Lecture
This lecture covers the principles of geometric stereo and depth recovery techniques. It begins with an introduction to the concept of stereo vision, explaining how depth can be perceived from two or more images. The instructor discusses the geometric relationships between image pairs, including triangulation and epipolar geometry, which are essential for establishing correspondences between images. The lecture also delves into disparity mapping, where the horizontal shift along epipolar lines is analyzed to infer depth information. Various methods for establishing correspondences, such as window-based approaches and normalized cross-correlation, are presented. The instructor highlights the importance of occlusion handling and the merging of disparity maps to create accurate 3D point clouds. Additionally, the lecture touches on advanced techniques like variational approaches and real-time implementations in stereo vision systems. The session concludes with practical applications, including the use of stereo vision in robotics and autonomous vehicles, showcasing the relevance of these techniques in modern technology.