Courses
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Descriptions
EECS 395, 495: Geospatial Vision and Visualization

Quarter Offered

Winter : Tu 6-9 ; Chen, Xin

Description

Geospatial information has become ubiquitous in everyday life, as evidenced by on-line mapping services, navigation software on mobile devices and vehicles, and HD map for automated driving. 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 HERE (formerly NAVTEQ), a leader in mapping and location technology. 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 and high definition 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 and counts as a project course.

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: Prof. Xin Chen, PhD, Senior Engineering Manager and Research Scientist, HERE, xin.5.chen(at)here.com

COURSE OUTLINE (SUBJECT TO CHANGE):

  1.     Course logistics and introduction; overview of state-of-the-art digital mapping content and location-based services; Overview of next generation map making technologies
  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.     Remote sensing revisited: emerging digital sensors, flight platforms, demanding applications; computer vision and image processing for remote sensing
  6.     3D computer vision and other emerging 3D sensing technologies (LIDAR) for mapping and navigation
  7.     Large scale geospatial and temporal data analysis

    Final project built on the topics above