EECS 395/495 - Geospatial Vision and Visualization
COURSE DESCRIPTION: Geospatial information has become ubiquitous in everyday life, as evidenced by on-line mapping services such as Microsoft Virtual Earth/Bing Map, the recent addition of "place" features on social network websites such as Facebook, and free navigation on Nokia smart phones. Behind the scenes is digital map content engineering that enables all types of location-based services. Course material will be drawn from the instructor's research experience at NOKIA Location and Commerce (formerly NAVTEQ), the Chicago-based leading global provider of digital map, traffic and location data. This course will provide comprehensive treatment of computer vision, image processing and visualization techniques in the context of digital mapping, global positioning and sensing, next generation map making, and three-dimensional map content creations. Real world problems and data and on-site industry visits will comprise part of the course curriculum.
- The course satisfies the interfaces breadth and depth requirements.
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)nokia.com
COURSE OUTLINE (SUBJECT TO CHANGE):
- 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
- Street level imagery: camera and image formation; image enhancement; mosaics and panorama
- Basic geodesy; survey technologies; GPS and other emerging positioning technologies
- Image analysis for digital mapping: feature matching, object detection and machine learning techniques
- Mid-term exam; OpenCV/PCL tutorial; MapAPI tutorial
- Remote sensing revisited: emerging digital sensors, flight platforms, demanding applications; computer vision and image processing for remote sensing.
- 3D computer vision and other emerging 3D sensing technologies (LIDAR) for mapping and navigation.
- Case study 1: Privacy protection in geospatial data visualization using computer vision technologies.
- Case study 2: Data Mining Large Scale Geo-referenced User Data
- Case study 3: Augmented Reality and Location Based Mobile Applications