Airborne photogrammetry and LIDAR for DSM extraction and 3D change detection over an urban area : a comparative study

A digital surface model (DSM) extracted from stereoscopic aerial images, acquired in March 2000, is compared with a DSM derived from airborne light detection and ranging (lidar) data collected in July 2009. Three densely built-up study areas in the city centre of Ghent, Belgium, are selected, each covering approximately 0.4 km(2). The surface models, generated from the two different 3D acquisition methods, are compared qualitatively and quantitatively as to what extent they are suitable in modelling an urban environment, in particular for the 3D reconstruction of buildings. Then the data sets, which are acquired at two different epochs t(1) and t(2), are investigated as to what extent 3D (building) changes can be detected and modelled over the time interval. A difference model, generated by pixel-wise subtracting of both DSMs, indicates changes in elevation. Filters are proposed to differentiate 'real' building changes from false alarms provoked by model noise, outliers, vegetation, etc. A final 3D building change model maps all destructed and newly constructed buildings within the time interval t(2) - t(1). Based on the change model, the surface and volume of the building changes can be quantified

Quality Index for Stereoscopic Images by Separately Evaluating Adding and Subtracting

The human visual system (HVS) plays an important role in stereo image quality perception. Therefore, it has aroused many people’s interest in how to take advantage of the knowledge of the visual perception in image quality assessment models. This paper proposes a full-reference metric for quality assessment of stereoscopic images based on the binocular difference channel and binocular summation channel. For a stereo pair, the binocular summation map and binocular difference map are computed first by adding and subtracting the left image and right image. Then the binocular summation is decoupled into two parts, namely additive impairments and detail losses. The quality of binocular summation is obtained as the adaptive combination of the quality of detail losses and additive impairments. The quality of binocular summation is computed by using the Contrast Sensitivity Function (CSF) and weighted multi-scale (MS-SSIM). Finally, the quality of binocular summation and binocular difference is integrated into an overall quality index. The experimental results indicate that compared with existing metrics, the proposed metric is highly consistent with the subjective quality assessment and is a robust measure. The result have also indirectly proved hypothesis of the existence of binocular summation and binocular difference channels

Particle Detection Algorithms for Complex Plasmas

In complex plasmas, the behavior of freely floating micrometer sized particles is studied. The particles can be directly visualized and recorded by digital video cameras. To analyze the dynamics of single particles, reliable algorithms are required to accurately determine their positions to sub-pixel accuracy from the recorded images. Typically, straightforward algorithms are used for this task. Here, we combine the algorithms with common techniques for image processing. We study several algorithms and pre- and post-processing methods, and we investigate the impact of the choice of threshold parameters, including an automatic threshold detection. The results quantitatively show that each algorithm and method has its own advantage, often depending on the problem at hand. This knowledge is applicable not only to complex plasmas, but useful for any kind of comparable image-based particle tracking, e.g. in the field of colloids or granular matter

Rock fractures analysis using Structure from Motion technology: new insight from Digital Outcrop Models

Fractures are one of the most important features of the rocks of the upper crust since they strongly influence their physical and chemical behavior and reflect their tectonic history. For this reason, fracture study plays a key role in different branches of the geosciences. Notwithstanding, the quantification of the features and parameters describing fractures could be unsatisfactory using the standard field techniques because they are mainly based on direct-contact methodologies that are affected by errors, as orientation bias and trace censoring, and scarce representativeness, due to the limited possibility of acquiring information of outcrops partially or totally inaccessible. Recently new remote sensing technologies, such as Terrestrial Laser Scanner (TLS) and Digital Photogrammetry (DP), can help to overcome these limitations. Whereas TLS could be very expensive and difficult to use in geological study, DP permits to obtain similar results in an easier way due to cheaper and lighter equipment and more straightforward procedures. Moreover, DP becomes even more useful when combined with Unmanned Aerial Vehicle (UAV) because permits to acquire digital images from positions inaccessible to humans, allowing to analyze geological objects from points of view previously unimaginable. The images acquired from the ground and/or by the UAV can be then processed using different digital algorithms, such as Structure from Motion (SfM), that permit to create 3D model of the studied outcrop. In geosciences, the 3D model representing the surface of the outcrop is often called Digital Outcrop Model (DOM). Despite DOMs can be really useful in different branches of geosciences, their applications are quite well limited because the procedures of their development and sampling/analysis are scarcely analyzed in literature. It is important to highlight that whereas the UAV-based SfM approach is fairly discussed in literature for simple flat areas, is scarcely treated for application to near vertical and not-planar slopes. Moreover, the validity of some procedures of fracture sampling on 3D model, with special regards to the automatic ones, that have been recently presented in literature, is not well treated for real cases of study. The scarce knowledge about these approaches could cause different troubles to the scientific-users: from the application of avoidable time-consuming routine, to the acquisition and interpretation of erroneous data. This research aims to contribute to the scientific knowledge of the use of digital photogrammetry for fractured rock mass analysis, creating and defining new approaches and procedures for the development, analysis and application of DOMs. Here, a workflow for the fracture analysis of steep rocky outcrops and slopes using the 3D DOM is presented. In particular, the following steps are discussed: (i) image acquisition; (ii) development of 3D model; (iii) sampling of DOM; (iv) quantification and parametrization of the 3D measures; (v) application of the 3D quantitative data and parameters to different case of study. Four different cases of study were selected to validate the proposed method: the upper Staffora Valley and Ponte Organasco (Northern Apennines, Italy), Ormea (Ligurian Alps, Italy), and Gallivaggio (Western Alps, Italy) cases of study. However, this methodology could not completely replace the 'direct-contact' field activity, because some information as roughness, infilling and aperture of fractures cannot be measured satisfactory, and because, where possible, field control measures to validate the 3D data are necessary. However, this methodology could be considered as a new necessary procedure for rock-fracture studies because it allows to overcome the inevitable errors of the ground-based traditional methodology and because the DOMs are always available for the analysis, promoting data sharing and comparison, two fundamental principles on which science have and will have to be basedFractures are one of the most important features of the rocks of the upper crust since they strongly influence their physical and chemical behavior and reflect their tectonic history. For this reason, fracture study plays a key role in different branches of the geosciences. Notwithstanding, the quantification of the features and parameters describing fractures could be unsatisfactory using the standard field techniques because they are mainly based on direct-contact methodologies that are affected by errors, as orientation bias and trace censoring, and scarce representativeness, due to the limited possibility of acquiring information of outcrops partially or totally inaccessible. Recently new remote sensing technologies, such as Terrestrial Laser Scanner (TLS) and Digital Photogrammetry (DP), can help to overcome these limitations. Whereas TLS could be very expensive and difficult to use in geological study, DP permits to obtain similar results in an easier way due to cheaper and lighter equipment and more straightforward procedures. Moreover, DP becomes even more useful when combined with Unmanned Aerial Vehicle (UAV) because permits to acquire digital images from positions inaccessible to humans, allowing to analyze geological objects from points of view previously unimaginable. The images acquired from the ground and/or by the UAV can be then processed using different digital algorithms, such as Structure from Motion (SfM), that permit to create 3D model of the studied outcrop. In geosciences, the 3D model representing the surface of the outcrop is often called Digital Outcrop Model (DOM). Despite DOMs can be really useful in different branches of geosciences, their applications are quite well limited because the procedures of their development and sampling/analysis are scarcely analyzed in literature. It is important to highlight that whereas the UAV-based SfM approach is fairly discussed in literature for simple flat areas, is scarcely treated for application to near vertical and not-planar slopes. Moreover, the validity of some procedures of fracture sampling on 3D model, with special regards to the automatic ones, that have been recently presented in literature, is not well treated for real cases of study. The scarce knowledge about these approaches could cause different troubles to the scientific-users: from the application of avoidable time-consuming routine, to the acquisition and interpretation of erroneous data. This research aims to contribute to the scientific knowledge of the use of digital photogrammetry for fractured rock mass analysis, creating and defining new approaches and procedures for the development, analysis and application of DOMs. Here, a workflow for the fracture analysis of steep rocky outcrops and slopes using the 3D DOM is presented. In particular, the following steps are discussed: (i) image acquisition; (ii) development of 3D model; (iii) sampling of DOM; (iv) quantification and parametrization of the 3D measures; (v) application of the 3D quantitative data and parameters to different case of study. Four different cases of study were selected to validate the proposed method: the upper Staffora Valley and Ponte Organasco (Northern Apennines, Italy), Ormea (Ligurian Alps, Italy), and Gallivaggio (Western Alps, Italy) cases of study. However, this methodology could not completely replace the 'direct-contact' field activity, because some information as roughness, infilling and aperture of fractures cannot be measured satisfactory, and because, where possible, field control measures to validate the 3D data are necessary. However, this methodology could be considered as a new necessary procedure for rock-fracture studies because it allows to overcome the inevitable errors of the ground-based traditional methodology and because the DOMs are always available for the analysis, promoting data sharing and comparison, two fundamental principles on which science have and will have to be base

Efficient Distance Accuracy Estimation Of Real-World Environments In Virtual Reality Head-Mounted Displays

Virtual reality (VR) is a very promising technology with many compelling industrial applications. As many advancements have been made recently to deploy and use VR technology in virtual environments, they are still less mature to be used to render real environments. The current VR systems settings, which are developed for virtual environments rendering, fail to adequately address the challenges of capturing and displaying real-world virtual reality that these systems entail. Before these systems can be used in real life settings, their performance needs to be investigated, more specifically, depth perception and how distances to objects in the rendered scenes are estimated. The perceived depth is influenced by Head Mounted Displays (HMD) that inevitability decrease the virtual content’s depth perception. Distances are consistently underestimated in virtual environments (VEs) compared to the real world. The reason behind this underestimation is still not understood. This thesis investigates another version of this kind of system, that to the best of authors knowledge has not been explored by any previous research. Previous research used a computer-generated scene. This work is examining distance estimation in real environments rendered to Head-Mounted Displays, where distance estimations is among the most challenging issues that are still investigated and not fully understood.This thesis introduces a dual-camera video feed system through a virtual reality head mounted display with two models: a video-based and a static photo-based model, in which, the purpose is to explore whether the misjudgment of distances in HMDs could be due to a lack of realism, or not, with the use of a real-world scene rendering system. Distance judgments performance in the real world and these two evaluated VE models were compared using protocols already proven to accurately measure real-world distance estimations. An improved model based on enhancing the field of view (FOV) of the displayed scenes to improve distance judgements when displaying real-world VR content to HMDs was developed; allowing to mitigate the limited FOV, which is among the first potential causes of distance underestimation, specially, the mismatch of FOV between the camera and the HMD field of views. The proposed model is using a set of two cameras to generate the video instead of hundreds of input cameras or tens of cameras mounted on a circular rig as previous works from the literature. First Results from the first implementation of this system found that when the model was rendered as static photo-based, the underestimation was less as compared with the live video feed rendering. The video-based (real + HMD) model and the static photo-based (real + photo + HMD) model averaged 80.2% of the actual distance, and 81.4% respectively compared to the Real-World estimations that averaged 92.4%. The improved developed approach (Real + HMD + FOV) was compared to these two models and showed an improvement of 11%, increasing the estimation accuracy from 80% to 91% and reducing the estimation error from 1.29% to 0.56%. This thesis results present strong evidence of the need for novel distance estimation improvements methods for real world VR content systems and provides effective initial work towards this goal