ECE 5554 Computer Vision | ECE | Virginia Tech


Course Information


Techniques for automated analysis of images and videos. Image formation, feature detection, segmentation, multiple view geometry, recognition, and video processing.

Why take this course?

Computers increasingly require the ability to "see" their surroundings in order to interact with humans and with the three-dimensional world. This course introduces theory and techniques for analyzing the content of images. Applications of computer vision include robotics, autonomous vehicle navigation, industrial automation, content-based search in image databases, face and gesture recognition, and aides for the seeing-impaired.

Learning Objectives

  • contrast common image formation models
  • implement various ways of extracting features from images
  • segment an image into meaningful regions
  • derive the theory behind multi-view geometry
  • implement various approaches to recognizing objects and scenes in images
  • implement techniques for processing video sequences

Course Topics


Percentage of Course

1. Features and filters: linear filters, edge detection, binary image analysis, image pyramids, texture 20%
2. Grouping and fitting: fitting lines and curves, robust fitting, RANSAC, Hough transform, segmentation, clustering 20%
3. Multiple views and motion: dense motion estimation, optical flow, camera model, image formation, planar homography, image warping, Epipolar geometry, stereo and multi-view reconstruction, invariant local features 20%
4. Recognition: instance recognition with local features, bag-of-words representations, shape matching, part-based models, face detection and recognition, sliding window detection 20%
5. Video processing: motion descriptors, tracking, background subtraction, activity recognition 20%