Showing papers in "ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences in 2013"

Feature relevance assessment for the semantic interpretation of 3D point cloud data

Abstract: The automatic analysis of large 3D point clouds represents a crucial task in photogrammetry, remote sensing and computer vision. In this paper, we propose a new methodology for the semantic interpretation of such point clouds which involves feature relevance assessment in order to reduce both processing time and memory consumption. Given a standard benchmark dataset with 1.3 million 3D points, we first extract a set of 21 geometric 3D and 2D features. Subsequently, we apply a classifier-independent ranking procedure which involves a general relevance metric in order to derive compact and robust subsets of versatile features which are generally applicable for a large variety of subsequent tasks. This metric is based on 7 different feature selection strategies and thus addresses different intrinsic properties of the given data. For the example of semantically interpreting 3D point cloud data, we demonstrate the great potential of smaller subsets consisting of only the most relevant features with 4 different state-of-the-art classifiers. The results reveal that, instead of including as many features as possible in order to compensate for lack of knowledge, a crucial task such as scene interpretation can be carried out with only few versatile features and even improved accuracy.

Hbim for conservation and management of built heritage: towards a library of vaults and wooden bean floors

Abstract: The paper illustrates the utility to switch from a 3D content model to a Historic Building Information Modelling (HBIM) in order to support conservation and management of built heritage. This three dimensional solution is based on simplified parametric models, suitable for industrial elements and modern architecture, that can be usefully applied to heritage documentation and management of the data on conservation practices. In this sense, the potentials in starting the definition of an HBIM targeted library are investigated, towards the logic of object data definition, beginning from surface surveying and representation. In order to motivate the opportunity in using this 3D object modelling instruments, some case studies are investigated in the paper. Vault and wooden bean floor analysis show how a HBIM for architectural heritage could be implemented in order to assemble different kind of data on historical buildings, such as e.g. dimensional, geometrical, thematic, historical and architectural information.

City-Wide Total Energy Demand Estimation of Buildings using Semantic 3D City Models and Statistical Data

Abstract: . The present climate and environmental policy efforts require comprehensive planning regarding the modification of the energy supply and infrastructures in cities. The strategic planning of the different measures requires a holistic approach and the combination of extensive and complex information. Within this paper, current developments in the context of the project Energy Atlas Berlin are presented. The Energy Atlas Berlin is based on the semantic information model of CityGML and provides an integrative data backbone for the common spatio-semantic representation of the city structure including energy related information of different themes. The virtual 3D city model of Berlin (mainly LOD2 building models) is used as data basis and has been enriched by information of different stakeholders and disciplines. In order to ensure the energy supply, the knowledge about the energy demands of buildings during the planning and optimization of measures is of great strategic importance. Therefore, this paper focuses on the city-wide estimation of the energy demands of buildings including heating, electricity and warm water energy in the city of Berlin using available official geobase and statistical data integrated within the Energy Atlas Berlin. It is explained in detail how the spatial and semantic properties of the 3D building models are being used to estimate these energy demands on an individual building level for the entire city.

Analyzing near water surface penetration in laser bathymetry – A case study at the River Pielach

Abstract: Recent developments in sensor technology yielded a major progress in airborne laser bathymetry for capturing shallow water bodies. Modern topo-bathymetric small foot print laser scanners do no longer use the primary near infrared (NIR) signal (=1064 nm) but only emit and receive the frequency doubled green signal (λ = 532 nm). For calculating correct water depths accurate knowledge of the water surface (air-water-interface) is mandatory for obtaining accurate spot positions and water depths. Due to the ability of the green signal to penetrate water the first reflections do not exactly represent the water surface but, depending on environmental parameters like turbidity, a certain penetration into the water column can be observed. This raises the question if it is even feasible to determine correct water level heights from the green laser echoes only. In this article, therefore, the near water surface penetration properties of the green laser signal are analyzed based on a test flight of the River Pielach (Austria) carried out with Riegl's VQ-820-G (532 nm) and VQ-580 (1064 nm) scanners mounted on the same airborne platform. It is shown that within the study area the mean penetration into the water column is in the range of 10–25 cm compared to the NIR signal as reference. However, as the upper hull of the green water surface echoes coincides with the NIR signal with cm-precision, it is still possible to derive water surface models from the green laser echoes only via statistical analysis of aggregated neighboring echoes and robustly keep the underestimation of the water level below 6 cm. This especially holds for still and stationary flowing water bodies.

Mobile laser scanning for indoor modelling

Abstract: The process of capturing and modelling buildings has gained increased focus in recent years with the rise of Building Information Modelling (BIM). At the heart of BIM is a process change for the construction and facilities management industries whereby a BIM aids more collaborative working through better information exchange, and as a part of the process Geomatic/Land Surveyors are not immune from the changes. Terrestrial laser scanning has been proscribed as the preferred method for rapidly capturing buildings for BIM geometry. This is a process change from a traditional measured building survey just with a total station and is aided by the increasing acceptance of point cloud data being integrated with parametric building models in BIM tools such as Autodesk Revit or Bentley Architecture. Pilot projects carried out previously by the authors to investigate the geometry capture and modelling of BIM confirmed the view of others that the process of data capture with static laser scan setups is slow and very involved requiring at least two people for efficiency. Indoor Mobile Mapping Systems (IMMS) present a possible solution to these issues especially in time saved. Therefore this paper investigates their application as a capture device for BIM geometry creation over traditional static methods through a fit-for-purpose test.

Online 4d reconstruction using multi-images available under open access

Abstract: . The advent of technology in digital cameras and their incorporation into virtually any smart mobile device has led to an explosion of the number of photographs taken every day. Today, the number of images stored online and available freely has reached unprecedented levels. It is estimated that in 2011, there were over 100 billion photographs stored in just one of the major social media sites. This number is growing exponentially. Moreover, advances in the fields of Photogrammetry and Computer Vision have led to significant breakthroughs such as the Structure from Motion algorithm which creates 3D models of objects using their twodimensional photographs. The existence of powerful and affordable computational machinery not only the reconstruction of complex structures but also entire cities. This paper illustrates an overview of our methodology for producing 3D models of Cultural Heritage structures such as monuments and artefacts from 2D data (pictures, video), available on Internet repositories, social media, Google Maps, Bing, etc. We also present new approaches to semantic enrichment of the end results and their subsequent export to Europeana, the European digital library, for integrated, interactive 3D visualisation within regular web browsers using WebGl and X3D. Our main goal is to enable historians, architects, archaeologists, urban planners and affiliated professionals to reconstruct views of historical structures from millions of images floating around the web and interact with them.

Evaluation of gis and bim roles for the information management of historical buildings

Abstract: . An architectural heritage object carries heterogeneous and multi-layered information beyond physical characteristics. It requires an integrated representation of various types of information for understanding and management prior to the decision-making process of conservation. This requirement is a twofold manner consisting of representation and management processes. There exists a variety of approaches for representation of heritage objects in digital three-dimensional (3D) environment, but the selection of the appropriate one according to the needs is crucial. On one hand, there have been recently great attempts to adopt Building Information Modeling (BIM) for historical buildings. Nevertheless, the related works in the topic focus mainly on pre-processing of data, such as the integration of born-digital material into a BIM environment and the creation of parametric objects according to historical building characteristics. As the information management of a historical building requires enhanced attribute management and integration of different datasets, further investigation on the BIM capabilities in management terms is crucial. On the other hand, Geographical Information Systems (GIS) have great potentials in exploring spatial relationships, but their potential in 3D representation is still somehow limited. The paper reviews and evaluates the roles of BIM and GIS, highlighting their advantages and disadvantages for integration, retrieval and management of heterogeneous data in the context of historical buildings.

Accuracy and block deformation analysis in automatic uav and terrestrial photogrammetry – lesson learnt –

Abstract: . The paper reports the results of an integrated Unmanned Aerial Vehicle (UAV) and terrestrial photogrammetric survey realized in the archaeological site of the Roman theatre in Ventimiglia, Italy. The main deliverables were 2D drawings at scale 1:20, which required a Ground Sample Distance (GSD) less than 4 mm and, consequently, accuracy better than 4 mm. The UAV was employed to acquire both vertical and oblique images, while the terrestrial imaging acquisition was realized with the aim of generating separate dense point clouds of some vertical structures, corresponding to the sections required. The variability of results with automatic photogrammetric procedures against different image network configurations, with and without ground control, are analysed and presented.

3d surveying and modeling of archaeological sites - some critical issues -

Abstract: . The goal of the reported project is to test and evaluate 3D surveying and modelling methods to document the remaining ancient byzantine city walls of the archaeological site of Aquileia in Friuli Venezia Giulia, Italy. The objectives are threefold: (1) to use 3D data to create maps, facades and sections that provide information useful for archaeological purposes such as the investigation of architectural construction techniques or construction phases, (2) to evaluate and compare photogrammetric and laser scanner data in order to identify the advantages and disadvantages of the two 3D surveying techniques for archaeological applications and needs and (3) to draw broader conclusions about the applicability of photogrammetry and laser scanning for documenting and analysing ancient walls within a particular set of environmental circumstances. The paper presents the employed 3D surveying techniques, the obtained 3D results and 2D products and some critical comments.

Markerless point cloud registration with keypoint-based 4-points congruent sets

Abstract: . This paper addresses the registration of LiDAR point clouds. More specifically, we present an automatic method for markerless registration of two such point clouds given in arbitrary local scan coordinates – i.e. without simplifying assumptions such as a common up-vector. Clearly, the critical step of the registration is to find a coarse initial alignment, to be refined with established local methods for fine registration, such as ICP or least-squares surface matching. The proposed approach builds on the 4-Points Congruent Sets (4PCS) algorithm (Aiger et al., 2008), a popular registration tool in computer graphics, and extends it to better deal with the specific challenges of LiDAR data. The main limitations of the original 4PCS method in that context are (i) that it does not cope well with strongly varying point densities, such as they routinely occur in laser scans due to the constant angular sampling from different viewpoints; and (ii) that to remain efficient, huge LiDAR point clouds must be down-sampled so heavily that approximate point-to-point correspondence can no longer be guaranteed. To overcome these drawbacks we propose not to apply 4PCS to the original point cloud (respectively, a randomly or regularly subsampled version of it), but rather to represent the point clouds with sets of distinctive 3D keypoints, and run (a slightly modified) 4PCS on the keypoint sets. The resulting combination, termed Keypoint-based 4-Points Congruent Sets (K-4PCS), proves to be very reliable: with suitable parameter settings, tests in indoor as well as outdoor environments yield 100% success rates.

Rail track detection and modelling in mobile laser scanner data

Abstract: We present a method for detecting and modelling rails in mobile laser scanner data. The detection is based on the properties of the rail tracks and contact wires such as relative height, linearity and relative position with respect to other objects. Points classified as rail track are used in a 3D modelling algorithm. The modelling is done by first fitting a parametric model of a rail piece to the points along each track, and estimating the position and orientation parameters of each piece model. For each position and orientation parameter a smooth low-order Fourier curve is interpolated. Using all interpolated parameters a mesh model of the rail is reconstructed. The method is explained using two areas from a dataset acquired by a LYNX mobile mapping system in a mountainous area. Residuals between railway laser points and 3D models are in the range of 2 cm. It is concluded that a curve fitting algorithm is essential to reliably and accurately model the rail tracks by using the knowledge that railways are following a continuous and smooth path.

Correction of Intensity Incidence Angle Effect in Terrestrial Laser Scanning

Abstract: . In this article, we have studied the incidence angle effect on Terrestrial Laser Scanning (TLS) intensity. In previous tests, it has been found that the backscattered intensity of an object affects the incidence angle effect. We made additional experiments to investigate the potential mixing of distance and incidence angle effects and the role of surface parameters such as object grain size and scanning wavelength. The results indicate that distance and incidence angle effects do not mix and laboratory measured correction values can be used to correct intensity data from field-scanned point clouds. We also compared the laboratory measurements to real world surfaces to validate the correction procedures in practical TLS applications. The idea is also to make practical recommendations for TLS intensity correction in most common TLS applications.

Enhanced lod concepts for virtual 3d city models

Abstract: Virtual 3D city models contain digital three dimensional representations of city objects like buildings, streets or technical infrastructure. Because size and complexity of these models continuously grow, a Level of Detail (LoD) concept effectively supporting the partitioning of a complete model into alternative models of different complexity and providing metadata, addressing informational content, complexity and quality of each alternative model is indispensable. After a short overview on various LoD concepts, this paper discusses the existing LoD concept of the CityGML standard for 3D city models and identifies a number of deficits. Based on this analysis, an alternative concept is developed and illustrated with several examples. It differentiates between first, a Geometric Level of Detail (GLoD) and a Semantic Level of Detail (SLoD), and second between the interior building and its exterior shell. Finally, a possible implementation of the new concept is demonstrated by means of an UML model.

Change Detection in 3D Point Clouds Acquired by a Mobile Mapping System

Abstract: . Thanks to the development of Mobile mapping systems (MMS), street object recognition, classification, modelling and related studies have become hot topics recently. There has been increasing interest in detecting changes between mobile laser scanning (MLS) point clouds in complex urban areas. A method based on the consistency between the occupancies of space computed from different datasets is proposed. First occupancy of scan rays (empty, occupied, unknown) are defined while considering the accuracy of measurement and registration. Then the occupancy of scan rays are fused using the Weighted Dempster–Shafer theory (WDST). Finally, the consistency between different datasets is obtained by comparing the occupancy at points from one dataset with the fused occupancy of neighbouring rays from the other dataset. Change detection results are compared with a conventional point to triangle (PTT) distance method. Changes at point level are detected fully automatically. The proposed approach allows to detect changes at large scales in urban scenes with fine detail and more importantly, distinguish real changes from occlusions.

Towards a 3d Spatial Urban Energy Modelling Approach

Abstract: . Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies conceptually and practically integrate urban spatial and energy planning approaches. The combined modelling approach that will be developed based on the described sectorial models holds the potential to represent hybrid energy systems coupling distributed generation of electricity with thermal conversion systems.

Land cover classification of satellite images using contextual information

Abstract: . This paper presents a method for the classification of satellite images into multiple predefined land cover classes. The proposed approach results in a fully automatic segmentation and classification of each pixel, using a small amount of training data. Therefore, semantic segmentation techniques are used, which are already successful applied to other computer vision tasks like facade recognition. We explain some simple modifications made to the method for the adaption of remote sensing data. Besides local features, the proposed method also includes contextual properties of multiple classes. Our method is flexible and can be extended for any amount of channels and combinations of those. Furthermore, it is possible to adapt the approach to several scenarios, different image scales, or other earth observation applications, using spatially resolved data. However, the focus of the current work is on high resolution satellite images of urban areas. Experiments on a QuickBird-image and LiDAR data of the city of Rostock show the flexibility of the method. A significant better accuracy can be achieved using contextual features.

Processing tree point clouds using gaussian mixture models

Abstract: . While traditionally used for surveying and photogrammetric fields, laser scanning is increasingly being used for a wider range of more general applications. In addition to the issues typically associated with processing point data, such applications raise a number of new complications, such as the complexity of the scenes scanned, along with the sheer volume of data. Consequently, automated procedures are required for processing, and analysing such data. This paper introduces a method for modelling multi-modal, geometrically complex objects in terrestrial laser scanning point data; specifically, the modelling of trees. The model method comprises a number of geometric features in conjunction with a multi-modal machine learning technique. The model can then be used for contextually dependent region growing through separating the tree into its component part at the point level. Subsequently object analysis can be performed, for example, performing volumetric analysis of a tree by removing points associated with leaves. The workflow for this process is as follows: isolate individual trees within the scanned scene, train a Gaussian mixture model (GMM), separate clusters within the mixture model according to exemplar points determined by the GMM, grow the structure of the tree, and then perform volumetric analysis on the structure.

Eigenvalue and graph-based object extraction from mobile laser scanning point clouds

Abstract: . The mapping of road environments is an important task, providing important input data for a broad range of scientific disciplines. Pole-like objects, their visibility and their influence onto local light and traffic noise conditions are of particular interest for traffic safety, public health and ecological issues. Detailed knowledge can support the improvement of traffic management, noise reducing infrastructure or the planning of photovoltaic panels. Mobile Mapping Systems coupled with computer aided mapping work-flows allow an effective data acquisition and provision. We present a classification work flow focussing on pole-like objects. It uses rotation and scale invariant point and object features for classification, avoiding planar segmentation and height slicing steps. Single objects are separated by connected component and Dijkstra-path analysis. Trees and artificial objects are separated using a graph based approach considering the branching levels of the given geometries. For the focussed semantic groups, classification accuracies higher than 0.9 are achieved. This includes both the quality of object aggregation and separation, where the combination of Dijkstrapath aggregation and graph-based classification shows good results. For planar objects the classification accuracies are lowered, recommending the usage of planar segmentation for classification and subdivision issues as presented by other authors. The presented work-flow provides sufficient input data for further 3D reconstructions and tree modelling.

Semi-Automatic Road/Pavement Modeling using Mobile Laser Scanning

Abstract: Scene analysis, in urban environments, deals with street modeling and understanding. A street mainly consists of roadways, pavements (i.e., walking areas), facades, still and moving obstacles. In this paper, we investigate the surface modeling of roadways and pavements using LIDAR data acquired by a mobile laser scanning (MLS) system. First, road border detection is considered. A system recognizing curbs and curb ramps while reconstructing the missing information in case of occlusion is presented. A user interface scheme is also described, providing an effective tool for semi-automatic processing of large amount of data. Then, based upon road edge information, a process that reconstructs surfaces of roads and pavements has been developed, providing a centimetric precision while reconstructing missing information. This system hence provides an important knowledge of the street, that may open perspectives in various domains such as path planning or road maintenance.

Parametric Modelling (bim) for the Documentation of Vernacular Construction Methods: a Bim Model for the Commissariat Building, Ottawa, Canada

Abstract: Whether a house of worship or a simple farmhouse, the fabrication of a building reveals both the unspoken cultural aspirations of the builder and the inevitable exigencies of the construction process. In other-words, why buildings are made is intimately and inevitably associated with how buildings are made. Nowhere is this more evident than in vernacular architecture. At the Carleton Immersive Media Studio (CIMS) we are concerned that the de-population of Canada's rural areas, paucity of specialized tradespersons, and increasing complexity of building codes threaten the sustainability of this invaluable cultural resource. For current and future generations, the quantitative and qualitative values of traditional methods of construction are essential for an inclusive cultural memory. More practically, and equally pressing, an operational knowledge of these technologies is essential for the conservation of our built heritage. To address these concerns, CIMS has launched a number of research initiatives over the past five years that explore novel protocols for the documentation and dissemination of knowledge related to traditional methods of construction. Our current project, Cultural Diversity and Material Imagination in Canadian Architecture (CDMICA), made possible through funding from Canada's Social Sciences and Humanities Research Council (SSHRC), explores the potential of building information modelling (BIM) within the context of a web-based environment. In this paper, we discuss our work-to-date on the development of a web-based library of BIM details that is referenced to ''typical'' assemblies culled from 19C and early 20C construction manuals. The parametric potential of these ''typical'' details is further refined by evidence from the documentation of ''specific'' details studied during comprehensive surveys of extant heritage buildings. Here, we consider a BIM of the roof truss assembly of one of the oldest buildings in Canada's national capital – the Commissariat Building and current home to the Bytown Museum – as a case study within the CDMICA project.

Points clouds generation using tls and dense-matching techniques. a test on approachable accuracies of different tools.

Abstract: 3D detailed models derived from digital survey techniques has increasingly developed and focused in many field of application, ranging from the land and urban areas survey, using remote sensed data, to landscape assets and finally to Cultural Heritage items. The high detailed content and accuracy of such models makes them so attractive and usable for large sets of purposes. The present paper is focused on a test aimed to point clouds generation fulfilled by archaeological data; active and passive sensors techniques and related image matching systems have been used in order to evaluate and compare the accuracy of results, achievable using proper TLS and low cost image-matching software and techniques. After a short review of approachable methods some attained results will be discussed; the test area consists of a set of mosaic floorings in a late roman domus located in Aquileia (UD-Italy) requesting a very high level of details and high scale and precision. The experimental section provides the descriptions of the applied tests in order to compare the different software and the employed methods.

Combined geometric and thermal analysis from uav platforms for archaeological heritage documentation

Abstract: The aim of this work is to study the value and potential of UAV technology as an instrument for documenting and analyzing a heritage site on both the detailed scale and the wider territorial scale. In particular, this paper will focus on the application of an UAV platform on the archeological site of Isola Comacina (Comacina Island), in the Lago di Como (Lake Como, Lombardy, Northern Italy). The work considers the advantages of different metric scales and the use of both RGB and thermal imagery, along with other terrestrial data (total station measurements and laser scans), in order to arrive at a working heritage information model. In particular, the archaeological remains on Isola Comacina have been intensively studied before by standard techniques but unfortunately no wider context is provided. A part of the research is the investigation of new methodologies offered by accurate geometric reconstructions combined with thermal imagery acquired by means of UAV platforms, e.g. the support of this type of imagery to discover rock formations partially buried.

Optimizing detection of road furniture (pole-like object) in Mobile Laser Scanner data

Abstract: . Due to the road safety problem is becoming more and more serious recent years, existing road safety assessment by using automatic method is necessary. Meanwhile, since the pole-like objects have large effect on road safety and are in high demand as facilities to be managed, the automatic pole-like objects extraction is becoming a hot issue. As a result, a robust, quick and automatic pole-like object detection algorithm in MLS data is proposed in this paper. Two datasets are tested to show performance of the proposed algorithm, it demonstrates that it is feasible to detect tree with an overall accuracy of over 92% and other pole-like object of 72% in dataset A and 82% of tree points and 75% of other pole points in dataset B.

Monument damage information system (mondis): an ontological approach to cultural heritage documentation

Abstract: . Deriving from the complex nature of cultural heritage conservation it is the need for enhancing a systematic but flexible organization of expert knowledge in the field. Such organization should address comprehensively the interrelations and complementariness among the different factors that come into play in the understanding of diagnostic and intervention problems. The purpose of MONDIS is to endorse this kind of organization. The approach consists in applying an ontological representation to the field of heritage conservation in order to establish an appropriate processing of data. The system allows replicating in a computer readable form the basic dependence among factors influencing the description, diagnosis and intervention of damages to immovable objects. More specifically MONDIS allows to input and search entries concerning object description, structural evolution, location characteristics and risk, component, material properties, surveys and measurements, damage typology, damage triggering events and possible interventions. The system supports searching features typical of standard databases, as it allows for the digitalization of a wide range of information including professional reports, books, articles and scientific papers. It also allows for computer aided retrieval of information tailored to user's requirements. The foreseen outputs will include a web user interface and a mobile application for visual inspection purposes.

Detection of lying tree stems from airborne laser scanning data using a line template matching algorithm

Abstract: . Dead wood is an important habitat characteristic in forests. However, dead wood lying on the ground below a canopy is difficult to detect from remotely sensed data. Data from airborne laser scanning include measurement of surfaces below the canopy, thus offering the potential to model objects on the ground. This paper describes a new line template matching algorithm for detecting lines along the ground. The line template matching is done directly to the laser point cloud and results in a raster showing the support of the line in each raster cell. Line elements are vectorized based on the raster to represent lying tree stems. The results have been validated versus field-measured lying tree stems. The number of detected lines was 845, of which 268 could be automatically linked to the 651 field-measured stems. The line template matching produced a raster which visually showed linear elements in areas where lying tree stems where present, but the result is difficult to compare with the field measurements due to positioning errors. The study area contained big piles of storm-felled trees in some places, which made it an unusually complex test site. Longer line structures such as ditches and roads also resulted in detected lines and further analysis is needed to avoid this, for example by specifically detecting longer lines and removing them.

Building Footprints Extraction from Oblique Imagery

Abstract: Nowadays, multi-camera aerial platforms combining nadir and oblique cameras are experiencing a revival and several companies have proposed new image acquisition systems. Due to their various advantages, oblique imagery have found their place in numerous companies and civil applications. However, the automatic processing of such image blocks still remains a topic of research. Camera configuration indeed poses a challenge on the traditional photogrammetric pipeline used in commercial software but, on the other hand, gives the opportunity to exploit the additional information provided by the oblique views and allows a more reliable feature extraction. In particular, the information that can be provided in correspondence of building facades can open new possibilities for the building detection and footprint extraction. In this paper, a methodology for the automated extraction of building footprints from oblique imagery is presented. The extraction is performed using dense point clouds generated using an image matching algorithm. The developed methodology and the achieved results are described in detail showing the advantages and opportunities offered by oblique aerial systems for cartographic and mapping purposes.

Combined Grammar for the Modeling of Building Interiors

Abstract: As spatial grammars have proven successful and efficient to deliver LOD3 models, the next challenge is their extension to indoor applications, leading to LOD4 models. Therefore, a combined indoor grammar for the automatic generation of indoor models from erroneous and incomplete observation data is presented. In building interiors where inaccurate observation data is available, the grammar can be used to make the reconstruction process robust, and verify the reconstructed geometries. In unobserved building interiors, the grammar can generate hypotheses about possible indoor geometries matching the style of the rest of the building. The grammar combines concepts from L-systems and split grammars. It is designed in such way that it can be derived from observation data fully automatically. Thus, manual predefinitions of the grammar rules usually required to tune the grammar to a specific building style, become obsolete. The potential benefit of using our grammar as support for indoor modeling is evaluated based on an example where the grammar has been applied to automatically generate an indoor model from erroneous and incomplete traces gathered by foot-mounted MEMS/IMU positioning systems.

Generation and weighting of 3d point correspondences for improved registration of rgb-d data

Abstract: Registration of RGB-D data using visual features is often influenced by errors in the transformation of visual features to 3D space as well as the random error of individual 3D points. In a long sequence, these errors accumulate and lead to inaccurate and deformed point clouds, particularly in situations where loop closing is not feasible. We present an epipolar search method for accurate transformation of the keypoints from 2D to 3D space, and define weights for the 3D points based on the theoretical random error of depth measurements. Our results show that the epipolar search method results in more accurate 3D correspondences. We also demonstrate that weighting the 3D points improves the accuracy of sensor pose estimates along the trajectory.

Enhanced detection of 3d individual trees in forested areas using airborne full-waveform lidar data by combining normalized cuts with spatial density clustering

Abstract: . A detailed understanding of the spatial distribution of forest understory is important but difficult. LiDAR remote sensing has been developing as a promising additional instrument to the conventional field work towards automated forest inventory. Unfortunately, understory (up to 50% of the top-tree height) in mixed and multilayered forests is often ignored due to a difficult observation scenario and limitation of the tree detection algorithm. Currently, the full-waveform (FWF) LiDAR with high penetration ability against overstory crowns can give us new hope to resolve the forest understory. Former approach based on 3D segmentation confirmed that the tree detection rates in both middle and lower forest layers are still low. Therefore, detecting sub-dominant and suppressed trees cannot be regarded as fully solved. In this work, we aim to improve the performance of the FWF laser scanner for the mapping of forest understory. The paper is to develop an enhanced methodology for detecting 3D individual trees by partitioning point clouds of airborne LiDAR. After extracting 3D coordinates of the laser beam echoes, the pulse intensity and width by waveform decomposition, the newly developed approach resolves 3D single trees are by an integrated approach, which delineates tree crowns by applying normalized cuts segmentation to the graph structure of local dense modes in point clouds constructed by mean shift clustering. In the context of our strategy, the mean shift clusters approximate primitives of (sub) single trees in LiDAR data and allow to define more significant features to reflect geometric and reflectional characteristics towards the single tree level. The developed methodology can be regarded as an object-based point cloud analysis approach for tree detection and is applied to datasets captured with the Riegl LMS-Q560 laser scanner at a point density of 25 points/m2 in the Bavarian Forest National Park, Germany, respectively under leaf-on and leaf-off conditions. The experiments lead to a detection rate of up to 67% for trees in the middle height layer and up to 53% for trees in the lower forest layer. It corresponds to an overall improvement in the detection rate of nearly 25% for forest understory compared to that obtained by the former method by extracting individual trees using normalized cuts segmentation solely.

Detecting and Updating Changes in Lidar Point Clouds for Automatic 3D Urban Cartography

Abstract: . This work presents a method that automatically detects, analyses and then updates changes in LiDAR point clouds for accurate 3D urban cartography. In the proposed method, the 3D point cloud obtained in each passage is first classified into 2 main object classes: Permanent and Temporary. The Temporary objects are then removed from the 3D point cloud to leave behind a perforated 3D point cloud of the urban scene. These perforated 3D point clouds obtained from different passages (in the same place) at different days and times are then matched together to complete the 3D urban landscape by incremental updating. Different natural or man-made changes occurring in the urban landscape over this period of time are detected and analyzed using cognitive functions of similarity and the resulting 3D cartography is progressively modified and updated accordingly. The results, evaluated on real data using different standard evaluation metrics, not only demonstrate the efficacy of the proposed method but also shows that this method is easily applicable and well scalable, making it suitable for handling large urban scenes.