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2019
Journal article
Open Access
High dynamic range point clouds for real-time relighting
Sabbadin M., Palma G., Banterle F., Boubekeur T., Cignoni P.
Acquired 3D point clouds make possible quick modeling of virtual scenes from the real world.With modern 3D capture pipelines, each point sample often comes with additional attributes such as normal vector and color response. Although rendering and processing such data has been extensively studied, little attention has been devoted using the light transport hidden in the recorded per-sample color response to relight virtual objects in visual effects (VFX) look-dev or augmented reality (AR) scenarios. Typically, standard relighting environment exploits global environment maps together with a collection of local light probes to reflect the light mood of the real scene on the virtual object. We propose instead a unified spatial approximation of the radiance and visibility relationships present in the scene, in the form of a colored point cloud. To do so, our method relies on two core components: High Dynamic Range (HDR) expansion and real-time Point-Based Global Illumination (PBGI). First, since an acquired color point cloud typically comes in Low Dynamic Range (LDR) format, we boost it using a single HDR photo exemplar of the captured scene that can cover part of it. We perform this expansion efficiently by first expanding the dynamic range of a set of renderings of the point cloud and then projecting these renderings on the original cloud. At this stage, we propagate the expansion to the regions not covered by the renderings or with low-quality dynamic range by solving a Poisson system. Then, at rendering time, we use the resulting HDR point cloud to relight virtual objects, providing a diffuse model of the indirect illumination propagated by the environment. To do so, we design a PBGI algorithm that exploits the GPU's geometry shader stage as well as a new mipmapping operator, tailored for G-buffers, to achieve real-time performances. As a result, our method can effectively relight virtual objects exhibiting diffuse and glossy physically-based materials in real time. Furthermore, it accounts for the spatial embedding of the object within the 3D environment. We evaluate our approach on manufactured scenes to assess the error introduced at every step from the perfect ground truth. We also report experiments with real captured data, covering a range of capture technologies, from active scanning to multiview stereo reconstruction.Source: Computer graphics forum (Online) 38 (2019): 513–525. doi:10.1111/cgf.13857
DOI: 10.1111/cgf.13857
Project(s): EMOTIVE
Metrics:
Sabbadin M., Palma G., Banterle F., Boubekeur T., Cignoni P.
Acquired 3D point clouds make possible quick modeling of virtual scenes from the real world.With modern 3D capture pipelines, each point sample often comes with additional attributes such as normal vector and color response. Although rendering and processing such data has been extensively studied, little attention has been devoted using the light transport hidden in the recorded per-sample color response to relight virtual objects in visual effects (VFX) look-dev or augmented reality (AR) scenarios. Typically, standard relighting environment exploits global environment maps together with a collection of local light probes to reflect the light mood of the real scene on the virtual object. We propose instead a unified spatial approximation of the radiance and visibility relationships present in the scene, in the form of a colored point cloud. To do so, our method relies on two core components: High Dynamic Range (HDR) expansion and real-time Point-Based Global Illumination (PBGI). First, since an acquired color point cloud typically comes in Low Dynamic Range (LDR) format, we boost it using a single HDR photo exemplar of the captured scene that can cover part of it. We perform this expansion efficiently by first expanding the dynamic range of a set of renderings of the point cloud and then projecting these renderings on the original cloud. At this stage, we propagate the expansion to the regions not covered by the renderings or with low-quality dynamic range by solving a Poisson system. Then, at rendering time, we use the resulting HDR point cloud to relight virtual objects, providing a diffuse model of the indirect illumination propagated by the environment. To do so, we design a PBGI algorithm that exploits the GPU's geometry shader stage as well as a new mipmapping operator, tailored for G-buffers, to achieve real-time performances. As a result, our method can effectively relight virtual objects exhibiting diffuse and glossy physically-based materials in real time. Furthermore, it accounts for the spatial embedding of the object within the 3D environment. We evaluate our approach on manufactured scenes to assess the error introduced at every step from the perfect ground truth. We also report experiments with real captured data, covering a range of capture technologies, from active scanning to multiview stereo reconstruction.Source: Computer graphics forum (Online) 38 (2019): 513–525. doi:10.1111/cgf.13857
DOI: 10.1111/cgf.13857
Project(s): EMOTIVE
Metrics:
See at:
ISTI Repository 
| diglib.eg.org 
| Computer Graphics Forum | CNR ExploRA
2018
Journal article
Open Access
Enhanced visualization of detected 3D geometric differences
Palma G., Sabbadin M., Corsini M., Cignoni P.
The wide availability of 3D acquisition devices makes viable their use for shape monitoring. The current techniques for the analysis of time-varying data can efficiently detect actual significant geometric changes and rule out differences due to irrelevant variations (such as sampling, lighting and coverage). On the other hand, the effective visualization of such detected changes can be challenging when we want to show at the same time the original appearance of the 3D model. In this paper, we propose a dynamic technique for the effective visualization of detected differences between two 3D scenes. The presented approach, while retaining the original appearance, allows the user to switch between the two models in a way that enhances the geometric differences that have been detected as significant. Additionally, the same technique is able to visually hides the other negligible, yet visible, variations. The main idea is to use two distinct screen space time-based interpolation functions for the significant 3D differences and for the small variations to hide. We have validated the proposed approach in a user study on a different class of datasets, proving the objective and subjective effectiveness of the method.Source: Computer graphics forum (Online) 35 (2018): 159–171. doi:10.1111/cgf.13239
DOI: 10.1111/cgf.13239
Project(s): HARVEST4D
Metrics:
Palma G., Sabbadin M., Corsini M., Cignoni P.
The wide availability of 3D acquisition devices makes viable their use for shape monitoring. The current techniques for the analysis of time-varying data can efficiently detect actual significant geometric changes and rule out differences due to irrelevant variations (such as sampling, lighting and coverage). On the other hand, the effective visualization of such detected changes can be challenging when we want to show at the same time the original appearance of the 3D model. In this paper, we propose a dynamic technique for the effective visualization of detected differences between two 3D scenes. The presented approach, while retaining the original appearance, allows the user to switch between the two models in a way that enhances the geometric differences that have been detected as significant. Additionally, the same technique is able to visually hides the other negligible, yet visible, variations. The main idea is to use two distinct screen space time-based interpolation functions for the significant 3D differences and for the small variations to hide. We have validated the proposed approach in a user study on a different class of datasets, proving the objective and subjective effectiveness of the method.Source: Computer graphics forum (Online) 35 (2018): 159–171. doi:10.1111/cgf.13239
DOI: 10.1111/cgf.13239
Project(s): HARVEST4D
Metrics:
See at:
ISTI Repository | Computer Graphics Forum | onlinelibrary.wiley.com | CNR ExploRA
2018
Report
Open Access
High dynamic range expansion of point clouds for real-time relighting
Sabbadin M., Palma G., Banterle F., Boubekeur T., Cignoni P.
Acquired 3D point clouds make possible quick modeling of virtual scenes from the real world. With modern 3D capture pipelines, each point sample often comes with additional attributes such as normal vector and color response. Although rendering and processing such data has been extensively studied, little attention has been devoted using the genuine light transport hidden in the recorded per-sample color response to relight virtual objects in visual effects (VFX) look-dev or augmented reality scenarios. Typically, standard relighting environment exploits global environment maps together with a collection of local light probes to reflect the light mood of the real scene on the virtual object. We propose instead a unified spatial approximation of the radiance and visibility relationships present in the scene, in the form of a colored point cloud. To do so, our method relies on two core components: High Dynamic Range (HDR) expansion and real-time Point-Based Global Illumination (PBGI). First of all, since an acquired color point cloud typically comes in Low Dynamic Range (LDR) format, we boost it using a single HDR photo exemplar of the captured scene, that may only cover part of it. We perform efficiently this expansion by first expanding the dynamic range of a set of renderings of the point cloud and then projecting these renderings on the original cloud. At this stage, we propagate the expansion to the regions which are not covered by the renderings or with low quality dynamic range by solving a Poisson's system. Then, at rendering time, we use the resulting HDR point cloud to relight virtual objects, providing a diffuse model of the indirect illumination propagated by the environment. To do so, we design a PBGI algorithm that exploits the GPU's geometry shader stage as well as a new mipmapping operator, tailored for G-buffers, to achieve real-time performances. As a result, our method can effectively relight virtual objects exhibiting diffuse and glossy physically-based materials in real time. Furthermore, it accounts for the spatial embedding of the object within the 3D environment. We evaluate our approach on manufactured scenes to assess the error introduced at every step with respect to the perfect ground truth. We also report experiments on real captured data, covering a range of capture technologies, from active scanning to multiview stereo reconstruction.Source: ISTI Technical reports, 2018
Sabbadin M., Palma G., Banterle F., Boubekeur T., Cignoni P.
Acquired 3D point clouds make possible quick modeling of virtual scenes from the real world. With modern 3D capture pipelines, each point sample often comes with additional attributes such as normal vector and color response. Although rendering and processing such data has been extensively studied, little attention has been devoted using the genuine light transport hidden in the recorded per-sample color response to relight virtual objects in visual effects (VFX) look-dev or augmented reality scenarios. Typically, standard relighting environment exploits global environment maps together with a collection of local light probes to reflect the light mood of the real scene on the virtual object. We propose instead a unified spatial approximation of the radiance and visibility relationships present in the scene, in the form of a colored point cloud. To do so, our method relies on two core components: High Dynamic Range (HDR) expansion and real-time Point-Based Global Illumination (PBGI). First of all, since an acquired color point cloud typically comes in Low Dynamic Range (LDR) format, we boost it using a single HDR photo exemplar of the captured scene, that may only cover part of it. We perform efficiently this expansion by first expanding the dynamic range of a set of renderings of the point cloud and then projecting these renderings on the original cloud. At this stage, we propagate the expansion to the regions which are not covered by the renderings or with low quality dynamic range by solving a Poisson's system. Then, at rendering time, we use the resulting HDR point cloud to relight virtual objects, providing a diffuse model of the indirect illumination propagated by the environment. To do so, we design a PBGI algorithm that exploits the GPU's geometry shader stage as well as a new mipmapping operator, tailored for G-buffers, to achieve real-time performances. As a result, our method can effectively relight virtual objects exhibiting diffuse and glossy physically-based materials in real time. Furthermore, it accounts for the spatial embedding of the object within the 3D environment. We evaluate our approach on manufactured scenes to assess the error introduced at every step with respect to the perfect ground truth. We also report experiments on real captured data, covering a range of capture technologies, from active scanning to multiview stereo reconstruction.Source: ISTI Technical reports, 2018
See at:
ISTI Repository | CNR ExploRA