PREREQUISITES: Linear Algebra, Calculus, Data Structures Working knowledge of Matlab or C/C++ or willingness + time to pick it up quickly No image processing, computer vision, computer graphics, visualization or cartography experience is assumed


REQUIRED TEXTS: No text books are required.

COURSE INSTRUCTOR: Xin Chen, PhD, Senior Research Scientist, Nokia,  xin.5.chen(at)


  1. Course logistics and introduction; overview of state-of-the-art digital mapping content and location-based services; Overview of mobile mapping technologies and research projects at NAVTEQ Research
  2. Street level imagery: camera and image formation; image enhancement; mosaics and panorama
  3. Basic geodesy; survey technologies; GPS and other emerging positioning technologies
  4. Image analysis for digital mapping: feature matching, object detection and machine learning techniques
  5. Mid-term exam; OpenCV/PCL tutorial; MapAPI tutorial
  6. Remote sensing revisited: emerging digital sensors, flight platforms, demanding applications; computer vision and image processing for remote sensing.
  7. 3D computer vision and other emerging 3D sensing technologies (LIDAR) for mapping and navigation.
  8. Case study 1: Privacy protection in geospatial data visualization using computer vision technologies.
  9. Case study 2: Data Mining Large Scale Geo-referenced User Data
  10. Case study 3: Augmented Reality and Location Based Mobile Applications

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