Browsing by Subject "Classification"

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  • 3D classification of crossroads from multiple aerial images using markov random fields 
    Kosov, Sergej; Rottensteiner, Franz; Heipke, Christian; Leitloff, Jens; Hinz, Stefan (Göttingen : Copernicus GmbH, 2012)
    The precise classification and reconstruction of crossroads from multiple aerial images is a challenging problem in remote sensing. We apply the Markov Random Fields (MRF) approach to this problem, a probabilistic model ...
  • The application of a car confidence feature for the classification of cross-roads using conditional random fields 
    Kosov, Sergej; Rottensteiner, Franz; Heipke, Christian; Leitloff, Jens; Hinz, Stefan (Göttingen : Copernicus GmbH, 2013)
    The precise classification and reconstruction of crossroads from multiple aerial images is a challenging problem in remote sensing. We apply the Conditional Random Fields (CRF) approach to this problem, a probabilistic ...
  • Automatic classification of aerial imagery for urban hydrological applications 
    Paul, A.; Yang, C.; Breitkopf, U.; Liu, Y.; Wang, Z.; Rottensteiner, F.; Wallner, M.; Verworn, A.; Heipke, C. (London : International Society for Photogrammetry and Remote Sensing, 2018)
    In this paper we investigate the potential of automatic supervised classification for urban hydrological applications. In particular, we contribute to runoff simulations using hydrodynamic urban drainage models. In order ...
  • Comparing satellite- to ground-based automated and manual cloud coverage observations – a case study 
    Werkmeister, Astrid; Lockhoff, M.; Schrempf, Michael; Tohsing, Korntip; Liley, B.; Seckmeyer, Gunther (Göttingen : Copernicus, 2015-05-06)
    In this case study we compare cloud fractional cover measured by radiometers on polar satellites (AVHRR) and on one geostationary satellite (SEVIRI) to ground-based manual (SYNOP) and automated observations by a cloud ...
  • Conditional random fields for the classification of lidar point clouds 
    Niemeyer, Joachim; Mallet, C.; Rottensteiner, Franz; Sörgel, Uwe (Göttingen : Copernicus GmbH, 2011)
    In this paper we propose a probabilistic supervised classification algorithm for LiDAR (Light Detection And Ranging) point clouds. Several object classes (i.e. ground, building and vegetation) can be separated reliably by ...
  • Contextual classification of point cloud data by exploiting individual 3d neigbourhoods 
    Weinmann, M.; Schmidt, Alena; Mallet, C.; Hinz, Stefan; Rottensteiner, Franz; Jutzi, B. (Göttingen : Copernicus GmbH, 2015)
    The fully automated analysis of 3D point clouds is of great importance in photogrammetry, remote sensing and computer vision. For reliably extracting objects such as buildings, road inventory or vegetation, many approaches ...
  • Contextual classification of point clouds using a two-stage CRF 
    Niemeyer, Joachim; Rottensteiner, Franz; Sörgel, Uwe; Heipke, Christian (Hannover : International Society for Photogrammetry and Remote Sensing, 2015)
    In this investigation, we address the task of airborne LiDAR point cloud labelling for urban areas by presenting a contextual classification methodology based on a Conditional Random Field (CRF). A two-stage CRF is set up: ...
  • A dynamic Bayes Network for visual pedestrian tracking 
    Klinger, Tobias; Rottensteiner, Franz; Heipke, Christian (Hannover : International Society for Photogrammetry and Remote Sensing, 2014)
    Many tracking systems rely on independent single frame detections that are handled as observations in a recursive estimation framework. If these observations are imprecise the generated trajectory is prone to be updated ...
  • Hierarchical higher order crf for the classification of airborne lidar point clouds in urban areas 
    Niemeyer, Joachim; Rottensteiner, Franz; Sörgel, Uwe; Heipke, Christian (Göttingen : Copernicus GmbH, 2016)
    We propose a novel hierarchical approach for the classification of airborne 3D lidar points. Spatial and semantic context is incorporated via a two-layer Conditional Random Field (CRF). The first layer operates on a point ...
  • Implementation of Machine Learning to Improve the Decision-Making Process of End-of-Usage Products in the Circular Economy 
    Diem, Michael; Braun, Anja; Louw, Louis (Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2020)
    Rising consumption due to a growing world population and increasing prosperity, combined with a linear economic system have led to a sharp increase in garbage collection, general pollution of the environment and the threat ...
  • Improved classification of satellite imagery using spatial feature maps extracted from social media 
    Leichter, Artem; Wittich, Dennis; Rottensteiner, Franz; Werner, Martin; Sester, Monika (London : International Society for Photogrammetry and Remote Sensing, 2018)
    In this work, we consider the exploitation of social media data in the context of Remote Sensing and Spatial Information Sciences. To this end, we explore a way of augmenting and integrating information represented by ...
  • Improved Synthesis of Global Irradiance with One-Minute Resolution for PV System Simulations 
    Hofmann, Martin; Riechelmann, Stefan; Crisosto, Christian; Mubarak, Riyad; Seckmeyer, Gunther (New York : Hindawi Publishing Corporation, 2014-11-26)
    High resolution global irradiance time series are needed for accurate simulations of photovoltaic (PV) systems, since the typical volatile PV power output induced by fast irradiance changes cannot be simulated properly ...
  • Land use classification with high-resolution satellite radar for estimating the impacts of land use change on the quality of ecosystem services 
    Bargiel, Damian; Herrmann, Sylvia; Lohmann, P.; Sörgel, Uwe (Göttingen : Copernicus GmbH, 2010)
    Ecosystems provide several services for human well-being. The quality of these ecosystem services is among others affected by agriculture, the main land user in Europe. Thus, it is essential to provide information about ...
  • Monitoring concepts for coastal areas using lidar data 
    Schmidt, Alena; Rottensteiner, Franz; Sörgel, Uwe (Hannover : International Society for Photogrammetry and Remote Sensing, 2013)
    Coastal areas are characterized by high spatial and temporal variability. In order to detect undesired changes at early stages, enabling rapid countermeasures to mitigate or minimize potential harm or hazard, a recurrent ...
  • Multi-source multi-scale hierarchical conditional random field model for remote sensing image classification 
    Zhang, Z.; Yang, M.Y.; Zhou, M. (Göttingen : Copernicus GmbH, 2015)
    Fusion of remote sensing images and LiDAR data provides complimentary information for the remote sensing applications, such as object classification and recognition. In this paper, we propose a novel multi-source multi-scale ...
  • Multi-stage approach to travel-mode segmentation and classification of gps traces 
    Zhang, Lijuan; Dalyot, Sagi; Eggert, Daniel; Sester, Monika (Göttingen : Copernicus GmbH, 2011)
    This paper presents a multi-stage approach toward the robust classification of travel-modes from GPS traces. Due to the fact that GPS traces are often composed of more than one travel-mode, they are segmented to find ...
  • Multiple-model based update of belgian reference road data 
    Ziems, Marcel; Beyen, J.; Müller, Sönke; Roovers, S.; Heipke, Christian (Göttingen : Copernicus GmbH, 2011)
    This paper describes a semi-automatic system for road update based on high resolution orthophotos and 3D surface models. Potential update regions are identified by an object-wise verification of all existing database ...
  • Multiple-model based verification of japanese road data 
    Ziems, M.; Fujimura, H.; Heipke, Christian; Rottensteiner, Franz (London : International Society for Photogrammetry and Remote Sensing, 2010)
    This paper describes a semi-automatic system for road verification from high resolution orthophotos in an urban context. The system combines several road detection and road verification approaches from current literature ...
  • Multitemporal crop type classification using conditional random fields and rapideye data 
    Hoberg, Thorsten; Müller, Sören (Göttingen : Copernicus GmbH, 2011)
    The task of crop type classification with multitemporal imagery is nowadays often done applying classifiers that are originally developed for single images like support vector machines (SVM). These approaches do not model ...
  • Multitemporal interpretation of remote sensing data 
    Müller, Sönke; Mota, Guilherme Lucio Abelha; Liedtke, Claus-Eberhard (London : International Society for Photogrammetry and Remote Sensing, 2004)
    The automated interpretation of aerial image data is a task with increasing significance for several applications, e.g. quality control and automatic updating of GIS data, automatic land use change detection, measurement ...