![]() ![]() Participation in the teaching sessions is not obligatory and not rewarded, but returning the homeworks is necessary and rewarded with bonus points. Thursday's sessions are usually located in Maari B classroom at Maarintalo.Īll the sessions and their locations can be found from the course calendar in M圜ourses. ![]() The deadline of weekly homework exercises is at noon on Fridays and the solutions are presented in Friday's exercise sessions. In addition, there is a guidance session every Thursday from 14:15 to 16:00 where teachers are available to give instructions for solving the homework. The first exercise and deadline of weekly homework is on Friday September 9. The first lecture is on Monday September 5.Įxercises are on Fridays from 12:15 to 14:00 in room TU1 (TUAS building). Video recordings of the lectures will become available after the lecture on this M圜ourses page under "Lectures and materials" section. Lectures are given on Mondays from 8:15 to 10:00 in room T1 (CS building). The course will be lectured by Assistant Professor Juho Kannala ( ).Ĭourse personnel has emails of the form firstname.lastname aalto.fi (i.e. The course gives an overview of algorithms, models and methods, which are used in automatic analysis of visual data. smoothness of the surface, integrability of the surface gradients), a complete depth image of the surface can also be obtained from a single image under certain conditions.This course provides an introduction to computer vision including fundamentals of image formation & filtering, feature detection & matching, structure-from-motion & image-based 3D modelling, motion estimation & tracking, and object detection & recognition. Due to the requirement that the reconstructed surface or its gradients must meet certain conditions (e.g. If only a single image is available, there are an infinite number of solutions to the reconstruction problem. Using the photometric stereo method, a complete depth image can be derived from several images of a scene under different lighting conditions. In this way, surface gradients and, from them, height profiles along image lines can be determined in a very simple way (photoclinometry). This requires knowledge of how incident light is scattered or reflected on the object surface. First of all, the most important radiometric quantities are introduced, and the image formation process is reproduced from a physical point of view. Intensity-based methods aim to derive the three-dimensional structure of an object from the intensity distribution in the image. It is assumed that a geometry model of the object in question is available. The following is an overview of methods for determining the three-dimensional position and orientation of objects from one or more images, which is also referred to as pose estimation. This is the standard method of photogrammetry, which enables the simultaneous determination of both internal and external camera parameters as well as the three-dimensional structure of the scene from several images recorded from different locations. which pixels belong to the same physical object or part of the object in the scene.Ī generalization of stereo image analysis to basically any number of cameras that view the scene from different positions is what is known as bundle adjustment. For this, it must be known, for example, which points in Figure 1 correspond to which points in Figure 2, i. The stereo image analysis, like more complex multiocular three-dimensional reconstruction methods, is based on the formation of mutual correspondences between points in the images of the scene. At this point, a brief introduction to the concept of projective geometry, which is quite helpful from a mathematical point of view, is given. The positions of image points belonging to scene features are determined in both images Then the three-dimensional structure of the scene features is determined by triangulation. One of the most important methods of three-dimensional scene reconstruction is stereo image analysis, which is based on the evaluation of image pairs of a scene. For this reason, an introduction to methods of camera calibration using a calibration body of known geometry is given. At the beginning of every image-based 3D scene reconstruction there is the calibration of the camera. In the first part of the lecture, the basics of optical imaging and imaging errors, in particular sharpness, color and distortion errors of lenses, are considered. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |