Auflistung nach Schlagwort "Image matching"

Sortiert nach: Sortierung: Ergebnisse:

  • 3D building change detection using high resolution stereo images and a GIS database 
    Dini, G.R.; Jacobsen, Karsten; Rottensteiner, Franz; Al Rajhi, M.; Heipke, Christian (Göttingen : Copernicus GmbH, 2012)
    In this paper, a workflow is proposed to detect 3D building changes in urban and sub-urban areas using high-resolution stereoscopic satellite images of different epochs and a GIS database. Semi-global matching (SGM) is ...
  • 3D feature point extraction from LiDAR data using a neural network 
    Feng, Yu; Schlichting, Alexander; Brenner, Claus (Göttingen : Copernicus GmbH, 2016)
    Accurate positioning of vehicles plays an important role in autonomous driving. In our previous research on landmark-based positioning, poles were extracted both from reference data and online sensor data, which were then ...
  • Delineation of building footprints from high resolution satellite stereo imagery using image matching and a GIS database 
    Dini, Gholam Reza; Jacobsen, Karsten; Heipke, Christian (Göttingen : Copernicus GmbH, 2013)
    In this paper, a workflow is proposed to delineate building footprints from high resolution satellite stereo images through integration of a Digital Surface Model (DSM), 3D edge matching technique and GIS building polygons. ...
  • DEM generation with short base length pleiades triplet 
    Jacobsen, Karsten; Topan, H. (Göttingen : Copernicus GmbH, 2015)
    An image triplet of Pleiades images covering the area of Zonguldak, Turkey has been investigated. The height to base relation of the first to the last image is just 1:4.5 and for the first and the second image 1:9. This ...
  • Exploring ALS and DIM data for semantic segmentation using CNNs 
    Politz, F.; Sester, M. (Katlenburg-Lindau : Copernicus Publications, 2018)
    Over the past years, the algorithms for dense image matching (DIM) to obtain point clouds from aerial images improved significantly. Consequently, DIM point clouds are now a good alternative to the established Airborne ...
  • Feature descriptor by convolution and pooling autoencoders 
    Chen, Lin; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2015)
    In this paper we present several descriptors for feature-based matching based on autoencoders, and we evaluate the performance of these descriptors. In a training phase, we learn autoencoders from image patches extracted ...
  • Feature detection and description for image matching: from hand-crafted design to deep learning 
    Chen, Lin; Rottensteiner, Franz; Heipke, Christian (Wuhan : Wuhan Univ. Journals Press, 2020)
    In feature based image matching, distinctive features in images are detected and represented by feature descriptors. Matching is then carried out by assessing the similarity of the descriptors of potentially conjugate ...
  • Guiding Deep Learning with Expert Knowledge for Dense Stereo Matching 
    Iqbal, Waseem; Paffenholz, Jens-André; Mehltretter, Max ([Cham] : Springer International Publishing, 2023)
    Dense depth information can be reconstructed from stereo images using conventional hand-crafted as well as deep learning-based approaches. While deep-learning methods often show superior results compared to hand-crafted ...
  • Integration of prior knowledge into dense image matching for video surveillance 
    Menze, Moritz; Heipke, Christian (Göttingen : Copernicus GmbH, 2014)
    Three-dimensional information from dense image matching is a valuable input for a broad range of vision applications. While reliable approaches exist for dedicated stereo setups they do not easily generalize to more ...
  • Joint classification of ALS and DIM point clouds 
    Politz, F.; Sester, M. (Göttingen : Copernicus GmbH, 2019)
    National mapping agencies (NMAs) have to acquire nation-wide Digital Terrain Models on a regular basis as part of their obligations to provide up-to-date data. Point clouds from Airborne Laser Scanning (ALS) are an important ...
  • Learning image descriptors for matching based on Haar features 
    Chen, Lin; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2014)
    This paper presents a new and fast binary descriptor for image matching learned from Haar features. The training uses AdaBoost; the weak learner is built on response function for Haar features, instead of histogram-type ...
  • Orientation of oblique airborne image sets - Experiences from the ISPRS/Eurosdr benchmark on multi-platform photogrammetry 
    Gerke, M.; Nex, F.; Remondino, F.; Jacobsen, Karsten; Kremer, J.; Karel, W.; Huf, H.; Ostrowski, W. (Göttingen : Copernicus GmbH, 2016)
    During the last decade the use of airborne multi camera systems increased significantly. The development in digital camera technology allows mounting several mid- or small-format cameras efficiently onto one platform and ...
  • A procedure for semi-automatic orthophoto generation from high resolution satellite imagery 
    Alrajhi, M.N.; Jacobsen, Karsten; Heipke, Christian (Göttingen : Copernicus GmbH, 2013)
    The General Directorate of Surveying and Mapping (GDSM), under the Ministry of Municipal and Rural Affairs (MOMRA) is responsible for the production and dissemination of accurate geospatial data for all the metropolitan ...
  • A stereo line matching technique for aerial images based on a pair-wise relation approach 
    Ok, A.O.; Wegner, Jan Dirk; Heipke, Christian; Rottensteiner, Franz; Sörgel, Uwe; Toprak, V. (Hannover : International Society for Photogrammetry and Remote Sensing, 2010)
    In this study, we developed a new pair-wise relation based approach for the matching of line features from stereo aerial images. To solve the final matching inconsistencies, we propose an iterative pair based post-processing ...
  • Vehicle localization by lidar point correlation improved by change detection 
    Schlichting, Alexander; Brenner, Claus (Göttingen : Copernicus GmbH, 2016)
    LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like ...