1,720,964 research outputs found
Indoor localisation based on point clouds of the ceiling: Syntheses Project 2019
No full textIndoor localisation is a highly relevant topic. It can be used for many applications,such as indoor navigation. Current indoor localisation approaches all have certaindownsides. In this report, the results of a completely new indoor localisation approach are described. The aim of this approach is to perform indoor localisation on room level based on a fingerprint solution using point clouds of the ceilings. The ceiling is used, because the ceiling does generally not change much and therefore it is easier to keep an up-to-date database. This research considers both the use of Dense Image Matching (DIM) input from pictures or videos made with a mobile phone and Light Detection And Ranging (LiDAR) input.Geomatic
Direct Analysis on Point Clouds: Geomatics Syntesis Project 2019
No full textWith the rapid growth in point cloud acquisition technologies the recent years we have the ability to measure large quantities of 3D points of significantly detailed and geometrically composite scenes such as urban environments. This advantage can be exploited and used for direct analysis on point clouds. A direct point cloud analysis has several advantages over for example 3D surface reconstruction, such as the end result having more details and the computation being less expensive. In order to make a point cloud representation a suitable alternative for other types of 3D city models, they need to be semantically enriched, resulting in a rich point cloud. One element of this enrichment is the detection of objects, such as windows. Extracting these from facades is specifically what this research revolves around, which can be done by taking advantage of the fact that they show up as holes, since lasers of the point cloud scanner do not properly reflect on them. Two different general approaches are taken to detect windows in a by mobile laser scanner obtained point cloud of Noordereiland, Rotterdam, The Netherlands.Geomatic
Improving vario-scale implementation based on needs of Kadaster topographic data users
No full textVario-scale is a new mapping technique which automatically generalizes maps from a baselayer of faces. Applications of vario-scale are continuous, smooth zoom in web maps,multi-scale representation in one map and being able to generate maps at arbitrary scale. Also,this would only require having to maintain the dataset at the highest scale level, since all otherscales are derived from it.Potentially, vario-scale could be an alternative for current web maps and generalizationalgorithms. The Dutch national mapping agency, Kadaster, currently employs its owngeneralization process. However, they would like to know whether the users of theirtopographic datasets are interested in vario-scale. At this moment, there is a workingimplementation of vario scale (made by dr. ir. Martijn Meijers). This implementation,however, is still lacking in, for example, cartographic quality. Therefore the research questionin this project is: how can the implementation of vario-scale be improved to better meet theneeds for end users of Kadaster topographic data?This question is answered by questioning surveying users of Kadaster data on what theywould like to see improved about the existing implementation. Combining this with anexploration of the current software leads to an attempt at improving the currentimplementation. The project goal is set as enabling the road network visualization and mobilemap adaptation. Road network visualization is achieved by building the roads space scalecube and overlay with the background area at the front-end. Mobile map adaptation is realizedby creating the touch screen interaction between the device and the user. Finally, a validationsurvey is conducted to examine the difference between the original vario scaleimplementation and the adapted one.Synthesis Project 2018Geomatic
Cyclist Route Choice Modeling: A research on influence of Openness & Monotony on cyclist route choice
No full textIn previous studies on cyclist route choice, many influencing factors have been identified. Openness of the built environment, which can be described as the extent of open space above and around a specific point, has no yet been related to cyclist travel behaviour. Monotony of the built environment, described as the extent of visual variation of elements that form the built environment for a sequence of locations, has been related to transportation problems but not to cyclist route choice in particular. This research seeks to bridge this gap in existing literature by determining the effect of the openness and monotony of the built environment on cyclist route choice in the Province of Noord-Brabant. The openness value for a specific route has been modeled by accounting for the building heights and distance to a building for a sequence of locations. Applying a linear regression analysis with the openness and monotony model as input shows that openness of the built environment has a negative influence on the amount of distance people are willing to diverge from the shortest path, while on the other hand, cyclists prefer to use roads with higher variation in the built environment. However, the results show that the proportional influence of both factors can be considered as low.Synthesis Project 2018Geomatic
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Utilizing a Discrete Global Grid System For Handling Point Clouds With Varying Locations, Times, and Levels of Detail
No full textDiscrete Global Grid Systems (DGGS) have emerged in recent years as a new specification for working with global heterogeneous datasets of different types, such as vector, raster, and quantitative datasets. There exists no research on using point clouds with a DGGS. This research aims to analyse the extent to which a DGGS can be used to handle LIDAR point clouds having varying coordinate systems, acquired at different levels of detail, and at different times in the creation of a global ‘map’ of point clouds. Various ways of mapping and modelling the Earth, indexing strategies for creating a continuous index of the surface of the Earth (including what is above and below it), performing analysis of 2D, 3D or 4D point clouds using DGGS, and the querying and visualization of massive point clouds is discussed. A DGGS is compared and contrasted with conventional coordinate systems. The advantages, opportunities, challenges, and limitations of point cloud integration in a DGGS are presented.Geomatic
A graph-matching approach to indoor localization: using a mobile device and a reference BIM
No full textIndoor localization provides for a much researched subject, as the complexity and size of many public buildings require extensive and properly designed methods to facilitate location specific processes. Indoor localization entails finding a qualitative description of the occupied area, that is human interpretable, rather than a quantitative position in Euclidean space. In other words, the context of an indoor environment has to be understood, such that a position can be transcended to a meaningful location. A space is defined as a mathematical structure with relational properties, to which all its members adhere. As a subset of space, topological space describes the relationships between (parts of) objects that do not change under continuous transformation. It further defines metric space, as a set where distances and angles between all of its elements are defined. Indoor space is then interpreted as a structure bounded by physical or functional elements, enabling human activities. It should entail the geometric place an actor is in, the topological structure that place is a part of, and the semantics giving the place meaning. Many indoor positioning methods have been developed, which can provide an actor with a relative geometric place. Most preferred are positioning systems not relying on a contingent system, which can be performed using a hybrid fusion of sensors embedded into a mobile device. Such a system found to perform sufficiently is VI-SLAM, simultaneously building a geometric place and tracking each pose and heading relatively. Its output is a mesh model, in which a viewshed of the indoor environment is built. From a mesh model, a topological structure can be derived in the form of its dual graph. Now to finalize this representation of indoor space which can be captured using a mobile device, it has to be enriched with a meaningful context. These semantics are generally stored in BIM models. Thus to transcend the position retrieved using SLAM to a location, is has to be matched with a BIM model, so that the appertaining semantics can be connected.The method proposed provides for a possibility to perform graph-based indoor localization, by extracting a graph from both input sources and comparing them, in order to find a match. However different in nature and structure, both input sources can be converted to a graph of similar calibre, such that they can be tested for a match. All operations performed on the graphs are derived from spectral graph theory. The graph simplification and analysis is performed using the eigen spectrum of the graph Laplacian, and the match is performed by remapping the spectral graphs into a vector sub space using the eigen spectrum of the data covariance matrix. After a match between both graphs is found, the current position of the actor within the mesh model can be translated to the room found in the graph. This room is now connected to a room within the reference graph, for which the semantics are stored in the BIM. Returning these to the actor, a location description is formed.Geomatic
Placement optimization of Positioning Nodes: Maximizing the distinction of Indoor Zones
No full textThe performance of an Indoor Positioning System is highly related to the placement of the transmitting nodes that are used as references for the positioning estimations. Within this graduation project, we propose a methodology that can be used to optimize such a deployment and thus, increase the performance of an Indoor Positioning System that a) is based on Received Signal Strength Fingerprinting and b) is orientated towards providing location or zone estimations instead of exact positioning. The optimization process involves 4 fundamental components. Firstly, the modeling of the obstructions in the indoor environment and also the zone modeling. Then, the definition of the performance metric that can be used to evaluate each different deployment scenario, in which case, our proposed metric considers the separation area and distances between the zones in the RSS vector space. The third component is the radio propagation model, required for simulating the transmitted signals from each node, where a model based on the ray tracing technique is selected. Finally, the last component is the selection of the optimization function that will control and drive the whole optimization process by choosing which deployment schemes to evaluate. For that, the utilization of a Genetic Algorithm has been selected. The evaluation of our methodology showed that the most problematic regions in terms of localization accuracy are, as expected, those where different zones become adjacent. Yet, comparisons between regular node deployments and our optimized solutions indicated that, regardless the number of nodes, our optimization introduced in each case an overall localization improvement that was especially concentrated at the most problematic regions.Geomatic
Exploring a pure landmark-based approach for indoor localisation
No full textHumans interact more and more with their environment through technology, recent decades have seen a huge increase in the need for and availability of Location-Based Services (LBS). Recently landmarks have gotten a renewed interest in the field of LBS , although already a quite old phenomenon. In both the outdoor and indoor environment they are being used to enrich existing services such as navigation, but not used as the basis for a technique or service.The indoor environment relies heavily on building specific and less-scalable sensor-based localisation techniques (such as Wi-Fi and Bluetooth), alternatives to sensor-based are becoming a necessity and would be a welcome addition. The exploration and development of landmark-based approaches for indoor localisation is something that can extend the field of geomatics and \ac{lbs}.This research investigates if a pure landmark-based approach works for indoor localisation and which characteristics of landmarks can be exploited. This is achieved by developing a conceptual framework that explores how a landmark-based indoor localisation would work from an artificial point of view. A Minimal Viable Product (MVP) is implemented to evaluate if a landmark-based approach works and what needs to be improved or considered in future studiesStarting from an artificial test case, the MVP to achieve indoor localisation is implementing and evaluated using a manually digitised real-world and more complex test case. The fundamental principle of landmark-based localisation is that through the observation of landmarks within the (indoor) environment a user’s location is obtained because the visibility and location of landmarks are known. The workflow to go from an observation to a location is by 1) calculating the visibility/isovist area of each landmark, 2) interpret the observations into a combination of landmarks, 3) intersect the visibility of all landmarks in the observation, 4) refine the location based on relative landmark constellations, and 5) follow-up with questions on potentially visible landmarks to improve location furtherOne of the key giveaways of this research is that approach for indoor localisation a landmark-based is feasible, principles and techniques exist (or are being developed), it is only a matter of setting them up in the right order and format them to work, and connect input with the researched process and use them for LBS driven applications.Future work on the subject of landmark-based localisation and LBS is connecting with existing spatial standards, extend the principles into the 3rd dimension, and integrate more aspects of landmark salience.Geomatic
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