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Route control
Dolobáč, Dávid ; Janáková, Ilona (referee) ; Richter, Miloslav (advisor)
This thesis sets itself the task to detect geometric changes, located on a previously known route, which is considered as a template or pattern. Geometric changes represent rigid transformations of objects in a scene, specifically their rotation, displacement and their combinations. Another type of change is the addition of new or removal of original objects. The original route is captured with a monocular camera and by using methods of photogrammetry, a 3D model of a scene in a point representation is reconstructed from the video sequence. In the same manner, a 3D model of the scene containing changes is created, but this model captures only the local section of the original route. This local point cloud is registered in the 3D model of the original route, so that the 3D models can be directly compared with each other. The investigated space is divided into cubic voxels of the same size which are successively traversed and the degree of similarity of local surfaces is investigated for each of them. The solution results in 3D points from both clouds marked as changed or unchanged. The mentioned methods are tested on real data in scenarios with different geometric modifications of the scene and the evaluation of change detection is implemented as in the case of a binary classifier.
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3D Reconstruction of Historic Landmarks from Flickr Pictures
Šimetka, Vojtěch ; Maršík, Lukáš (referee) ; Polok, Lukáš (advisor)
Tato práce popisuje problematiku návrhu a vývoje aplikace pro rekonstrukci 3D modelů z 2D obrazových dat, označované jako bundle adjustment. Práce analyzuje proces 3D rekonstrukce a důkladně popisuje jednotlivé kroky. Prvním z kroků je automatizované získání obrazové sady z internetu. Je představena sada skriptů pro hromadné stahování obrázků ze služeb Flickr a Google Images a shrnuty požadavky na tyto obrázky pro co nejlepší 3D rekonstrukci. Práce dále popisuje různé detektory, extraktory a párovací algoritmy klíčových bodů v obraze s cílem najít nejvhodnější kombinaci pro rekonstrukci budov. Poté je vysvětlen proces rekonstrukce 3D struktury, její optimalizace a jak je tato problematika realizovaná v našem programu. Závěr práce testuje výsledky získané z implementovaného programu pro několik různých datových sad a porovnává je s výsledky ostatních podobných programů, představených v úvodu práce.
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Design of 3D scan method based on computer vision
Kratochvíl, Jaromír ; Mašek, Petr (referee) ; Růžička, Michal (advisor)
This thesis deals with designing 3D scan method for visualization of laser beam. The first part deals with the division of 3D scanners and explains how they work. The second part compares various image processing tools and selects the most suitable for this work. The third part proposes a solution that explains the individual methods that were used or considered for this work. The fourth part deals with the solution, explaining how the methods has been created. The next part deals with practical experiments where proposed solutions are applied to different objects in different positions. The last part is the conclusion summarizing the results of this work.
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3D Objects Reconstruction from Image Data
Cír, Filip ; Kršek, Přemysl (referee) ; Španěl, Michal (advisor)
This paper deals with 3D reconstruction of objects from image data. There is describes theoretical basis of the 3D optical scanning. Handheld 3D optical scanner setup is described composed of a single camera and a line laser whose position is fixed with respect to the camera. Set of image markers and a simple real-time detection algorithm are proposed. Detected markers are used to estimate position and orientation of the camera. Finally, laser detection and triangulation of points lying on object surface are discussed.
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Sensor Calibration for Multispectral Data Fusion in Mobile Robotics
Kalvodová, Petra ; Hanzl, Vlastimil (referee) ; Mazal,, Jan (referee) ; Pospíšil,, Jiří (referee) ; Weigel, Josef (advisor)
Thesis deals with data fusion and calibration of sensory system of Orpheus-X3 robot and EnvMap mapping robot. These robots are parts of Cassandra robotic system that is used for exploration of hazardous or inaccessible areas. Corrections of measured distances are determined for used laser scanners Velodyne HDL-64, Velodyne HDL-32 and range camera SwissRanger SR4000. Software MultiSensCalib has been created and is described. This software is used for determination of intrinsic parameters of heterogeneous cameras of the sensory head and for determination of mutual position and orientation of these sensors. Algorithm for data fusion of CCD camera stereo pair, thermal imager stereo pair and range camera is proposed. Achieved calibration and data-fusion parameters are evaluated by several experiments.
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Height Measurement in Digital Image
Olejár, Adam ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
The aim of this paper is a summary of the theory necessary for a modification, detection of person and the height calculation of the detected person in the image. These information were then used for implementation of the algoritm. The first half reveals teoretical problems and solutions. Shows the basic methods of image preprocessing and discusses the basic concepts of plane and projective geometry and transformations. Then describes the distortion, that brings into the picture imperfections of optical systems of cameras and the possibilities of removing them. Explains HOG algorithm and the actual method of calculating height of person detected in the image. The second half describes algoritm structure and statistical evaluation.
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Speed Measurement of Vehicles from Surveillance Camera
Jaklovský, Samuel ; Juránek, Roman (referee) ; Sochor, Jakub (advisor)
This master's thesis is focused on fully automatic calibration of traffic surveillance camera, which is used for speed measurement of passing vehicles. Thesis contains and describes theoretical information and algorithms related to this issue. Based on this information and algorithms, a comprehensive system design for automatic calibration and speed measurement was built. The proposed system has been successfully implemented. The implemented system is optimized to process the smallest portion of the video input for the automatic calibration of the camera. Calibration parameters are obtained after processing only two and half minutes of input video. The accuracy of the implemented system was evaluated on the dataset BrnoCompSpeed. The speed measurement error using the automatic calibration system is 8.15 km/h. The error is mainly caused by inaccurate scale acquisition, and when it is replaced by manually obtained scale, the error is reduced to 2.45 km/h. The speed measuring system itself has an error of only 1.62 km/h (evaluated using manual calibration parameters).
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Projector camera cooperation
Walter, Viktor ; Horák, Karel (referee) ; Richter, Miloslav (advisor)
The focus of this thesis is the cooperation of cameras and projectors in projection of data into a scene. It describes the means and theory necessary to achieve such cooperation, and suggests tasks for demonstration. A part of this project is also a program capable of using a camera and a projector to obtain necessary parameters of these devices. The program can demonstrate the quality of this calibration by projecting a pattern onto an object according to its current pose, as well as reconstruct the shape of an object with structured light. The thesis also describes some challenges and observations from development and testing of the program.
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Detection of Landmarks on Vehicle Images
Chadima, Vojtěch ; Bartl, Vojtěch (referee) ; Herout, Adam (advisor)
This thesis aims to introduce automatic detection of landmarks on vehicle images. Detected landmarks can be then used for automatic traffic surveillance camera calibration or other computer vision applications. I solved the landmarks detection problem by using a novel type of convolutional neural network called Stacked Hourglass. Furthemore, I created an automatic trainig dataset (image + anotations) generator based on Blender API, which allows to create various datasets. Detected landmarks are analyzed and sorted in order to determine a set of superior landmarks that could be later used for camera calibration. The best-performing models detect up to 1 021 landmarks, while the best of them have less than 3.0 pixels average error. Finally, results can be further used in automatic camera calibration based on landmarks detection, to create custom datasets or to train Stacked Hourglass convolutional neural networks.
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