- Insight look into the implementation of Computer Vision Applications
- Software packages, libraries, and tools used in Computer Vision Applications
Computer vision from an applied point of view. We will review popular programming languages as well as open and closed source software (e.g. Matlab, NumPy, OpenCV) and talk about their pros and cons. We will also talk about how to approach computer vision problems in a principled way, and how related topics such as image processing, probability theory, numerical optimization, and machine learning fit into the picture. For the most part we will talk about selected successful computer vision applications. For example, modern cameras can detect faces in real-time, and we will see how this works. Other topics include Kinect¿s depth and pose estimation as well as deep learning, one of the current ¿hot topics¿ in computer vision.
Oral Exam
Basic image processing and computer vision knowledge is expected (e.g. what is linear filtering? what is a camera matrix?).
