bluuebunny/crossref_metadata_2025 huggingface dataset:
ACCURACY POTENTIAL AND APPLICATIONS OF MIDAS AERIAL OBLIQUE CAMERA SYSTEM
Authors: Madani M.
Published: August 2012

Abstract. Airborne oblique cameras such as Fairchild T-3A were initially used for military reconnaissance in 30s. A modern professional digital oblique camera such as MIDAS (Multi-camera Integrated Digital Acquisition System) is used to generate lifelike three dimensional to the users for visualizations, GIS applications, architectural modeling, city modeling, games, simulators, etc. Oblique imagery provide the best vantage for accessing and reviewing changes to the local government tax base, property valuation assessment, buying & selling of residential/commercial for better decisions in a more timely manner. Oblique imagery is also used for infrastructure monitoring making sure safe operations of transportation, utilities, and facilities. Sanborn Mapping Company acquired one MIDAS from TrackAir in 2011. This system consists of four tilted (45 degrees) cameras and one vertical camera connected to a dedicated data acquisition computer system. The 5 digital cameras are based on the Canon EOS 1DS Mark3 with Zeiss lenses. The CCD size is 5,616 by 3,744 (21 MPixels) with the pixel size of 6.4 microns. Multiple flights using different camera configurations (nadir/oblique (28 mm/50 mm) and (50 mm/50 mm)) were flown over downtown Colorado Springs, Colorado. Boresight fights for 28 mm nadir camera were flown at 600 m and 1,200 m and for 50 mm nadir camera at 750 m and 1500 m. Cameras were calibrated by using a 3D cage and multiple convergent images utilizing Australis model. In this paper, the MIDAS system is described, a number of real data sets collected during the aforementioned flights are presented together with their associated flight configurations, data processing workflow, system calibration and quality control workflows are highlighted and the achievable accuracy is presented in some detail. This study revealed that the expected accuracy of about 1 to 1.5 GSD (Ground Sample Distance) for planimetry and about 2 to 2.5 GSD for vertical can be achieved. Remaining systematic errors were modeled by analyzing residuals using correction grid. The results of the final bundle adjustments are sufficient to enable Sanborn to produce DEM/DTM and orthophotos from the nadir imagery and create 3D models using georeferenced oblique imagery.
ONE-STEP AND TWO-STEP CALIBRATION OF A PORTABLE PANORAMIC IMAGE MAPPING SYSTEM
Authors: Wang P.-C. , Tsai P.-C. , Chen Y.-C. , Tseng Y.-H.
Published: August 2012

Abstract. A Portable Panoramic Image Mapping System (PPIMS) is proposed for rapid acquisition of three-dimensional spatial information. By considering the convenience of use, cost, weight of equipment, precision, and power supply, the designed PPIMS is equipped with 6 circularly arranged cameras to capture panoramic images and a GPS receiver for positioning. The motivation for this design is to develop a hand-held Mobile Mapping System (MMS) for some difficult accessing areas by vehicle MMS, such as rugged terrains, forest areas, heavily damaged disaster areas, and crowed places etc. This PPIMS is in fact a GPS assisted close-range photogrammetric system. Compared with the traditional close-range photogrammetry, PPIMS can reduce the need of ground control points significantly. Under the condition of knowing the relative geometric relationships of the equipped sensors, the elements of exterior orientation of each captured image can be solved. However, the procedure of a system calibration should be done accurately to determine the relative geometric relationships of multi-cameras and the GPS antenna center, before the PPIMS can be applied for geo-referenced mapping. In this paper, both of one-step and two-step calibration procedures for PPIMS are performed to determine the lever-arm offsets and boresight angles among cameras and GPS. The performance of the one-step and two-step calibration is evaluated through the analysis of the experimental results. The comparison between these two calibration procedures was also conducted. The two-step calibration method outperforms the one-step calibration method in terms of calibration accuracy and operation convenience. We expect that the proposed two-step calibration procedure can also be applied to other platform-based MMSs.
IMAGE REGISTRATION USING TERRAIN RELIEF CORRECTION BASED ON THE RIGOROUS SENSOR MODELS
Authors: Kim H. , Kim M.-G.
Published: August 2012

Abstract. Multiple CCDs are used in space-borne camera system to have multiple bands and/or to have wider swath even in one band. Due to design constraints, the multiple CCDs may be placed at different position on the effective focal plane. In such case, each band or each CCD in a band has different look angle, and hence suffers so-called "parallax effect" when registration between images from different CCD is required. Since the parallax effect is a function of height of the target when the baseline is fixed, the displacement of each target for the registration differs from target to target depending on the height of each target in the images. Hence, the registration between images from different CCDs cannot be achieved using simple affine transform, and rather requires higher order matching methods, such as local warping. In this paper, we suggest the band registration method which includes the compensation of terrain relief by sensor model with DEM data. Since the parallax effect is compensated in this approach, the simpler matching strategy can be adopted for the robustness of algorithm. In the proposed approach, the slave image is resampled to virtual CCD geometry, which has same geometry with master image. In order to realize such approach, accurate camera model for each band and DEM data were used. The difference of proposed approach with conventional ortho-rectification is that the geometry of master image is kept. The experiment results demonstrated that proposed method can effectively correct the displacement caused by parallax effect.
3D PHOTOGRAMMETRIC PROCESSING OF WORLDVIEW-2 DATA WITHOUT GCP
Authors: Toutin T. , Schmitt C. V. , Wang H. , Reinartz P.
Published: August 2012

Abstract. A hybrid model based on 3D deterministic Toutin's model developed at the Canada Centre for Remote Sensing and taking full advantages of the image metadata was used for the 3D photogrammetric processing of WorldView-1 stereo images without in situ ground control points (GCP) collection. The accuracy of the modelling results in monoscopy and stereoscopy was around 0.7-1.8 m in planimetry and 2.7 m in altimetry computed over 40 dGPs checked points. Elevations were thus extracted and compared to 0.2 m accurate lidar elevation data. Elevations linear error with 68 percent confidence level (LE68) computed over bare surfaces was 2.6 m, with small biases. These results were compared with the solution using 8 dGPS GCPs and demonstrated there is no significant difference in auccuracy. Consequently, the new hybrid model will offer a strong advantage of no-control collection in operational conditions, mainly in remote and harsh environments or when cartographic or ground control data do not exist.
ACCURACY VERIFICATION OF GPS-INS METHOD IN INDONESIA
Authors: Mulyana A. K. , Rizaldy A. , Uesugi K.
Published: August 2012

Abstract. Pasco Corporation (Japan) has been implementing a project in Indonesia for Sumatra Island which is named Data Acquisition and Production on the National Geo-Spatial Data Infrastructure (NSDI) Development. Digital aerial images in 25 cm GSD for 1:10,000 scale mapping have been taken as a part of the project. The owner of the project, The National Coordinating Agency for Surveys and Mapping (Bakosurtanal) planned to apply conventional aerial triangulation method as the initial stage. Pasco recommended Direct Geo-Reference Methodology by using GPS-IMU measurements and carried out a verification work in a city area. Measurements of tie points were implemented by using KLT/ATLAS software manually and adjusted by BINGO software. Aerial triangulation accuracy verifications were done by using one height control in the block center, one GCP in the center and four GCPs at the corners and one in the center. The results are sequentially, rms X,Y = 0.410 cm, rms Z = 0.394 cm (one height control point), rms X,Y = 0.430 cm, rms Z = 0.392 cm (one GCP) and rms X,Y = 0.356 cm, rms Z = 0.395 cm (5 GCPs). 5 GCPs for each block in official applications have been preferred for safety reasons. Comparisons of direct geo-referencing results with geodetic check points and aerial triangulation block adjustments have been done. The details of the work have been given in this study.
PHOTOGRAMMETRIC MEASUREMENTS IN FIXED WING UAV IMAGERY
Authors: Gülch E.
Published: August 2012

Abstract. Several flights have been undertaken with PAMS (Photogrammetric Aerial Mapping System) by Germap, Germany, which is briefly introduced. This system is based on the SmartPlane fixed-wing UAV and a CANON IXUS camera system. The plane is equipped with GPS and has an infrared sensor system to estimate attitude values. A software has been developed to link the PAMS output to a standard photogrammetric processing chain built on Trimble INPHO. The linking of the image files and image IDs and the handling of different cases with partly corrupted output have to be solved to generate an INPHO project file. Based on this project file the software packages MATCH-AT, MATCH-T DSM, OrthoMaster and OrthoVista for digital aerial triangulation, DTM/DSM generation and finally digital orthomosaik generation are applied. The focus has been on investigations on how to adapt the "usual" parameters for the digital aerial triangulation and other software to the UAV flight conditions, which are showing high overlaps, large kappa angles and a certain image blur in case of turbulences. It was found, that the selected parameter setup shows a quite stable behaviour and can be applied to other flights. A comparison is made to results from other open source multi-ray matching software to handle the issue of the described flight conditions. Flights over the same area at different times have been compared to each other. The major objective was here to see, on how far differences occur relative to each other, without having access to ground control data, which would have a potential for applications with low requirements on the absolute accuracy. The results show, that there are influences of weather and illumination visible. The "unusual" flight pattern, which shows big time differences for neighbouring strips has an influence on the AT and DTM/DSM generation. The results obtained so far do indicate problems in the stability of the camera calibration. This clearly requests a usage of GCPs for all projects, independent on the application. The effort is estimated to be even higher as expected, as also self-calibration will be an issue to handle a possibly instable camera calibration. To overcome some of the encountered problems with the very specific features of UAV flights a software UAVision was developed based on Open Source libraries to produce input data for bundle adjustment of UAV images by PAMS. The empirical test results show a considerable improvement in the matching of tie points. The results do, however, show that the Open Source bundle adjustment was not applicable to this type of imagery. This still leaves the possibility to use the improved tie point correspondences in the commercial AT package.
DETERMINATION OF EXTERIOR ORIENTATION PARAMETERS THROUGH DIRECT GEO-REFERENCING IN A REAL-TIME AERIAL MONITORING SYSTEM
Authors: Kim H. , Lee J. , Choi K. , Lee I.
Published: August 2012

Abstract. Rapid responses for emergency situations such as natural disasters or accidents often require geo-spatial information describing the on-going status of the affected area. Such geo-spatial information can be promptly acquired by a manned or unmanned aerial vehicle based multi-sensor system that can monitor the emergent situations in near real-time from the air using several kinds of sensors. Thus, we are in progress of developing such a real-time aerial monitoring system (RAMS) consisting of both aerial and ground segments. The aerial segment acquires the sensory data about the target areas by a low-altitude helicopter system equipped with sensors such as a digital camera and a GPS/IMU system and transmits them to the ground segment through a RF link in real-time. The ground segment, which is a deployable ground station installed on a truck, receives the sensory data and rapidly processes them to generate ortho-images, DEMs, etc. In order to generate geo-spatial information, in this system, exterior orientation parameters (EOP) of the acquired images are obtained through direct geo-referencing because it is difficult to acquire coordinates of ground points in disaster area. The main process, since the data acquisition stage until the measurement of EOP, is discussed as follows. First, at the time of data acquisition, image acquisition time synchronized by GPS time is recorded as part of image file name. Second, the acquired data are then transmitted to the ground segment in real-time. Third, by processing software for ground segment, positions/attitudes of acquired images are calculated through a linear interpolation using the GPS time of the received position/attitude data and images. Finally, the EOPs of images are obtained from position/attitude data by deriving the relationships between a camera coordinate system and a GPS/IMU coordinate system. In this study, we evaluated the accuracy of the EOP decided by direct geo-referencing in our system. To perform this, we used the precisely calculated EOP through the digital photogrammetry workstation (DPW) as reference data. The results of the evaluation indicate that the accuracy of the EOP acquired by our system is reasonable in comparison with the performance of GPS/IMU system. Also our system can acquire precise multi-sensory data to generate the geo-spatial information in emergency situations. In the near future, we plan to complete the development of the rapid generation system of the ground segment. Our system is expected to be able to acquire the ortho-image and DEM on the damaged area in near real-time. Its performance along with the accuracy of the generated geo-spatial information will also be evaluated and reported in the future work.
USING A MICRO-UAV FOR ULTRA-HIGH RESOLUTION MULTI-SENSOR OBSERVATIONS OF ANTARCTIC MOSS BEDS
Authors: Lucieer A. , Robinson S. , Turner D. , Harwin S. , Kelcey J.
Published: August 2012

Abstract. This study is the first to use an Unmanned Aerial Vehicle (UAV) for mapping moss beds in Antarctica. Mosses can be used as indicators for the regional effects of climate change. Mapping and monitoring their extent and health is therefore important. UAV aerial photography provides ultra-high resolution spatial data for this purpose. We developed a technique to extract an extremely dense 3D point cloud from overlapping UAV aerial photography based on structure from motion (SfM) algorithms. The combination of SfM and patch-based multi-view stereo image vision algorithms resulted in a 2 cm resolution digital terrain model (DTM). This detailed topographic information combined with vegetation indices derived from a 6-band multispectral sensor enabled the assessment of moss bed health. This novel UAV system has allowed us to map different environmental characteristics of the moss beds at ultra-high resolution providing us with a better understanding of these fragile Antarctic ecosystems. The paper provides details on the different UAV instruments and the image processing framework resulting in DEMs, vegetation indices, and terrain derivatives.
THE PERFORMANCE ANALYSIS OF A UAV BASED MOBILE MAPPING SYSTEM
Authors: Tsai M. L. , Chiang K. W. , Tseng Y. H. , Rau J. Y. , Huang Y. W. , Lo C. F.
Published: August 2012

Abstract. In order to facilitate applications such as environment detection or disaster monitoring, developing a quickly and low cost system to collect near real time spatial information is very important. Such a rapid spatial information collection capability has become an emerging trend in the technology of remote sensing and mapping application. In this study, a fixed-wing UAV based spatial information acquisition platform is developed and evaluated. The proposed UAV based platform has a direct georeferencing module including an low cost INS/GPS integrated system, low cost digital camera as well as other general UAV modules including immediately video monitoring communication system. This direct georeferencing module is able to provide differential GPS processing with single frequency carrier phase measurements to obtain sufficient positioning accuracy. All those necessary calibration procedures including interior orientation parameters, the lever arm and boresight angle are implemented. In addition, a flight test is performed to verify the positioning accuracy in direct georeferencing mode without using any ground control point that is required for most of current UAV based photogrammetric platforms. In other word, this is one of the pilot studies concerning direct georeferenced based UAV photogrammetric platform. The preliminary results in term of positioning accuracy in direct georeferenced mode without using any GCP illustrate horizontal positioning accuracies in x and y axes are both less than 20 meters, respectively. On the contrary, the positioning accuracy of z axis is less than 50 meters with 600 meters flight height above ground. Such accuracy is good for near real time disaster relief. Therefore, it is a relatively safe and cheap platform to collect critical spatial information for urgent response such as disaster relief and assessment applications where ground control points are not available.
THE PERFORMANCE OF A TIGHT INS/GNSS/PHOTOGRAMMETRIC INTEGRATION SCHEME FOR LAND BASED MMS APPLICATIONS IN GNSS DENIED ENVIRONMENTS
Authors: Chu C. H. , Chiang K. W.
Published: August 2012

Abstract. Nowadays the most common technologies used for positioning and orientation of a mobile mapping system include using Global Navigation Satellite System (GNSS) as a major positioning sensor and Inertial Navigation System (INS) as the major orientation sensor. The integration strategy of the most commercially system is the loosely coupled (LC) architecture, that has the simplest architecture using the GNSS solutions to aid the INS navigation information with proper optimization estimator. The LC does combine the two sensors’ solutions when the number of tracked satellite is more than four. In recent year, another commonly integration strategy is known as tightly coupled (TC) architecture. Because the TC uses the GNSS measurements to aid INS, it can integrate measurements provided by GNSS receiver and INS unless no GNSS satellite is tracked. Obviously, the TC architecture is a better candidate for land based mobile mapping applications than LC in Taiwan. Unfortunately, there are still many GNSS denied environment in the urban area, therefore the TC architecture is still not robust and stable enough for MMS application. The overall objective of this paper is to provide a scheme that tightly integrates INS/GNSS and Photogrammetric for land based MMS applications with sufficient and stable POS solutions during GNSS outages. In the traditional photogrammetry operation, numerous ground control points are applied to compute those Exterior Orientation Parameters (EOPs) of cameras by bundle adjustment. The key opinion is to derive the INS centre position and attitude and reconstruct 3-D tracking and 3-D object space by cameras EOPs. The proposed algorithm is verified using field test data collected in GNSS denied environments and the preliminary results presented in this study illustrated that the proposed algorithm is able to provide 60% improvement in terms of positioning and orientation accuracy in Taipei and Tainan cities.
SURFACE COMPLEXITY COMPONENT OF LIDAR POINT CLOUD ERROR CHARACTERIZATION
Authors: Toth C. , Grejner-Brzezinska D.
Published: August 2012

Abstract. There are several data product characterization methods to describe LiDAR data quality. Typically based on guidelines developed by government or professional societies, these techniques require the statistical analysis of vertical differences at known checkpoints (surface patches) to obtain a measure of the vertical accuracy. More advanced methods attempt to also characterize the horizontal accuracy of the LiDAR point cloud, using measurements at LiDAR-specific targets or other man-made objects that can be distinctly extracted from both horizontal and vertical representation in the LiDAR point cloud. There are two concerns with these methods. First, the number of check points/features is relatively small with respect to the point cloud size that is typically measured, at least, in millions. Second, these locations are usually selected in relatively benign areas, such as hard flat surfaces at easily accessible locations. The problem with this characterization is that it is not likely that a statistically representative analysis can be obtained from a limited number of points at locations that may not properly represent the overall object space composition. There is an ongoing effort to address these issues, and some of the newer methods to characterize LiDAR data include an average points spacing measure, computed from the LiDAR point cloud. Clearly, it is an important step forward but it ignores the surface complexity. The objective of this study is to elaborate only on the requirements for adequate surface representation in combination with the LiDAR error characterization techniques to identify the relation between the two surfaces, the measured and reference (ideal), and thus, to support better LiDAR or, in general, point cloud error characterization.
PERFORMANCE ANALYSIS OF FAST AT FOR CORRIDOR AERIAL MAPPING
Authors: Blázquez M. , Colomina I.
Published: August 2012

Abstract. Nowadays most airborne photogrammetric and remote sensing systems are equipped with GNSS receivers and inertial sensors that allow the use of various orientation methods: from Direct Sensor Orientation (DiSO) to Integrated Sensor Orientation (ISO), all the way to "Fast Aerial Triangulation" (Fast AT), a new orientation method recently proposed by the authors of this paper. On the one hand, DiSO is the fastest method. It only needs the INS/GNSS time-position-attitude aerial control information and the previously calibrated system constants as the lever-arm vectors and boresight matrices. On the other hand, ISO is the most accurate and robust orientation and calibration method. It uses all the available information: a large number of image coordinates, some ground control points and the INS/GNSS time-position-attitude aerial control information. Fast AT is a new orientation method that combines the image measurement of few ground control points, the coordinates of these ground control points and the time-position-attitude aerial control information. Fast AT is clearly an alternative to DiSO, even an alternative to ISO depending on project specifications. Our preliminary results with regular blocks indicate that Fast AT performances are closer to the ISO than to the DiSO results. In the light of the good results for block aerial mapping, in this paper we investigate Fast AT performance for corridor aerial mapping: we briefly review the concept, discuss its geometry and analyse its potential for corridor aerial mapping.
SIMPLIFIED 3D CITY MODELS FROM LIDAR
Authors: Lesparre J. , Gorte B. G. H.
Published: August 2012

Abstract. Aerial laser scan data is widely used to produce 2 1/2D digital elevation models automatically. However, creating full 3D city models from this data is a complex task. A simplified 3D model, like a 2 1/2D model with vertical walls will be easier to produce automatically, especially when the model is not produced to look nice, but just to give realistic results in an analysis or a simulation. To be able to include vertical walls in a 2 1/2D model we extend the TIN data structure in such way that the height of a vertex is stored implicitly in a way that allows multiple heights and efficient processing at the same time. To generate the city model we first apply data reduction in planar areas of an initial TIN. Next, we segment the TIN into planar segments for the ground, walls and roof planes. Finally, we intersect the segments to obtain a 2 1/2D model with slightly slanted walls, which should be adjusted to become exactly vertical. The results for simulated point cloud data are near-perfect. Real aerial laser scan data are more challenging, but the method still gives promising results.
DIGITAL ARCHIVING OF PEOPLE FLOW BY RECYCLING LARGE-SCALE SOCIAL SURVEY DATA OF DEVELOPING CITIES
Authors: Sekimoto Y. , Watanabe A. , Nakamura T. , Horanont T.
Published: August 2012

Abstract. Data on people flow has become increasingly important in the field of business, including the areas of marketing and public services. Although mobile phones enable a person's position to be located to a certain degree, it is a challenge to acquire sufficient data from people with mobile phones. In order to grasp people flow in its entirety, it is important to establish a practical method of reconstructing people flow from various kinds of existing fragmentary spatio-temporal data such as social survey data. For example, despite typical Person Trip Survey Data collected by the public sector showing the fragmentary spatio-temporal positions accessed, the data are attractive given the sufficiently large sample size to estimate the entire flow of people. In this study, we apply our proposed basic method to Japan International Cooperation Agency (JICA) PT data pertaining to developing cities around the world, and we propose some correction methods to resolve the difficulties in applying it to many cities and stably to infrastructure data.
MULTI-LEVEL BUILDING RECONSTRUCTION FOR AUTOMATIC ENHANCEMENT OF HIGH RESOLUTION DSMS
Authors: Arefi H. , Reinartz P.
Published: August 2012

Abstract. In this article a multi-level approach is proposed for reconstruction-based improvement of high resolution Digital Surface Models (DSMs). The concept of Levels of Detail (LOD) defined by CityGML standard has been considered as basis for abstraction levels of building roof structures. Here, the LOD1 and LOD2 which are related to prismatic and parametric roof shapes are reconstructed. Besides proposing a new approach for automatic LOD1 and LOD2 generation from high resolution DSMs, the algorithm contains two generalization levels namely horizontal and vertical. Both generalization levels are applied to prismatic model of buildings. The horizontal generalization allows controlling the approximation level of building footprints which is similar to cartographic generalization concept of the urban maps. In vertical generalization, the prismatic model is formed using an individual building height and continuous to included all flat structures locating in different height levels. The concept of LOD1 generation is based on approximation of the building footprints into rectangular or non-rectangular polygons. For a rectangular building containing one main orientation a method based on Minimum Bounding Rectangle (MBR) in employed. In contrast, a Combined Minimum Bounding Rectangle (CMBR) approach is proposed for regularization of non-rectilinear polygons, i.e. buildings without perpendicular edge directions. Both MBRand CMBR-based approaches are iteratively employed on building segments to reduce the original building footprints to a minimum number of nodes with maximum similarity to original shapes. A model driven approach based on the analysis of the 3D points of DSMs in a 2D projection plane is proposed for LOD2 generation. Accordingly, a building block is divided into smaller parts according to the direction and number of existing ridge lines. The 3D model is derived for each building part and finally, a complete parametric model is formed by merging all the 3D models of the individual parts and adjusting the nodes after the merging step. In order to provide an enhanced DSM, a surface model is provided for each building by interpolation of the internal points of the generated models. All interpolated models are situated on a Digital Terrain Model (DTM) of corresponding area to shape the enhanced DSM. Proposed DSM enhancement approach has been tested on a dataset from Munich central area. The original DSM is created using robust stereo matching of Worldview-2 stereo images. A quantitative assessment of the new DSM by comparing the heights of the ridges and eaves shows a standard deviation of better than 50cm.
EVALUATION OF PENALTY FUNCTIONS FOR SEMI-GLOBAL MATCHING COST AGGREGATION
Authors: Banz C. , Pirsch P. , Blume H.
Published: August 2012

Abstract. The stereo matching method semi-global matching (SGM) relies on consistency constraints during the cost aggregation which are enforced by so-called penalty terms. This paper proposes new and evaluates four penalty functions for SGM. Due to mutual dependencies, two types of matching cost calculation, census and rank transform, are considered. Performance is measured using original and degenerated images exhibiting radiometric changes and noise from the Middlebury benchmark. The two best performing penalty functions are inversely proportional and negatively linear to the intensity gradient and perform equally with 6.05% and 5.91% average error, respectively. The experiments also show that adaptive penalty terms are mandatory when dealing with difficult imaging conditions. Consequently, for highest algorithmic performance in real-world systems, selection of a suitable penalty function and thorough parametrization with respect to the expected image quality is essential.
QUALITY MONITORING OF LARGE STEEL BUILDINGS USING TERRESTRIAL LIDAR TECHNIQUE
Authors: Wang Y. , Wang G.
Published: August 2012

Abstract. Terrestrial LIDAR Technology is used for quality monitoring in construction of large-scale steel buildings to solve the problem of quick and precise inspecting for large steel structure. Point Cloud is acquired fast and of high accuracy with tie-control points that set in different blocks. Feature points are extracted from scan data and compared with its reference points designed to analyze its variation of position and size, which has active guidance meaning for engineering construction. Finally three applications are given to prove the effectiveness of the method proposed.
STUDY ON THE FEASIBILITY OF RGB SUBSTITUTE CIR FOR AUTOMATIC REMOVAL VEGETATION OCCLUSION BASED ON GROUND CLOSE-RANGE BUILDING IMAGES
Authors: Li C. , Li F. , Liu Y. , Li X. , Liu P. , Xiao B.
Published: August 2012

Abstract. Building 3D reconstruction based on ground remote sensing data (image, video and lidar) inevitably faces the problem that buildings are always occluded by vegetation, so how to automatically remove and repair vegetation occlusion is a very important preprocessing work for image understanding, compute vision and digital photogrammetry. In the traditional multispectral remote sensing which is achieved by aeronautics and space platforms, the Red and Near-infrared (NIR) bands, such as NDVI (Normalized Difference Vegetation Index), are useful to distinguish vegetation and clouds, amongst other targets. However, especially in the ground platform, CIR (Color Infra Red) is little utilized by compute vision and digital photogrammetry which usually only take true color RBG into account. Therefore whether CIR is necessary for vegetation segmentation or not has significance in that most of close-range cameras don’t contain such NIR band. Moreover, the CIE L*a*b color space, which transform from RGB, seems not of much interest by photogrammetrists despite its powerfulness in image classification and analysis. So, CIE (L, a, b) feature and support vector machine (SVM) is suggested for vegetation segmentation to substitute for CIR. Finally, experimental results of visual effect and automation are given. The conclusion is that it's feasible to remove and segment vegetation occlusion without NIR band. This work should pave the way for texture reconstruction and repair for future 3D reconstruction.
INDEXING OF SATELLITE IMAGES OF DIFFERENT SPATIAL RESOLUTIONS USING MULTI FEATURES
Authors: Luo B. , Jiang S. , Zhang L. , Huang X.
Published: August 2012

Abstract. In this paper, we investigate the issue of the retrievals of remote sensing images with different spatial resolutions by using texture features. Since the texture features extracted on images with different resolutions are not directly comaprable, we use the resolution or scale invariance of the texture features to make them comparable. Image retrieval experiments are carried out on the database composed by SPOT images at two different resolutions.
ROAD DETECTION BY NEURAL AND GENETIC ALGORITHM IN URBAN ENVIRONMENT
Authors: Barsi A.
Published: August 2012

Abstract. In the urban object detection challenge organized by the ISPRS WG III/4 high geometric and radiometric resolution aerial images about Vaihingen/Stuttgart, Germany are distributed. The acquired data set contains optical false color, near infrared images and airborne laserscanning data. The presented research focused exclusively on the optical image, so the elevation information was ignored. The road detection procedure has been built up of two main phases: a segmentation done by neural networks and a compilation made by genetic algorithms. The applied neural networks were support vector machines with radial basis kernel function and self-organizing maps with hexagonal network topology and Euclidean distance function for neighborhood management. The neural techniques have been compared by hyperbox classifier, known from the statistical image classification practice. The compilation of the segmentation is realized by a novel application of the common genetic algorithm and by differential evolution technique. The genes were implemented to detect the road elements by evaluating a special binary fitness function. The results have proven that the evolutional technique can automatically find major road segments.
LIBRJMCMC: AN OPEN-SOURCE GENERIC C++ LIBRARY FOR STOCHASTIC OPTIMIZATION
Authors: Brédif M. , Tournaire O.
Published: August 2012

Abstract. The librjmcmc is an open source C++ library that solves optimization problems using a stochastic framework. The library is primarily intended for but not limited to research purposes in computer vision, photogrammetry and remote sensing, as it has initially been developed in the context of extracting building footprints from digital elevation models using a marked point process of rectangles. It has been designed to be both highly modular and extensible, and have computational times comparable to a code specifically designed for a particular application, thanks to the powerful paradigms of metaprogramming and generic programming. The proposed stochastic optimization is built on the coupling of a stochastic Reversible-Jump Markov Chain Monte Carlo (RJMCMC) sampler and a simulated annealing relaxation. This framework allows, with theoretical guarantees, the optimization of an unrestricted objective function without requiring any initial solution. The modularity of our library allows the processing of any kind of input data, whether they are 1D signals (e.g. LiDAR or SAR waveforms), 2D images, 3D point clouds... The library user has just to define a few modules describing its domain specific context: the encoding of a configuration (e.g. its object type in a marked point process context), reversible jump kernels (e.g. birth, death, modifications...), the optimized energies (e.g. data and regularization terms) and the probabilized search space given by the reference process. Similar to this extensibility in the application domain, concepts are clearly and orthogonally separated such that it is straightforward to customize the convergence test, the temperature schedule, or to add visitors enabling visual feedback during the optimization. The library offers dedicated modules for marked point processes, allowing the user to optimize a Maximum A Posteriori (MAP) criterion with an image data term energy on a marked point process of rectangles.
LEGION SEMENTATION FOR BUILDING EXTRACTION FROM LIDAR BASED DSM DATA
Authors: Liu C. , Shi B. , Yang X. , Li N.
Published: August 2012

Abstract. Recently, a neural oscillator network based on biologically framework named LEGION (Locally Excitatory Globally Inhibitory Oscillator Network), which each oscillator has excitatory lateral connections to the oscillators in its local neighbourhood as well as a connection with a global inhibitor, has been applied to segmentation field. The extended LEGION approach is constructed to extract buildings digital surface model (DSM) generated from LiDAR data. This approach is with no assumption about the underlying structures in DSM data and no prior knowledge regarding the number of regions. Instead of using lateral potential to find a major oscillator block in original way, Gray Level Co-occurence Matrix (GLCM) homogeneity measuring DSM height texture is applied to distinguish buildings from trees and assist to find LEGION leaders in building targets. Alongside the DSM height texture attribure, extended LEGION can extract buildings close to trees automatically. Then a solution of least squares with perpendicularity constraints is put forward to determine regularized rectilinear building boundaries, after tracing and connection the rough building boundaries. In general, the paper presents the concept, algorithms and procedures of the approach. It also gives experimental result of Vaihingen A2 region by the ISPRS text project and another result based on a DSM data of suburban area. The experiment result showed that the proposed method can effectively produce more accurate buildings boundary extraction.
EXTRACTING SEMANTIC BUILDING MODELS FROM AERIAL STEREO IMAGES AND CONVERSION TO CITYGML
Authors: Sengul A.
Published: August 2012

Abstract. The collection of geographic data is of primary importance for the creation and maintenance of a GIS. Traditionally the acquisition of 3D information has been the task of photogrammetry using aerial stereo images. Digital photogrammetric systems employ sophisticated software to extract digital terrain models or to plot 3D objects. The demand for 3D city models leads to new applications and new standards. City Geography Mark-up Language (CityGML), a concept for modelling and exchange of 3D city and landscape models, defines the classes and relations for the most relevant topographic objects in cities and regional models with respect to their geometrical, topological, semantically and topological properties. It now is increasingly accepted, since it fulfils the prerequisites required e.g. for risk analysis, urban planning, and simulations. There is a need to include existing 3D information derived from photogrammetric processes in CityGML databases. In order to filling the gap, this paper reports on a framework transferring data plotted by Erdas LPS and Stereo Analyst for ArcGIS software to CityGML using Safe Software's Feature Manupulate Engine (FME)
MULTIPLE HUMAN TRACKING IN COMPLEX SITUATION BY DATA ASSIMILATION WITH PEDESTRIAN BEHAVIOR MODEL
Authors: Nakanishi W. , Fuse T.
Published: August 2012

Abstract. A new method of multiple human tracking is proposed. The key concept is that to assume a tracking process as a data assimilation process. Despite the importance of understanding pedestrian behavior in public space with regard to achieving more sophisticated space design and flow control, automatic human tracking in complex situation is still challenging when people move close to each other or are occluded by others. For this difficulty, we stochastically combine existing tracking method by image processing with simulation models of walking behavior. We describe a system in a form of general state space model and define the components of the model according to the review on related works. Then we apply the proposed method to the data acquired at the ticket gate of the railway station. We show the high performance of the method, as well as compare the result with other model to present the advantage of integrating the behavior model to the tracking method. We also show the method's ability to acquire passenger flow information such as ticket gate choice and OD data automatically from the tracking result.
AN ALGORITHM FOR COASTLINE DETECTION USING SAR IMAGES
Authors: Acar U. , Bayram B. , Sanli F. B. , Abdikan S. , Sunar F. , Cetin H. I.
Published: August 2012

Abstract. Coastal management requires rapid, up-to-date, and correct information. Thus, coastal movements have primary importance for coastal managers. For monitoring the change of shorelines, remote sensing data are some of the most important information and are utilized for differentiating any detections of change on shorelines. It is possible to monitor coastal changes by extracting the coastline from satellite images. In the literature most of the algorithms developed for optical images have been discussed in detail. In this study, an algorithm which extracts coastlines efficiently and automatically by processing SAR (Synthetic Aperture Radar) satellite images has been developed. A data set of ALOS Palsar image of Fine Beam Double (FBD) HH-HV polarized data has been used. PALSAR image has L-band data, and has a 14 MHz bandwidth and 34.3 degrees look angle. Data were acquired in ascending geometry. Ground resolution of PALSAR image was resampled to 15 m to amplitude image. Zonguldak city, lies on the northwest costs of Turkey, has been selected as the test area. An algorithm was developed for automatic coastline extraction from SAR images. The algorithm is encoded in a C__ environment. To verify the results the algorithm was applied on two PALSAR images gathered in two different date as 2007 and 2010. The results of automatic coastline extraction obtained from SAR images were compared to the results derived from manual digitizing. Random control points which are seen on each image were used. The average differences of selected points were calculated.
REMOVING SHADOWS FROM HIGH-RESOLUTION URBAN AERIAL IMAGES BASED ON COLOR CONSTANCY
Authors: Ye Q. , Xie H. , Xu Q.
Published: August 2012

Abstract. A method is explored to remove tall building shadows in true color and color infrared urban aerial images based on the theory of color constancy. This paper first uses the specthem ratio and Otsu threshold segmentation methods to detect building shadows on urban aerial true color and color infrared aerial images. Then, based on the shadow detection result, one of the color constancy algorithms SoG (Shades of Gray) is used to remove the shadows in aerial images with different p values of the Minkowski norm. Finally, the shadow removal results with different p values have been compared by brightness, contrast and average gradients. The experiments show that the result of this method based on color constancy has a good visual effect, and different from general scene image shadow removal, the aerial images get the best shadow removal result when p is 2. It means the two types of aerial images should not be simply regarded as gray world images.
NATURAL USER INTERFACE SENSORS FOR HUMAN BODY MEASUREMENT
Authors: Boehm J.
Published: August 2012

Abstract. The recent push for natural user interfaces (NUI) in the entertainment and gaming industry has ushered in a new era of low cost three-dimensional sensors. While the basic idea of using a three-dimensional sensor for human gesture recognition dates some years back it is not until recently that such sensors became available on the mass market. The current market leader is PrimeSense who provide their technology for the Microsoft Xbox Kinect. Since these sensors are developed to detect and observe human users they should be ideally suited to measure the human body. We describe the technology of a line of NUI sensors and assess their performance in terms of repeatability and accuracy. We demonstrate the implementation of a prototype scanner integrating several NUI sensors to achieve full body coverage. We present the results of the obtained surface model of a human body.
VHRS STEREO IMAGES FOR 3D MODELLING OF BUILDINGS
Authors: Bujakiewicz A. , Holc M.
Published: August 2012

Abstract. The paper presents the project which was carried out in the Photogrammetric Laboratory of Warsaw University of Technology. The experiment is concerned with the extraction of 3D vector data for buildings creation from 3D photogrammetric model based on the Ikonos stereo images. The model was reconstructed with photogrammetric workstation – Summit Evolution combined with ArcGIS 3D platform. Accuracy of 3D model was significantly improved by use for orientation of pair of satellite images the stereo measured tie points distributed uniformly around the model area in addition to 5 control points. The RMS for model reconstructed on base of the RPC coefficients only were 16,6 m, 2,7 m and 47,4 m, for X, Y and Z coordinates, respectively. By addition of 5 control points the RMS were improved to 0,7 m, 0,7 m 1,0 m, where the best results were achieved when RMS were estimated from deviations in 17 check points (with 5 control points)and amounted to 0,4 m, 0,5 m and 0,6 m, for X, Y, and Z respectively. The extracted 3D vector data for buildings were integrated with 2D data of the ground footprints and afterwards they were used for 3D modelling of buildings in Google SketchUp software. The final results were compared with the reference data obtained from other sources. It was found that the shape of buildings (in concern to the number of details) had been reconstructed on level of LoD1, when the accuracy of these models corresponded to the level of LoD2.
ANALYSIS OF THE EFFECTS OF IMAGE QUALITY ON DIGITAL MAP GENERATION FROM SATELLITE IMAGES
Authors: Kim H. , Kim D. , Kim S. , Kim T.
Published: August 2012

Abstract. High resolution satellite images are widely used to produce and update a digital map since they became widely available. It is well known that the accuracy of digital map produced from satellite images is decided largely by the accuracy of geometric modelling. However digital maps are made by a series of photogrammetric workflow. Therefore the accuracy of digital maps are also affected by the quality of satellite images, such as image interpretability. For satellite images, parameters such as Modulation Transfer Function(MTF), Signal to Noise Ratio(SNR) and Ground Sampling Distance(GSD) are used to present images quality. Our previous research stressed that such quality parameters may not represent the quality of image products such as digital maps and that parameters for image interpretability such as Ground Resolved Distance(GRD) and National Imagery Interpretability Rating Scale(NIIRS) need to be considered. In this study, we analyzed the effects of the image quality on accuracy of digital maps produced by satellite images. QuickBird, IKONOS and KOMPSAT-2 imagery were used to analyze as they have similar GSDs. We measured various image quality parameters mentioned above from these images. Then we produced digital maps from the images using a digital photogrammetric workstation. We analyzed the accuracy of the digital maps in terms of their location accuracy and their level of details. Then we compared the correlation between various image quality parameters and the accuracy of digital maps. The results of this study showed that GRD and NIIRS were more critical for map production then GSD, MTF or SNR.