Ioannis Pitas, firstname.lastname@example.org
Image acquisition. Mathematical modeling of image formation. Introduction to image processing and analysis. Camera calibration. Stereo vision. Depth estimation. Object localization. 3D image analysis. Surface geometry. Object topology. Object landmarks and features. Object recognition. Object registration. Object description. Applications in medical imaging, image retrieval, robotic vision.
Compulsory bibliographical and/or programming assignments are foreseen to be carried out during the course.
In order to pass the course, you will be requested to:
1) study the course lecture pdfs (in English) and fill the respective understanding questionnaires:
2) do an obligatory bibliographical project (in ppt and tex)
3) do an obligatory programming project
4) participate in the final written course exams (remotely).
The course is quite demanding, but it provides excellent knowledge of the entire domain of Computer Vision.
13 weeks, 2,5 hours/ week
0-10 for written exams. Literature survey or programming assignments or mid-term exams or oral presentations provide an additional 2-4 points, if the exam mark is at least 4.
Asynchronous on-line participation
Up to 5 participants