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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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Robot Localization Using Camera
Heřman, Petr ; Španěl, Michal (referee) ; Beran, Vítězslav (advisor)
The objective of this work is to design a simple localization method and its implementation in robot operating system ROS. This method uses a monocular camera as the only sensor and estimates the position in a known map. In experiments with prototypes are tested key points of type SURF, SIFT and ORB.
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Running Motion Analysis
Eliáš, Radoslav ; Kolářová, Jana (referee) ; Goldmann, Tomáš (advisor)
Cieľom tejto práce je analyzovať pohyb a držanie tela pri behu. Systém pracuje so záznamom z dvoch kamier, zboku a zozadu. Využíva nástroj na detekciu postoja ľudského tela založenú na konvolučnej metóde. Práca porovnáva niekoľko detektorov. Výsledný systém používa detektor OpenPose a implementuje knižnicu s výpočtami pre rôzne metriky používane na ohodnotenie formy behu. Výsledky sú zobrazené v multiplatformnej aplikácii. Ohodnotená bola niekoľkými experimentmi na osobnej dátovej sade videí behu.
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Automatic calibration ot robotic arm using cameras
Adámek, Daniel ; Richter, Miloslav (referee) ; Honec, Peter (advisor)
K nahrazení člověka při úloze testování dotykových embedded zařízení je zapotřebí vyvinout komplexní automatizovaný robotický systém. Jedním ze zásadních úkolů je tento systém automaticky zkalibrovat. V této práci jsem se zabýval možnými způsoby automatické kalibrace robotického ramene v prostoru ve vztahu k dotykovému zařízení pomocí jedné či více kamer. Následně jsem představil řešení založené na estimaci polohy jedné kamery pomocí iterativních metod jako např. Gauss-Newton nebo Levenberg-Marquardt. Na konci jsem zhodnotil dosaženou přesnost a navrhnul postup pro její zvýšení.
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6-DOF Object Localization in Industrial Applications
Macurová, Nela ; Španěl, Michal (referee) ; Hradiš, Michal (advisor)
The aim of this work is to design a method for the object localization in the point could and as accurately as possible estimates the 6D pose of known objects in the industrial scene for bin picking. The design of the solution is inspired by the PoseCNN network. The solution also includes a scene simulator that generates artificial data. The simulator is used to generate a training data set containing 2 objects for training a convolutional neural network. The network is tested on annotated real scenes and achieves low success, only 23.8 % and 31.6 % success for estimating translation and rotation for one type of obejct and for another 12.4 % and 21.6 %, while the tolerance for correct estimation is 5 mm and 15°. However, by using the ICP algorithm on the estimated results, the success of the translation estimate is 81.5 % and the rotation is 51.8 % and for the second object 51.9 % and 48.7 %. The benefit of this work is the creation of a generator and testing the functionality of the network on small objects
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Detection of object position
Baáš, Filip ; Janáková, Ilona (referee) ; Richter, Miloslav (advisor)
Master’s thesis deals with object pose estimation using monocular camera. As an object is considered every rigid, shape fixed entity with strong edges, ideally textureless. Object position in this work is represented by transformation matrix, which describes object translation and rotation towards world coordinate system. First chapter is dedicated to explanation of theory of geometric transformations and intrinsic and extrinsic parameters of camera. This chapter also describes detection algorithm Chamfer Matching, which is used in this work. Second chapter describes all development tools used in this work. Third, fourth and fifth chapter are dedicated to practical realization of this works goal and achieved results. Last chapter describes created application, that realizes known object pose estimation in scene.
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Self-Supervised Learning for Recognition of Sports Poses in Image
Olekšák, Samuel ; Kocur, Viktor (referee) ; Herout, Adam (advisor)
This thesis demonstrates a solution for minimizing the amount of necessary labelled training data in the classification of sports poses using a neural network trained with contrastive self-supervised learning. Training consists of two stages. The first stage trains a feature extractor which uses unlabelled training images extracted from recordings of exercises from multiple viewpoints. In the second stage, using a small amount of labelled data, a simple classifier connected to the feature extractor is trained. The thesis discusses classification in the context of yoga poses, however, the final solution can be easily applied to any other sport in case of obtaining a suitable dataset. During the development of the solution, emphasis is placed on the performance of the resulting model so that it can be used on mobile devices. The resulting model reached an accuracy of 76 % using augmentations with a data set containing four labelled images per yoga pose. On a larger data set with 800 labelled images for all poses, an accuracy of 82 % is reached.
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3D Objects Detection in Images
Bordovský, Gabriel ; Veľas, Martin (referee) ; Španěl, Michal (advisor)
This bachelors thesis deals with detection of a known 3D object in images and its pose estimation. The method uses the ORB-type keypoints and their location on the surface of a bounding box. By using solve of PnP problem a pose of the object is obtained using the points 2D coordinates from the image and the 3D coordinates of the very points from the registered model. This thesis expands a detection method for simple box-shaped objects, which is a part of OpenCV library, for the usage on more complex objects. In experiments, the detector reached a detection success rate of 85 % and the computed pose matches the real one approximately for 88 %.
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Application of Augmented Reality: Measurement of Object Dimensions
Karásek, Miroslav ; Beran, Vítězslav (referee) ; Herout, Adam (advisor)
The goal of this diploma thesis is design and implementation of an application for automated measurement of objects in augmented reality. It focuses on automating the entire process, so that the user carries out the fewest number of manual actions. The proposed interface divides the measurement into several steps in which it gives the user instructions to progress to the next stage. The result is an Android application with ARCore technology. Is capable of determining the minimal bounding box of an object of a general shape lying on a horizontal surface. Measure error depends on ambient conditions and is in units of percent.
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