This course on advanced image/video/3D processing brings you to the level of interesting internships and projects in computer vision at MSc level. The course discusses state-of-the-art techniques in image/video feature analysis, like texture (edge) analysis, motion analysis, 3D reconstruction and object detection/classification. Also, the course introduces you the most efficient deep learning concepts. You will gain a hands-on experience with the computer vision techniques by capturing and processing the 2D/3D imaging data from a UAV drone.
The course starts with the main concept of camera projection matrix and explains the working principles of different imaging sensor types (mono, stereo, ToF, LiDAR, etc) and image data types (RGB, disparity, depth, point cloud, mesh, etc). The video analysis part of the course discusses segmentation techniques and the commonly used feature descriptors: SIFT, HOG, all with the associated filtering. Using these techniques as a basis, we proceed to motion analysis, as well as object detection and tracking techniques. The course also introduces object classification techniques like Gaussian Mixture Modeling, K-means clustering, SVM and basics of Deep Learning. In the 3D imaging part of the course, the 3D multi-view geometry, 3D reconstruction and visual SLAM techniques are presented.