This dissertation work is describing the usage of the software tool Computer Vision System Toolbox to create applications in computer vision. At the beginning of the work is performed background research of image scanning and its representation by using colour models. It is followed by a description of epipolar geometry and lastly is stated a description of the Computer Vision System Toolbox. In the next section of the work we deal with setting of used Basler cameras and processing of the scanned image. The following is a description how to create applications for object detection and after this description, we get to know applications for creation of depth maps area.

The thesis deals with head pose estimation in stereo data. The theoretical part provides the basis for understanding the geometry of the camera, its parameters and the method of calibration. The following describes the principles of stereo analysis and creating of disparity maps. In the research section, the methods used for head pose modelling are presented and an analysis of selected published articles is given. In the course of the master’s thesis, a system of two cameras for stereoscopic acquisition of motion of the head was designed and several measurements were carried out. The obtained data was prepared for creation of disparity maps and further processing. Based on the detection of facial features, in particular the inner and outer corners of the eyes and corners of the mouth, and their correspondences, a simple geometric model in shape of triangle was created to illustrate the inclination of the facial plane in space. By computing the angle of inclination in three axes, the current head pose is obtained. Motion is modelled by tracking detected points during video sequences.

This work describes 3D reconstruction using stereo vision. It presents methods for automatic localization of corresponding points in both images and their reprojection into 3D space. Application created can be used for navigation of a robot and object avoidance. Second part of the document describes chosen components of the robot. Path finding algorithms are also discussed, particulary Voronoi's diagram.

This thesis solves design of functional device that will be able to automatically positioning back view mirrors according to the positio of driver face. Measuring position of the face provides stereovision of two webacams. The device is based on a computer Raspberry Pi 2 with designed expansion board. The created prototype can follow set view int the mirror with accuracy up to 7 cm (horizontally up to 5cm) in level of rear corner of a car. The results of this project validate design of automatic positioning mirror and it can be basis for specific implementations of the device in car.

This work presents a system for semi-autonomous optical localization of distant moving targets using multiple positionable cameras. The cameras were calibrated and stationed using custom designed calibration targets and methodology with the objective to alleviate the main sources of errors which were pinpointed in thorough precision analysis. The detection of the target is performed manually, while the visual tracking is automatic and it utilizes two state-of-the-art approaches. The estimation of the target location in 3-space is based on multi-view triangulation working with noisy measurements. A basic setup consisting of two camera units was tested against static targets and a moving terrestrial target, and the precision of the location estimation was compared to the theoretical model. The modularity and portability of the system allows fast deployment in a wide range of scenarios including perimeter monitoring or early threat detection in defense systems, as well as air traffic control in public space.