A parallel algorithm for Delaunay triangulation of moving points on the plane

Delaunay Triangulation(DT) is one of the important geometric problems that is used in various branches of knowledge such as computer vision, terrain modeling, spatial clustering and networking. Kinetic data structures have become very important in computational geometry for dealing with moving objects. However, when dealing with moving points, maintaining a dynamically changing Delaunay triangulation can be challenging. So, In this case, we have to update triangulation repeatedly. If points move so far, it is better to rebuild the triangulation. One approach to handle moving points is to use an incremental algorithm. For the case that points move slowly, we can give a faster algorithm than rebuilding it. Furthermore, sequential algorithms can be computationally expensive for large datasets. So, one way to compute as fast as possible is parallelism. In this paper, we propose a parallel algorithm for moving points. we propose an algorithm that divides datasets into equal partitions and give every partition to one block. Each block satisfay the Delaunay constraints after each time step and uses delete and insert algorithms to do this. We show this algorithm works faster than serial algorithms

Delaunay Tessellations and Voronoi Diagrams in CGAL

The Cgal library provides a rich variety of Voronoi diagrams and Delaunay triangulations. This variety covers several aspects: generators, dimensions and metrics, which we describe in Section 2. One aim of this paper is to present the main paradigms used in CGAL: Generic programming, separation between predicates/constructions and combinatorics, and exact geometric computation (not to be confused with exact arithmetic!). The first two paradigms translate into software design choices, described in Section 4, while the last covers both robustness and efficiency issues, respectively described in Sec- tion 6 and 7. Other important aspects of the Cgal library are the interface issues, be they for traversing a tessellation, or for interoperability with other libraries or languages, see Section 5. We present in Section 8 some tessellations at work in the context of surface reconstruction and mesh generation. Section 9 is devoted to some on-going and future work on periodic triangulations (triangulations in periodic spaces), and on high-quality mesh generation with optimized tessellations. Section 10 provides typical numbers in terms of efficiency and scalability for constructing tessellations, and lists the remaining weaknesses. We conclude by listing some of our directions for the future

Seismic wave propagation in Iran and eastern Indian shield

This dissertation addresses several important aspects of observational earthquake seismology: 1) methods for data management and processing large datasets, 2) analysis of seismic wave propagation at local to regional (up to about 700 km) source-receiver distances, 3) analysis of seismic coda, and 4) critical re-evaluation of the fundamental problem of seismic wave attenuation and measurement of the seismic “quality” factor (Q). These studies are carried out using new and previously analyzed earthquake data from Iran. In each of the four application areas above, innovative methods are used and significant new results are obtained. First, for efficient managing and processing of large earthquake datasets, I use a flexible, exploration-style open-source seismic processing system. Custom and problem-oriented scripts using Matlab or Octave software are included as tools in this processing system, allowing interactive and non-interactive analysis of earthquake records. In the second application, I note that the existing models for body-wave amplitudes are hampered by several difficulties, such as inaccurate accounts for the contributions of source and receiver effects and insufficient accuracy at the transition between the local and regional distances. Finding a reliable model for body-wave amplitudes is critical for many studies. To achieve such a reliable model, I use a joint inversion method based on a new parameterization of seismic attenuation and additional constraints on model quality. The joint inversion provides a correct model for geometrical spreading and attenuation. The geometrical-spreading model reveals the existence of an increase of body S wave amplitudes from 90 to about 115 km from the source which might be caused by waves reflecting from the crust‐mantle boundary. Outside of this distance range, amplitude decays are significantly faster than usually assumed in similar models. Third, in two chapters of this dissertation devoted to coda studies, I consider the concept of the frequency-dependent coda Q (Qc). Although this quantity is usually attributed to the subsurface, I argue that because of subjective selections of model assumptions and algorithms, Qc cannot be rigorously viewed as a function of surface or subsurface points. Also, frequency dependence of the measured Qc strongly trades off with the subjectively selected parameters of the measurement procedure. To mitigate these problems, instead of mapping a hypothetical in-situ Qc, I obtain maps of physically justified parameters of the subsurface: exponents of geometrical spreading (denoted ) and effective attenuation (denoted qe). For the areas of this study, parameter ranges from 0.005 s-1 to 0.05 s-1 (within Zagros area of Iran) and 0.010 s-1 to 0.013 s-1 (within the eastern Indian Shield). Finally, from both body- and coda-wave studies, I derive estimates of seismic attenuation within the study areas. In two areas of Iran and within the Indian Shield, weak attenuation with Q-factors of 2000–6000 or higher is found. In particular, coda envelopes can be explained by wave reverberations within elastic crustal structures, and the Q-type attenuation appears undetectable

Scene Reconstruction from Multi-Scale Input Data

Geometry acquisition of real-world objects by means of 3D scanning or stereo reconstruction constitutes a very important and challenging problem in computer vision. 3D scanners and stereo algorithms usually provide geometry from one viewpoint only, and several of the these scans need to be merged into one consistent representation. Scanner data generally has lower noise levels than stereo methods and the scanning scenario is more controlled. In image-based stereo approaches, the aim is to reconstruct the 3D surface of an object solely from multiple photos of the object. In many cases, the stereo geometry is contaminated with noise and outliers, and exhibits large variations in scale. Approaches that fuse such data into one consistent surface must be resilient to such imperfections. In this thesis, we take a closer look at geometry reconstruction using both scanner data and the more challenging image-based scene reconstruction approaches. In particular, this work focuses on the uncontrolled setting where the input images are not constrained, may be taken with different camera models, under different lighting and weather conditions, and from vastly different points of view. A typical dataset contains many views that observe the scene from an overview perspective, and relatively few views capture small details of the geometry. What results from these datasets are surface samples of the scene with vastly different resolution. As we will show in this thesis, the multi-resolution, or, "multi-scale" nature of the input is a relevant aspect for surface reconstruction, which has rarely been considered in literature yet. Integrating scale as additional information in the reconstruction process can make a substantial difference in surface quality. We develop and study two different approaches for surface reconstruction that are able to cope with the challenges resulting from uncontrolled images. The first approach implements surface reconstruction by fusion of depth maps using a multi-scale hierarchical signed distance function. The hierarchical representation allows fusion of multi-resolution depth maps without mixing geometric information at incompatible scales, which preserves detail in high-resolution regions. An incomplete octree is constructed by incrementally adding triangulated depth maps to the hierarchy, which leads to scattered samples of the multi-resolution signed distance function. A continuous representation of the scattered data is defined by constructing a tetrahedral complex, and a final, highly-adaptive surface is extracted by applying the Marching Tetrahedra algorithm. A second, point-based approach is based on a more abstract, multi-scale implicit function defined as a sum of basis functions. Each input sample contributes a single basis function which is parameterized solely by the sample's attributes, effectively yielding a parameter-free method. Because the scale of each sample controls the size of the basis function, the method automatically adapts to data redundancy for noise reduction and is highly resilient to the quality-degrading effects of low-resolution samples, thus favoring high-resolution surfaces. Furthermore, we present a robust, image-based reconstruction system for surface modeling: MVE, the Multi-View Environment. The implementation provides all steps involved in the pipeline: Calibration and registration of the input images, dense geometry reconstruction by means of stereo, a surface reconstruction step and post-processing, such as remeshing and texturing. In contrast to other software solutions for image-based reconstruction, MVE handles large, uncontrolled, multi-scale datasets as well as input from more controlled capture scenarios. The reason lies in the particular choice of the multi-view stereo and surface reconstruction algorithms. The resulting surfaces are represented using a triangular mesh, which is a piecewise linear approximation to the real surface. The individual triangles are often so small that they barely contribute any geometric information and can be ill-shaped, which can cause numerical problems. A surface remeshing approach is introduced which changes the surface discretization such that more favorable triangles are created. It distributes the vertices of the mesh according to a density function, which is derived from the curvature of the geometry. Such a mesh is better suited for further processing and has reduced storage requirements. We thoroughly compare the developed methods against the state-of-the art and also perform a qualitative evaluation of the two surface reconstruction methods on a wide range of datasets with different properties. The usefulness of the remeshing approach is demonstrated on both scanner and multi-view stereo data

A multi-scale study on the movement ecology of Afrotropical waterbirds

Understanding the processes and mechanisms governing animal movement is a fundamental goal in ecology. Processes driving movement can occur across multiple spatiotemporal scales and have important consequences for the structure and dynamics of populations, communities and ecosystems. The study of movement provides insights into the ecological resources and habitats necessary for persistence of species and communities. It also provides a theoretical and applied basis from which to formulate informed conservation plans. Waterbirds in semiarid southern Africa are an ideal study group for understanding interactions between movement and environmental factors because they exhibit a wide range of movement strategies and are located within a landscape in which resources are characterised by high levels of spatiotemporal variability. Emphasis has been placed on understanding movement phenomena from individually-tracked animals, but cases which consider this approach in conjunction with traditional community ecology perspectives are rare. In this thesis I explored questions of movement in both individuals and communities, and argue that an integrated multi-scale approach is necessary to advance our broader understanding of movement in waterbirds. In the first part of the study I addressed an individual-level movement perspective. I used fine-scale telemetry data from 35 individually tracked Egyptian Geese Alopochenaegyptiaca and Red-billed Teal Anas erythrorhyncha with novel analytical techniques to explore questions of trade-offs in habitat selection, functional responses and whether movement responses to landscape resources are reactive or prescient. My findings suggested that, at the home-range scale, both forage optimisation and predation risk were limiting factors of movement and habitat selection of Egyptian Geese. I also showed for the first time that waterbirds exhibit functional responses in relation to changes in the availability of habitat types. I subsequently showed that the proximate drivers of waterfowl movement are the dynamics of rainfall and primary productivity. Egyptian Geese and Red-billed Teal were able to perceive and respond to temporal shifts in resource conditions prior to habitat patch occupation. This in turn suggested that their movements in semi-arid landscapes are underpinned by an intimate knowledge of the local environment and that waterfowl exhibit a complex behavioural movement strategy. In the second part of the study I used waterbird count data collected from wetlands in KwaZulu-Natal, South Africa, to address the community-level movement perspective

Exploiting Spatio-Temporal Coherence for Video Object Detection in Robotics

This paper proposes a method to enhance video object detection for indoor environments in robotics. Concretely, it exploits knowledge about the camera motion between frames to propagate previously detected objects to successive frames. The proposal is rooted in the concepts of planar homography to propose regions of interest where to find objects, and recursive Bayesian filtering to integrate observations over time. The proposal is evaluated on six virtual, indoor environments, accounting for the detection of nine object classes over a total of ∼ 7k frames. Results show that our proposal improves the recall and the F1-score by a factor of 1.41 and 1.27, respectively, as well as it achieves a significant reduction of the object categorization entropy (58.8%) when compared to a two-stage video object detection method used as baseline, at the cost of small time overheads (120 ms) and precision loss (0.92).</p

Geophysics for Mineral Exploration

This Special Issue contains ten papers which focus on emerging geophysical techniques for mineral exploration, novel modeling, and interpretation methods, including joint inversions of multi physics data, and challenging case studies. The papers cover a wide range of mineral deposits, including banded iron formations, epithermal gold–silver–copper–iron–molybdenum deposits, iron-oxide–copper–gold deposits, and prospecting forgroundwater resources

Temporal Variation in Space and Resource Use of Macaws in the Southeastern Peruvian Amazon

Space use and resource use of three species of macaws (Ara ararauna, A. chloropterus, and A. macao) were studied for a period of three years in the southeastern Peruvian Amazon. Basic information on wild macaw populations is lacking due to the logistical and behavioral challenges of working with these species in dense rainforest. Population declines world-wide have been attributed significantly to a reduction in food and nesting resources due to habitat loss. This research aims to obtain baseline data on macaws in a region with relatively intact rainforest. Specific objectives were to (1) quantify space use, describe the spatial and temporal variation in movement patterns, explore habitat selection and spatial pattern of resources during the non-breeding season, and (2) identify key nesting and foraging species and determine whether there is seasonal variation in diet, and explore how resources may be related to movements and competition. Individuals from each species were radio-tagged and monitored from 2004 to 2008 by ground, platform, and aerial tracking. Seasonal ranges were estimated using MCP and KDE methods. Diversity and niche measurements and selection were calculated for dietary items, nesting substrate, and habitat. The relationship between palm habitat distribution and A. ararauna movements was explored using landscape analysis techniques. All species had similar home range sizes during the breeding season, ranging from a mean of 1,540 ha to 2,541 ha. Non-breeding ranges were significantly larger for A. ararauna (117,849 ha). Greater than 200 species of plants were consumed, yet seasonal preferences vary. The increase in dietary breadth and decrease in overlap during dry season is unlikely related to food scarcity or competition. Key nesting and dietary species include Mauritia flexuosa, Dipterix micrantha, and Bertholletia excelsa. Palm habitat is a key resource for Ara ararauna and associated with long-distance movements. This research addresses a critical gap in our knowledge regarding macaw movements and resource use in Amazonian rainforest. Despite their mobility, their low fecundity and specialized nesting requirements can impact reproductive success and population growth if habitat loss continues on its current trajectory