Auflistung Fakultät für Bauingenieurwesen und Geodäsie nach Autor/in "Paparoditis, N."

Auflistung Fakultät für Bauingenieurwesen und Geodäsie nach Autor/in "Paparoditis, N."

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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 ...
  • Classification of airborne laser scanning data in wadden sea areas using conditional random fields 
    Schmidt, Alena; Rottensteiner, Franz; Sörgel, Uwe (Göttingen : Copernicus GmbH, 2012)
    In this paper we investigate the influence of contextual knowledge for the classification of airborne laser scanning data in Wadden Sea areas. For this propose we use Conditional Random Fields (CRF) for the classification ...
  • Context-based urban terrain reconstruction from images and videos 
    Bulatov, Dimitri; Rottensteiner, Franz; Schulz, Karsten (Göttingen : Copernicus GmbH, 2012)
    Detection of buildings and vegetation, and even more reconstruction of urban terrain from sequences of aerial images and videos is known to be a challenging task. It has been established that those methods that have as ...
  • A dynamic Bayes Network for visual pedestrian tracking 
    Klinger, Tobias; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 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 ...
  • Exploring cloud-based platforms for rapid insar time series analysis 
    Piter, A.; Vassileva, M.; Haghshenas Haghighi, M.; Motagh, M. (Katlenburg-Lindau : Copernicus Publications, 2021)
    The idea of near real-time deformation analysis using Synthetic Aperture Radar (SAR) data as a response to natural and anthropogenic disasters has been an interesting topic in the last years. A major limiting factor for ...
  • Extraction of fluvial networks in lidar data using marked point processes 
    Schmidt, Alena; Rottensteiner, Franz; Sörgel, Uwe; Heipke, Christian (Göttingen : Copernicus GmbH, 2014)
    We propose a method for the automatic extraction of fluvial networks in lidar data with the aim to obtain a connected network represented by the fluvial channels' skeleton. For that purpose we develop a two-step approach. ...
  • A global approach for image orientation using Lie algebraic rotation averaging and convex L∞ minimisation 
    Reich, Martin; Heipke, Christian (Göttingen : Copernicus GmbH, 2014)
    In this paper we present a new global image orientation approach for a set of multiple overlapping images with given homologous point tuples which is based on a two-step procedure. The approach is independent on initial ...
  • Global rotation estimation using weighted iterative lie algebraic averaging 
    Reich, Martin; Heipke, Christian (Göttingen : Copernicus GmbH, 2015)
    In this paper we present an approach for a weighted rotation averaging to estimate absolute rotations from relative rotations between two images for a set of multiple overlapping images. The solution does not depend on ...
  • A graph based model for the detection of tidal channels using marked point processes 
    Schmidt, Alena; Rottensteiner, Franz; Sörgel, Uwe; Heipke, Christian (Göttingen : Copernicus GmbH, 2015)
    In this paper we propose a new method for the automatic extraction of tidal channels in digital terrain models (DTM) using a sampling approach based on marked point processes. In our model, the tidal channel system is ...
  • Impact analysis of accidents on the traffic flow based on massive floating car data 
    Golze, J.; Feuerhake, U.; Koetsier, C.; Sester, M. (Katlenburg-Lindau : Copernicus Publications, 2021)
    The wide usage of GPS-equipped devices enables the mass recording of vehicle movement trajectories describing the movement behavior of the traffic participants. An important aspect of the road traffic is the impact of ...
  • 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 ...
  • The ISPRS benchmark on urban object classification and 3d building reconstruction 
    Rottensteiner, Franz; Sohn, Gunho; Jung, Jaewook; Gerke, Markus; Baillard, Caroline; Benitez, Sebastien; Breitkopf, Uwe (Göttingen : Copernicus GmbH, 2012)
    For more than two decades, many efforts have been made to develop methods for extracting urban objects from data acquired by airborne sensors. In order to make the results of such algorithms more comparable, benchmarking ...
  • 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 ...
  • Network snakes for adapting GIS roads to height data of different data sources - performance analysis using als data and stereo images 
    Göpfert, Jens; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2012)
    In order to tackle the problem of consistently integrating 2D vector data and a DTM, we presented an approach for the adaptation of 2D GIS road objects to airborne laser scanning (ALS) data using active contours (snakes) ...
  • Octree-based SIMD strategy for ICP registration and alignment of 3d point clouds 
    Eggert, D.; Dalyot, S. (Göttingen : Copernicus GmbH, 2012)
    Matching and fusion of 3D point clouds, such as close range laser scans, is important for creating an integrated 3D model data infrastructure. The Iterative Closest Point algorithm for alignment of point clouds is one of ...
  • Persistent object tracking with randomized forests 
    Klinger, Tobias; Muhle, Daniel (Göttingen : Copernicus GmbH, 2012)
    Our work addresses the problem of long-term visual people tracking in complex environments. Tracking a varying number of objects entails the problem of associating detected objects to tracked targets. To overcome the data ...
  • Probabilistic multi-person tracking using dynamic bayes networks 
    Klinger, Tobias; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2015)
    Tracking-by-detection is a widely used practice in recent tracking systems. These usually rely on independent single frame detections that are handled as observations in a recursive estimation framework. If these observations ...
  • Transfer learning based on logistic regression 
    Paul, Andreas; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2015)
    In this paper we address the problem of classification of remote sensing images in the framework of transfer learning with a focus on domain adaptation. The main novel contribution is a method for transductive transfer ...
  • A two-layer Conditional Random Field model for simultaneous classification of land cover and land use 
    Albert, Lena; Rottensteiner, Franz; Heipke, Christian (Göttingen : Copernicus GmbH, 2014)
    This paper proposes a two-layer Conditional Random Field model for simultaneous classification of land cover and land use. Both classification tasks are integrated into a unified graphical model, which is reasonable due ...
  • Using stereo vision to support the automated analysis of surveillance videos 
    Menze, Moritz; Muhle, Daniel (Göttingen : Copernicus GmbH, 2012)
    Video surveillance systems are no longer a collection of independent cameras, manually controlled by human operators. Instead, smart sensor networks are developed, able to fulfil certain tasks on their own and thus supporting ...

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