isaac, Corsini Massimiliano, Moyes Jordi, Ranzuglia Guido, Scopigno Roberto, Brunet Pere
The dichotomy between full detail representation and the efficient management of data digitization is still a big issue in the context of the acquisition and visualization of 3D objects, especially in the field of the cultural heritage. Modern scanning devices enable very detailed geometry to be acquired, but it is usually quite hard to apply these technologies to large artifacts. In this article we present a project aimed at virtually reconstructing the impressive (7×11 m.) portal of the Ripoll Monastery, Spain. The monument was acquired using triangulation laser scanning technology, producing a dataset of 2212 range maps for a total of more than 1 billion triangles. All the steps of the entire project are described, from the acquisition planning to the final setup for dissemination to the public. We show how time-of-flight laser scanning data can be used to speed-up the alignment process. In addition we show how, after creating a model and repairing imperfections, an interactive and immersive setup enables the public to navigate and display a fully detailed representation of the portal. This article shows that, after careful planning and with the aid of state-of-the-art algorithms, it is now possible to preserve and visualize highly detailed information, even for very large surfaces.Source: ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE, vol. 3 (issue 4), pp. 14-20
DOI: 10.1145/1957825.1957827
Metrics:
See at:
Journal on Computing and Cultural Heritage | CNR IRIS | CNR IRIS | portal.acm.org
2011
Conference article
Restricted
Improving high-speed scanning systems by photometric stereo
Larue F, Dellepiane M, Scopigno R
High-speed scanning systems can be extremely valuable for Cultural Heritage applications, especially when large collections of small objects have to be acquired. However, fine details may not be acquired using this technology. Nevertheless, it is possible to try to recover them by taking advantage of the additional data provided by these systems: the calibrated video sequence of the acquisition, and the position of the projector light for each frame. In this paper, we propose a workflow that processes the video sequence with a photometric stereo approach, in order to refine the coarse geometry provided by the scanner. A normal map is first extracted by a method that accounts for the unevenly distributed sampling that generally results from the particular trajectory followed by this kind of scanners during the acquisition. This normal map is then integrated in order to recover missing geometric features. Good performances are achieved, since the whole workflow is particularly suited to GPU programming.Project(s): 3D-COFORM
Larue F, Dellepiane M, Scopigno R
High-speed scanning systems can be extremely valuable for Cultural Heritage applications, especially when large collections of small objects have to be acquired. However, fine details may not be acquired using this technology. Nevertheless, it is possible to try to recover them by taking advantage of the additional data provided by these systems: the calibrated video sequence of the acquisition, and the position of the projector light for each frame. In this paper, we propose a workflow that processes the video sequence with a photometric stereo approach, in order to refine the coarse geometry provided by the scanner. A normal map is first extracted by a method that accounts for the unevenly distributed sampling that generally results from the particular trajectory followed by this kind of scanners during the acquisition. This normal map is then integrated in order to recover missing geometric features. Good performances are achieved, since the whole workflow is particularly suited to GPU programming.Project(s): 3D-COFORM
2011
Journal article
Restricted
3D models for cultural heritage: beyond plain visualization
Scopigno R, Callieri M, Cignoni P, Corsini M, Dellepiane M, Ponchio F, Ranzuglia G
Digital technologies are transforming the way cultural heritage researchers, archaeologists, and curators work by providing new ways to collaborate, record excavations, and restore artifacts. The first Web extra is a video that highlights the Cenobium project, a pioneering Web system for presenting medieval cloisters and sculptures. The second video presents the results of a study using digital 3D technologies to assess the apparent shape similarity of a bronze statuette and drawings, to evaluate a possible innovative attribution hypothesis. The third video presents a very complex restoration project of a statue severely damaged by a recent earthquake in central Italy. The project made extensive use of ICT technologies. The fourth video presents a hypothesis of the original location of some terracotta statues over the old temple of Luni during the Roman Etruscan period in Italy. The fifth video was produced for a 2010 exposition on the Roman Empire held in Tokyo and shows the potential of new visual technologies for presenting works of art and supporting storytelling.Source: COMPUTER, vol. 44 (issue 7), pp. 48-55
DOI: 10.1109/mc.2011.196
Project(s): V-MUST.NET
Metrics:
Scopigno R, Callieri M, Cignoni P, Corsini M, Dellepiane M, Ponchio F, Ranzuglia G
Digital technologies are transforming the way cultural heritage researchers, archaeologists, and curators work by providing new ways to collaborate, record excavations, and restore artifacts. The first Web extra is a video that highlights the Cenobium project, a pioneering Web system for presenting medieval cloisters and sculptures. The second video presents the results of a study using digital 3D technologies to assess the apparent shape similarity of a bronze statuette and drawings, to evaluate a possible innovative attribution hypothesis. The third video presents a very complex restoration project of a statue severely damaged by a recent earthquake in central Italy. The project made extensive use of ICT technologies. The fourth video presents a hypothesis of the original location of some terracotta statues over the old temple of Luni during the Roman Etruscan period in Italy. The fifth video was produced for a 2010 exposition on the Roman Empire held in Tokyo and shows the potential of new visual technologies for presenting works of art and supporting storytelling.Source: COMPUTER, vol. 44 (issue 7), pp. 48-55
DOI: 10.1109/mc.2011.196
Project(s): V-MUST.NET
Metrics:
2011
Contribution to book
Restricted
Processing sampled 3D data: reconstruction and visualization technologies
Callieri M, Dellepiane M, Cignoni P, Scopigno R
The introduction of new technologies in the context of Cultural Heritage (CH) and Archeology has often been a difficult issue. This is probably related to the lack in confidence in replacing consolidated approaches with experimental methods heavily based on innovative hardware or software systems. This already happened for a number of revolutionary technologies: for example, the advent of photography, color images and digital cameras took some time before changing the reference methods for archival and studies in the context of archeological excavation or of restoration actions. The same considerations hold for the use of digital 3D models in CH applications. One basic issue is the need to switch from a two-dimensional visualization and reasoning approach (essentially based on photos and drawings) to the possibility to explore and visualize the object in its full three-dimensional (3D) nature. Nevertheless, in the last few years both 3D modeling and 3D scanning have become a valued way to present and analyze CH artifacts. Several interesting practical applications have been made available to the publicly in museums, or virtually on the Web. Here we just cite a single sample paper [56], which deals with the problem of interactive inspection and rendering of complex 3D models; many other experiences are presented in this Chapter.Project(s): 3D-COFORM
Callieri M, Dellepiane M, Cignoni P, Scopigno R
The introduction of new technologies in the context of Cultural Heritage (CH) and Archeology has often been a difficult issue. This is probably related to the lack in confidence in replacing consolidated approaches with experimental methods heavily based on innovative hardware or software systems. This already happened for a number of revolutionary technologies: for example, the advent of photography, color images and digital cameras took some time before changing the reference methods for archival and studies in the context of archeological excavation or of restoration actions. The same considerations hold for the use of digital 3D models in CH applications. One basic issue is the need to switch from a two-dimensional visualization and reasoning approach (essentially based on photos and drawings) to the possibility to explore and visualize the object in its full three-dimensional (3D) nature. Nevertheless, in the last few years both 3D modeling and 3D scanning have become a valued way to present and analyze CH artifacts. Several interesting practical applications have been made available to the publicly in museums, or virtually on the Web. Here we just cite a single sample paper [56], which deals with the problem of interactive inspection and rendering of complex 3D models; many other experiences are presented in this Chapter.Project(s): 3D-COFORM
See at:
CNR IRIS | CNR IRIS | www.routledge.com
2011
Conference article
Restricted
Processing a complex architectural sampling with MeshLab: the case of Piazza della Signoria
Callieri M, Cignoni P, Dellepiane Ma, Ranzuglia G, Scopigno R
The paper presents a recent 3D scanning project performed with long range scanning technology showing how a complex sampled dataset can be processed with the features available in MeshLab, an open source tool. MeshLab is an open source mesh processing system. It is a portable and extensible system aimed to help the processing of the typical not-so-small unstructured models that arise in 3D scanning, providing a set of tools for editing, cleaning, processing, inspecting, rendering and converting meshes. The MeshLab system started in late 2005 as a part of a university course, and considerably evolved since then thanks to the effort of the Visual Computing Lab and of the support of several funded EC projects. MeshLab gained so far an excellent visibility and distribution, with several thousands downloads every month, and a continuous evolution. The aim of this scanning campaign was to sample the fac?ades of the buildings located in Piazza della Signoria (Florence, Italy). This digital 3D model was required, in the framework of a Regional Project, as a basic background model to present a complex set of images using a virtual navigation metaphor (following the PhotoSynth approach). Processing of complex dataset, such as the ones produced by long range scanners, often requires specialized, difficult to use and costly software packages. We show in the paper how it is possible to process this kind of data inside an open source tool, thanks to the many new features recently introduced in MeshLab for the management of large sets of sampled point.Source: THE INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES, vol. 38, pp. 205-212. Trento, 2-5 March 2011
Project(s): 3D-COFORM
Callieri M, Cignoni P, Dellepiane Ma, Ranzuglia G, Scopigno R
The paper presents a recent 3D scanning project performed with long range scanning technology showing how a complex sampled dataset can be processed with the features available in MeshLab, an open source tool. MeshLab is an open source mesh processing system. It is a portable and extensible system aimed to help the processing of the typical not-so-small unstructured models that arise in 3D scanning, providing a set of tools for editing, cleaning, processing, inspecting, rendering and converting meshes. The MeshLab system started in late 2005 as a part of a university course, and considerably evolved since then thanks to the effort of the Visual Computing Lab and of the support of several funded EC projects. MeshLab gained so far an excellent visibility and distribution, with several thousands downloads every month, and a continuous evolution. The aim of this scanning campaign was to sample the fac?ades of the buildings located in Piazza della Signoria (Florence, Italy). This digital 3D model was required, in the framework of a Regional Project, as a basic background model to present a complex set of images using a virtual navigation metaphor (following the PhotoSynth approach). Processing of complex dataset, such as the ones produced by long range scanners, often requires specialized, difficult to use and costly software packages. We show in the paper how it is possible to process this kind of data inside an open source tool, thanks to the many new features recently introduced in MeshLab for the management of large sets of sampled point.Source: THE INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES, vol. 38, pp. 205-212. Trento, 2-5 March 2011
Project(s): 3D-COFORM
See at:
CNR IRIS | CNR IRIS | www.3d-arch.org
2011
Journal article
Open Access
Image guided reconstruction of un-sampled data: a filling technique for cultural heritage models
Dellepiane M, Venturi A, Scopigno R
Cultural Heritage (CH) is one of the major fields of application of 3D scanning technologies. In this context, one of the main limitations perceived by the practitioners is the uncompleteness of the sampling. Whenever we scan a complex artifact, the produced sampling usually presents a large number of unsampled regions. Many algorithmic solutions exist to close those gaps (from specific hole-filling algorithms to the drastic solution of using water-tight reconstruction methods). Unfortunately, adding patches over un-sampled regions is an issue in CH applications: if the 3D model should be used as a master document over the shape (and status) of the artwork, informed CH curators usually do not accept that an algorithm is used to {em guess} portions of a surface. In this paper, we present a low-cost setup and related algorithms to reconstruct un-sampled portions of the 3D models by inferring information about the real shape of the missing region from photographs. Data needed to drive the surface completion process are obtained by coupling a calibrated pattern of laser diodes to a digital camera. Thus, we are proposing a simple active acquisition device (based on consumer components and more flexible than standard 3D scanning devices) to improve selectively the sampling produced by a standard 3D scanning device. After acquiring one or more images with the laser-enhanced camera, an almost completely automatic process analyzes the image/s in order to extract the pattern, to estimate the laser projector intersections over the surface and determining coordinates of those points (using the consolidated triangulation approach). Then, the gathered geometric data are used to steer the hole filling in order to obtain a patch which is coherent with the real shape of the object. A series of tests on real objects proves that our method is able to recover geometrical features that cannot be reconstructed using state-of-the-art methods. Consequently, it can be used to obtain complete 3D models without creating plausible but false data.Source: INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 94 (issue 1), pp. 2-11
DOI: 10.1007/s11263-010-0382-2
Project(s): 3D-COFORM
Metrics:
Dellepiane M, Venturi A, Scopigno R
Cultural Heritage (CH) is one of the major fields of application of 3D scanning technologies. In this context, one of the main limitations perceived by the practitioners is the uncompleteness of the sampling. Whenever we scan a complex artifact, the produced sampling usually presents a large number of unsampled regions. Many algorithmic solutions exist to close those gaps (from specific hole-filling algorithms to the drastic solution of using water-tight reconstruction methods). Unfortunately, adding patches over un-sampled regions is an issue in CH applications: if the 3D model should be used as a master document over the shape (and status) of the artwork, informed CH curators usually do not accept that an algorithm is used to {em guess} portions of a surface. In this paper, we present a low-cost setup and related algorithms to reconstruct un-sampled portions of the 3D models by inferring information about the real shape of the missing region from photographs. Data needed to drive the surface completion process are obtained by coupling a calibrated pattern of laser diodes to a digital camera. Thus, we are proposing a simple active acquisition device (based on consumer components and more flexible than standard 3D scanning devices) to improve selectively the sampling produced by a standard 3D scanning device. After acquiring one or more images with the laser-enhanced camera, an almost completely automatic process analyzes the image/s in order to extract the pattern, to estimate the laser projector intersections over the surface and determining coordinates of those points (using the consolidated triangulation approach). Then, the gathered geometric data are used to steer the hole filling in order to obtain a patch which is coherent with the real shape of the object. A series of tests on real objects proves that our method is able to recover geometrical features that cannot be reconstructed using state-of-the-art methods. Consequently, it can be used to obtain complete 3D models without creating plausible but false data.Source: INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 94 (issue 1), pp. 2-11
DOI: 10.1007/s11263-010-0382-2
Project(s): 3D-COFORM
Metrics:
See at:
International Journal of Computer Vision 
| International Journal of Computer Vision | CNR IRIS | CNR IRIS | link.springer.com
2011
Contribution to book
Restricted
Using digital 3D models for study and restoration of Cultural Heritage artifacts
Dellepiane M, Callieri M, Corsini M, Scopigno R
This Chapter describes the so-called 3D scanning pipeline (i.e., how raw sampled 3D data have to be processed to obtain a complete 3D model of a real-world object). This kind of raw data may be the result of the sampling of a real-world object by a 3D scanning device [1] or by one of the recent image-based approaches (which returns raw 3D data by processing set of images) [2] . Thanks to the improvement of the 3D scanning devices (and the development of software tools), it is now quite easy to obtain high quality, high resolution three-dimensional sampling in relatively short times. Conversely, processing this fragmented/raw data to generate a complete and usable 3D model is still a complex task, requiring the use of several algorithms and tools; the knowledge of the processing tasks and solutions required is still the realm of well-informed practitioners and it often appears as a set of obscure black boxes to most of the users. Therefore, we focus the Chapter on: (a) the geometric processing tasks that have to be applied to raw 3D scanned data to transform them into a clean and complete 3D model and, (b), how 3D scanning technology should be used for the acquisition of real artifacts. The sources of sample 3D data (i.e., the different hardware systems used in 3D scanning), are briefly presented in the following subsection. Please note that the domains of 3D scanning, geometric processing, visualization and applications to CH are too wide to provide a complete and exhaustive bibliography in a single Chapter; we decided to describe and cite here just a few, representative references to the literature. Our goal is to describe the software processing, the pitfalls of current solutions (trying to cope both with existing commercial systems and academic tools/results) and to highlight some topics of interest for future research, according to our experience and sensibility. The presentation follows in part the structure of a recently published paper on the same subject [3].Project(s): 3D-COFORM
Dellepiane M, Callieri M, Corsini M, Scopigno R
This Chapter describes the so-called 3D scanning pipeline (i.e., how raw sampled 3D data have to be processed to obtain a complete 3D model of a real-world object). This kind of raw data may be the result of the sampling of a real-world object by a 3D scanning device [1] or by one of the recent image-based approaches (which returns raw 3D data by processing set of images) [2] . Thanks to the improvement of the 3D scanning devices (and the development of software tools), it is now quite easy to obtain high quality, high resolution three-dimensional sampling in relatively short times. Conversely, processing this fragmented/raw data to generate a complete and usable 3D model is still a complex task, requiring the use of several algorithms and tools; the knowledge of the processing tasks and solutions required is still the realm of well-informed practitioners and it often appears as a set of obscure black boxes to most of the users. Therefore, we focus the Chapter on: (a) the geometric processing tasks that have to be applied to raw 3D scanned data to transform them into a clean and complete 3D model and, (b), how 3D scanning technology should be used for the acquisition of real artifacts. The sources of sample 3D data (i.e., the different hardware systems used in 3D scanning), are briefly presented in the following subsection. Please note that the domains of 3D scanning, geometric processing, visualization and applications to CH are too wide to provide a complete and exhaustive bibliography in a single Chapter; we decided to describe and cite here just a few, representative references to the literature. Our goal is to describe the software processing, the pitfalls of current solutions (trying to cope both with existing commercial systems and academic tools/results) and to highlight some topics of interest for future research, according to our experience and sensibility. The presentation follows in part the structure of a recently published paper on the same subject [3].Project(s): 3D-COFORM
See at:
CNR IRIS | CNR IRIS | www.routledge.com