Computer Vision

Aim

After having passed this course, the student is expected to be able to describe problems and algorithms for the following basic computer vision and image processing tasks:

• tracking of image regions
• structure from motion estimation
• estimation of optical flow
• detection and matching of local image features
• structure from motion and bundle adjustment
• generative image models
• segmentation of image regions
• enhancement of images
• debugging and visualisationThese are relevant for applications 3D reconstruction, camera pose estimation, object detection, motion estimation, visualization, and quality control within the areas of 3D vision, object tracking, scientific and industrial image analysis.

Content

Computational methods related to the various applications mentioned in the learning outcomes above. For each application, a number of standard methods are being presented. Necessary mathematics is being introduced. Alternative methods and related research areas are mentioned.