730 resultados para Stereo-Photogrammetry
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In this paper we propose a novel fully probabilistic solution to the stereo egomotion estimation problem. We extend the notion of probabilistic correspondence to the stereo case which allow us to compute the whole 6D motion information in a probabilistic way. We compare the developed approach against other known state-of-the-art methods for stereo egomotion estimation, and the obtained results compare favorably both for the linear and angular velocities estimation.
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On December 4th 2007, a 3-Mm3 landslide occurred along the northwestern shore of Chehalis Lake. The initiation zone is located at the intersection of the main valley slope and the northern sidewall of a prominent gully. The slope failure caused a displacement wave that ran up to 38 m on the opposite shore of the lake. The landslide is temporally associated with a rain-on-snow meteorological event which is thought to have triggered it. This paper describes the Chehalis Lake landslide and presents a comparison of discontinuity orientation datasets obtained using three techniques: field measurements, terrestrial photogrammetric 3D models and an airborne LiDAR digital elevation model to describe the orientation and characteristics of the five discontinuity sets present. The discontinuity orientation data are used to perform kinematic, surface wedge limit equilibrium and three-dimensional distinct element analyses. The kinematic and surface wedge analyses suggest that the location of the slope failure (intersection of the valley slope and a gully wall) has facilitated the development of the unstable rock mass which initiated as a planar sliding failure. Results from the three-dimensional distinct element analyses suggest that the presence, orientation and high persistence of a discontinuity set dipping obliquely to the slope were critical to the development of the landslide and led to a failure mechanism dominated by planar sliding. The three-dimensional distinct element modelling also suggests that the presence of a steeply dipping discontinuity set striking perpendicular to the slope and associated with a fault exerted a significant control on the volume and extent of the failed rock mass but not on the overall stability of the slope.
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In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence
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Catadioptric sensors are combinations of mirrors and lenses made in order to obtain a wide field of view. In this paper we propose a new sensor that has omnidirectional viewing ability and it also provides depth information about the nearby surrounding. The sensor is based on a conventional camera coupled with a laser emitter and two hyperbolic mirrors. Mathematical formulation and precise specifications of the intrinsic and extrinsic parameters of the sensor are discussed. Our approach overcomes limitations of the existing omni-directional sensors and eventually leads to reduced costs of production
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This research involved two studies: one to determine the local geoid to obtain mean sea level elevation from a global positioning system (GPS) to an accuracy of ±2 cm, and the other to determine the location of roadside features such as mile posts and stop signs for safety studies, geographic information systems (GIS), and maintenance applications, from video imageries collected by a van traveling at traffic speed.
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In this work we propose a new automatic methodology for computing accurate digital elevation models (DEMs) in urban environments from low baseline stereo pairs that shall be available in the future from a new kind of earth observation satellite. This setting makes both views of the scene similarly, thus avoiding occlusions and illumination changes, which are the main disadvantages of the commonly accepted large-baseline configuration. There still remain two crucial technological challenges: (i) precisely estimating DEMs with strong discontinuities and (ii) providing a statistically proven result, automatically. The first one is solved here by a piecewise affine representation that is well adapted to man-made landscapes, whereas the application of computational Gestalt theory introduces reliability and automation. In fact this theory allows us to reduce the number of parameters to be adjusted, and tocontrol the number of false detections. This leads to the selection of a suitable segmentation into affine regions (whenever possible) by a novel and completely automatic perceptual grouping method. It also allows us to discriminate e.g. vegetation-dominated regions, where such an affine model does not apply anda more classical correlation technique should be preferred. In addition we propose here an extension of the classical ”quantized” Gestalt theory to continuous measurements, thus combining its reliability with the precision of variational robust estimation and fine interpolation methods that are necessary in the low baseline case. Such an extension is very general and will be useful for many other applications as well.
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Five test flights were conducted to study the use of Global Positioning System (GPS) in Photogrammetry, three in Iowa, one each in California and Texas. These tests show that GPS can be used to establish ground control by the static method and to determine camera location by the kinematic method. In block triangulation, six GPS controls are required and additional elevation control along the centerline is also required in strip triangulation. The camera location determined by aerial triangulation depends on the scale of the photography. The 1:3000 scale photography showed that the absolute accuracy of the camera location by GPS is better than five centimeters. The 1:40000 scale photography showed that the relative accuracy of the camera location by GPS is about one millimeter. In a strip triangulation elevation control is required in addition to the camera location by GPS. However, for block triangulation camera location by GPS is sufficient. Pre-targeting of pass and tie points gives the best results in both block and strip triangulation. In normal mapping for earth work computations the use of 1:6000 scale photography with GPS control instead of 1:3000 scale is recommended. It is recommended that research be done in the use of GPS for navigation in aerial photographic missions. It is highly recommended that research be done in the use of GPS to determine tip and tilt of the aerial camera, that is required in stereoplotting.
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The objective of this project was to use a Global Positioning System (GPS) to determine the aerial camera location and orientation that best facilitated mapping done from aerial photographs without any ground control. Four test flights were conducted. The first test flight was performed in June 1993 at St. Louis, with the objective of testing the multiantenna concept using two antenna on the aircraft. The second test in August 1993 was conducted over the Iowa State University (ISU) campus at Ames. This flight evaluated the use of GPS for pinpoint navigation. The third test flight over St. Louis was flown in October 1993, with four antenna on aircraft; its objective was to evaluate the 3DF GPS receiver and the antenna locations. On the basis of the results of these three tests, a final test flight over the Mustang Project area in Ames and the ISU campus was conducted in June 1994. Analysis of these data showed that airborne GPS can be used (1) in pinpoint navigation with an accuracy of 25 m or better, (2) to determine the location of the camera nodal point with an accuracy of 10 cm or better, and (3) to determine the orientation angles of the camera with an accuracy of 0.0001 radians or better. In addition, the exterior orientation elements determined by airborne GPS can be used to rectify aerial photos, to produce orthophotos, and in direct stereo plotting. Further research is recommended in these areas to maximize the use of airborne GPS. The report is organized in the following chapters: (1) Introduction; (2) Photogrammetry and Kinematic GPS; (3) Analysis of First Test; (4) Analysis of Second Test; (5) Analysis of Third Test; (6) Analysis of Final Test; (7) Applications of Airborne GPS; and (8) Conclusion and Recommendation.
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The SoftPlotter, a soft photogrammetric software and Silicon Graphics workstation, was used to evaluate the accuracy of soft photogrammetry and identify applications of this technology to highway engineering. A comparative study showed that SoftPlotter compares well with other software such as Socket and Integraph. The PC software TNTMips is inexpensive but needs further development to be comparable to SoftPlotter. The Campus Project showed that soft photogrammetry is accurate for traditional photogrammetric applications. It is also accurate for producing orthophoto and base maps for Geographic Information Systems (GISs). The Highway Project showed that soft photogrammetry is accurate for highway engineering and that the technical staff at the Iowa Department of Transportation (IA DOT) can be easily trained in this new technology. The research demonstrated that soft photogrammetry can be used with low-flight helicopter photography for large-scale mapping in highway engineering. The researchers recommend that research be conducted to test the use of digital cameras instead of the traditional aerial cameras in helicopter photography. Research that examines the use of soft photogrammetry with video logging imagery for inventory and GIS studies in highway maintenance is also recommended. Research is also warranted into the integration of soft photogrammetry with virtual reality, which can be used in three-dimensional designing and visualization of highways and subdivisions in real time. The IA DOT owns one analytical plotter and two analogue plotters. The analytical plotter is used for aerial triangulation, and the analogue plotters are used for plotting. However, neither is capable of producing orthophotos. Therefore, the researchers recommend that the IA DOT purchase soft photogrammetric workstations for orthophoto production, and if and when required, use it for aerial triangulation and plotting. In the future, the analogue plotters may become obsolete. At that time, the researchers recommend that the analogue plotters be phased out and replaced by soft photogrammetric workstations.
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Abstract
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University of Helsinki, Faculty of Agriculture and Forestry, Department of Forest Resource Management
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In many industrial applications, accurate and fast surface reconstruction is essential for quality control. Variation in surface finishing parameters, such as surface roughness, can reflect defects in a manufacturing process, non-optimal product operational efficiency, and reduced life expectancy of the product. This thesis considers reconstruction and analysis of high-frequency variation, that is roughness, on planar surfaces. Standard roughness measures in industry are calculated from surface topography. A fast and non-contact method to obtain surface topography is to apply photometric stereo in the estimation of surface gradients and to reconstruct the surface by integrating the gradient fields. Alternatively, visual methods, such as statistical measures, fractal dimension and distance transforms, can be used to characterize surface roughness directly from gray-scale images. In this thesis, the accuracy of distance transforms, statistical measures, and fractal dimension are evaluated in the estimation of surface roughness from gray-scale images and topographies. The results are contrasted to standard industry roughness measures. In distance transforms, the key idea is that distance values calculated along a highly varying surface are greater than distances calculated along a smoother surface. Statistical measures and fractal dimension are common surface roughness measures. In the experiments, skewness and variance of brightness distribution, fractal dimension, and distance transforms exhibited strong linear correlations to standard industry roughness measures. One of the key strengths of photometric stereo method is the acquisition of higher frequency variation of surfaces. In this thesis, the reconstruction of planar high-frequency varying surfaces is studied in the presence of imaging noise and blur. Two Wiener filterbased methods are proposed of which one is optimal in the sense of surface power spectral density given the spectral properties of the imaging noise and blur. Experiments show that the proposed methods preserve the inherent high-frequency variation in the reconstructed surfaces, whereas traditional reconstruction methods typically handle incorrect measurements by smoothing, which dampens the high-frequency variation.