LIDAR (2D) has been widely used for mapping, localization and navigation in mobile robotics. However, its usage is limited to simple environments. This problem can be solved by adding more sensors and processing these data together. This paper explores a method how measurements from a stereo camera and LIDAR are fused to dynamical mapping. An occupancy grid map from LIDAR data is used as prerequisite and extended by a 2D grid map from stereo camera. This approach is based on the ground plane estimation in disparity map acquired from the stereo vision. For the ground plane detection, RANSAC and Least Squares methods are used. After obstacles determination, 2D occupancy map is generated. The output of this method is 2D map as a fusion of complementary maps from LIDAR and camera. Experimental results obtained from RUDA robot and MIT Stata Center Data Set are good enough to determine that this method is a benefit, although my implementation is still a prototype. In this paper, we present the applied methods, analyze the results and discuss the modifications and possible extensions to get better results.

This thesis deals with the task of three-dimensional scene reconstruction using image data obtained from multiple views. It is assumed that intrinsic parameters of the utilized cameras are known. The theoretical chapters describe the basic priciples of individual reconstruction steps. Variuous possible implementaions of data model suitable for this task are also described. The practical part also includes a comparison of false keypoint correspondence filtering, implementation of polar stereo rectification and comparison of disparity map calculation methods that are bundled with the OpenCV library. In the final portion of the thesis, examples of reconstructed 3D models are presented and discussed.

Cette thèse traite des caméras light-field en tant que caméra ayant des capacités 3D. Les images brutes, acquises avec ces systèmes, sont généralement inexploitables directement. L’obstacle majeur concernant l'utilisation de ces caméras réside dans la complexité du traitement des images acquises. Cette thèse vise à dépasser ces limitations en s'intéressant aux dispositifs multi-vues et multi-caméras. De plus, comme l'un des domaines d'application envisagé est la vision industrielle, les images sont acquises en lumière naturelle afin de conserver la possibilité d'effectuer des traitements conventionnels par vision sur les images. Le travail de thèse repose sur trois axes : l'étude et la conception optique de systèmes light-field multi-caméras et multi-vues, le calibrage de ces dispositifs et le développement d’algorithmes et enfin leur mise en application pour montrer les intérêts de ces caméras dans divers domaines. / This thesis deals with light-field cameras as cameras having 3D capacities. The raw images. acquired with these systems, are generally unusable directly. The main obstacle about their use lies in the complex processing of the recorded images. This thesis aims to overcome these limitations by focusing on multi-views and multi-camera devices. Morcover, as one of the application domains is the industrial vision, the images are acquired in natural lightning in order to conserve the possibility to make conventional treatments by vision on the images. The work is based on three axis: the study and'the optical desien of light-field systems, the calibration of these devices and the development of algorithms to show the intercsts of these cameras in various fields.

The goal of the master thesis is the design and construction of a device for capturing video sequences of the cardiovascular system of the finger of a human hand and the subsequently design and implementation of a method of data extraction for its reconstruction into a 3D model.

This thesis covers with the problems of photogrammetry. It describes the instruments, theoretical background and procedures of acquiring, preprocessing, segmentation of input images and of the depth map calculating. The main content of this thesis is the description of the new method of stereovision. Its algorithm, implementation and evaluation of experiments. The covered method belongs to correlation based methods. The main emphasis lies in the segmentation, which supports the depth map calculation.