834 research outputs found

    Semi-automatic 3D reconstruction of urban areas using epipolar geometry and template matching

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    WOS:000240143800002 (Nº de Acesso Web of Science)In this work we describe a novel technique for semi-automatic three-dimensional (3D) reconstruction of urban areas, from airborne stereo-pair images whose output is VRML or DXF. The main challenge is to compute the relevant information—building's height and volume, roof's description, and texture—algorithmically, because it is very time consuming and thus expensive to produce it manually for large urban areas. The algorithm requires some initial calibration input and is able to compute the above-mentioned building characteristics from the stereo pair and the availability of the 2D CAD and the digital elevation model of the same area, with no knowledge of the camera pose or its intrinsic parameters. To achieve this, we have used epipolar geometry, homography computation, automatic feature extraction and we have solved the feature correspondence problem in the stereo pair, by using template matching

    A Framework for SAR-Optical Stereogrammetry over Urban Areas

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    Currently, numerous remote sensing satellites provide a huge volume of diverse earth observation data. As these data show different features regarding resolution, accuracy, coverage, and spectral imaging ability, fusion techniques are required to integrate the different properties of each sensor and produce useful information. For example, synthetic aperture radar (SAR) data can be fused with optical imagery to produce 3D information using stereogrammetric methods. The main focus of this study is to investigate the possibility of applying a stereogrammetry pipeline to very-high-resolution (VHR) SAR-optical image pairs. For this purpose, the applicability of semi-global matching is investigated in this unconventional multi-sensor setting. To support the image matching by reducing the search space and accelerating the identification of correct, reliable matches, the possibility of establishing an epipolarity constraint for VHR SAR-optical image pairs is investigated as well. In addition, it is shown that the absolute geolocation accuracy of VHR optical imagery with respect to VHR SAR imagery such as provided by TerraSAR-X can be improved by a multi-sensor block adjustment formulation based on rational polynomial coefficients. Finally, the feasibility of generating point clouds with a median accuracy of about 2m is demonstrated and confirms the potential of 3D reconstruction from SAR-optical image pairs over urban areas.Comment: This is the pre-acceptance version, to read the final version, please go to ISPRS Journal of Photogrammetry and Remote Sensing on ScienceDirec

    Detecting shadows and low-lying objects in indoor and outdoor scenes using homographies

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    Many computer vision applications apply background suppression techniques for the detection and segmentation of moving objects in a scene. While these algorithms tend to work well in controlled conditions they often fail when applied to unconstrained real-world environments. This paper describes a system that detects and removes erroneously segmented foreground regions that are close to a ground plane. These regions include shadows, changing background objects and other low-lying objects such as leaves and rubbish. The system uses a set-up of two or more cameras and requires no 3D reconstruction or depth analysis of the regions. Therefore, a strong camera calibration of the set-up is not necessary. A geometric constraint called a homography is exploited to determine if foreground points are on or above the ground plane. The system takes advantage of the fact that regions in images off the homography plane will not correspond after a homography transformation. Experimental results using real world scenes from a pedestrian tracking application illustrate the effectiveness of the proposed approach

    Depth Recovery with Rectification using Single-Lens Prism based Stereovision System

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    Ph.DDOCTOR OF PHILOSOPH
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