|
|
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.
|
|
|
Gamification of line-follower robot videorecordings
Soboňa, Tomáš ; Honec, Peter (referee) ; Janáková, Ilona (advisor)
This bacheor’s thesis is concerned with the processing of a vehicle’s trajectory following a black line located on an unchanging white background, and subsequently comparing of the quality of each vehicle’s covered distance on this trajectory. The first part of the thesis describes the theory for recognizing the track, individual graphic tags, as well as detection of important points in the picture and their correlation with points in another picture, for which an algorithm SIFT is used. The second part deals with the description of the program, which was created as part of this work, its classes and methods. The program is written in Python, for image processing is used mainly an open source library OpenCV and, to a lesser extent, the NumPy library. Finally, the results are concluded at the end of the thesis.
|
|
|
Processing Sensor Data from a Wearable Device by Machine Learning
Hlavačka, Martin ; Dobeš, Petr (referee) ; Herout, Adam (advisor)
The goal of this master's thesis is to analyze the situation of wearable devices with the Android Wear operating system and recognition capabilities of various movement activities using neural networks. The primary focus is therefore on identifying and describing the most appropriate tool for recognizing dynamic movements using machine learning methods based on data obtained from this type of devices. The practical part of the thesis then comments on the implementation of a stand-alone Android Wear application capable of recording and formatting data from sensors, training the neural network in a designed external desktop tool, and then reusing trained neural network for motion recognition directly on the device.
|
|
|
Moving Object Detection in the Environment of Mobile Robot
Dorotovič, Viktor ; Beran, Vítězslav (referee) ; Veľas, Martin (advisor)
This work's aim is movement detection in the environment of a robot, that may move itself. A 2D occupancy grid representation is used, containing only the currently visible environment, without filtering in time. Motion detection is based on a grid-based particle filter introduced by Tanzmeister et al. in Grid-based Mapping and Tracking in Dynamic Environments using a Uniform Evidential Environment Representation. The system was implemented in the Robot Operating System, which allows for re-use of modules which the solution is composed of. The KITTI Visual Odometry dataset was chosen as a source~of LiDAR data for experiments, along with ground-truth pose information. Ground segmentation based on Loopy Belief Propagation was used to filter the point clouds. The implemeted motion detector is able to distiguish between static and dynamic vehicles in this dataset. Further tests in a simulated environment have shown some shortcomings in the detection of large continuous moving objects.
|
|
|
Movement Identification in the Space
Šolony, Marek ; Beran, Vítězslav (referee) ; Potúček, Igor (advisor)
The aim of this paper is to suggest optical system capable of movement identification in space and its reconstruction. The motion capture system uses markers attached to parts of human body, and a camera pair to capture the movement. This paper describes step-by-step parts of this system. Epipolar geometry is used to deal with problem of object correspondence between two views.
|
|
|
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.
|
|
|
Processing Sensor Data from a Wearable Device by Machine Learning
Hlavačka, Martin ; Dobeš, Petr (referee) ; Herout, Adam (advisor)
The goal of this master's thesis is to analyze the situation of wearable devices with the Android Wear operating system and recognition capabilities of various movement activities using neural networks. The primary focus is therefore on identifying and describing the most appropriate tool for recognizing dynamic movements using machine learning methods based on data obtained from this type of devices. The practical part of the thesis then comments on the implementation of a stand-alone Android Wear application capable of recording and formatting data from sensors, training the neural network in a designed external desktop tool, and then reusing trained neural network for motion recognition directly on the device.
|
|
|
Gamification of line-follower robot videorecordings
Soboňa, Tomáš ; Honec, Peter (referee) ; Janáková, Ilona (advisor)
This bacheor’s thesis is concerned with the processing of a vehicle’s trajectory following a black line located on an unchanging white background, and subsequently comparing of the quality of each vehicle’s covered distance on this trajectory. The first part of the thesis describes the theory for recognizing the track, individual graphic tags, as well as detection of important points in the picture and their correlation with points in another picture, for which an algorithm SIFT is used. The second part deals with the description of the program, which was created as part of this work, its classes and methods. The program is written in Python, for image processing is used mainly an open source library OpenCV and, to a lesser extent, the NumPy library. Finally, the results are concluded at the end of the thesis.
|
|
|
Moving Object Detection in the Environment of Mobile Robot
Dorotovič, Viktor ; Beran, Vítězslav (referee) ; Veľas, Martin (advisor)
This work's aim is movement detection in the environment of a robot, that may move itself. A 2D occupancy grid representation is used, containing only the currently visible environment, without filtering in time. Motion detection is based on a grid-based particle filter introduced by Tanzmeister et al. in Grid-based Mapping and Tracking in Dynamic Environments using a Uniform Evidential Environment Representation. The system was implemented in the Robot Operating System, which allows for re-use of modules which the solution is composed of. The KITTI Visual Odometry dataset was chosen as a source~of LiDAR data for experiments, along with ground-truth pose information. Ground segmentation based on Loopy Belief Propagation was used to filter the point clouds. The implemeted motion detector is able to distiguish between static and dynamic vehicles in this dataset. Further tests in a simulated environment have shown some shortcomings in the detection of large continuous moving objects.
|
|
|
Movement Identification in the Space
Šolony, Marek ; Beran, Vítězslav (referee) ; Potúček, Igor (advisor)
The aim of this paper is to suggest optical system capable of movement identification in space and its reconstruction. The motion capture system uses markers attached to parts of human body, and a camera pair to capture the movement. This paper describes step-by-step parts of this system. Epipolar geometry is used to deal with problem of object correspondence between two views.
|
guest ::
