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System for tracking and classification of objects in the sky
Franka, Jakub ; Honec, Peter (referee) ; Janáková, Ilona (advisor)
This work deals with the use of computer vision in the field of detection, tracking and classification of flying objects in a real environment. The goal is to create a robust system, capable of working effectively in adverse conditions and accurately identifying different types of objects in the sky. The work progresses from theoretical foundations, choice of methods, to the design and implementation of a computer vision system.
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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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Easter eggs scanning module
Pitrun, Tomáš ; Janáková, Ilona (referee) ; Honec, Peter (advisor)
This master thesis deals with the design and implementation of a preparation for scanning the museum's collection of Easter eggs. A monochrome line scan camera combined with RGB lighting and stepper motor is used to capture the Easter eggs. The control of the whole fixture is solved by using an Arduino Mega microcontroller in combination with the developed PCB. The data from the camera are processed in software on a PC using Matlab. Finally, a 3D model of the easter egg with the scanned texture is created using the Processing library.
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Augmented Reality in Industrial Production and Maintenance
Kajan, Matej ; Janáková, Ilona (referee) ; Horák, Karel (advisor)
This paper seeks to explore the possibility to utilize XR (extended reality) in industrial assembly. The aim is to implement a system, which is able to visually navigate the operator during the product assembly process by the means of object recognition and image augmentation. The first chapter presents the use-case of augmented reality in the industry. The next part consists of research on the topic of augmented and virtual reality devices and provides a brief comparison of the current state of the art. Afterwards, a methodology is presented for object recognition of an arbitrary object. The implementation is able to detect the object in real-time, is resilient to occlusion and contains the information about the object’s orientation.
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A computer vision system for emotion recognition
Wójcik, Jan ; Bilík, Šimon (referee) ; Janáková, Ilona (advisor)
The term paper deals with the design of an emotion recognition system, which will be used as a communication tool for people with autism spectrum disorder. Camera data will be used for emotion recognition, so it will be a computer vision application. The work deals with areas such as face detection, extraction of relevant features, finding a suitable dataset or designing a classifier.
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Device for the traffic situation evaluating
Gábel, Matej ; Honec, Peter (referee) ; Janáková, Ilona (advisor)
The bachelor's thesis deals with the implementation of a device for evaluating the traffic situation, specifically by traffic signs detection. In this work, I tried different methods of traffic sign recognition, where the resulting implementation on hardware is done using convolutional neural networks. More precisely, it is the YOLOv5 architecture, which is suitable for recognizing traffic signs in real time.
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Product quality control
Pitrun, Tomáš ; Janáková, Ilona (referee) ; Boštík, Ondřej (advisor)
The bachelor’s thesis deals with the industrial inspection of defects on injection molding based on computer recognition. Part of the work is a description of injection molding technology and defects that may occur with this technology. The detection application is implemented in Python on the Raspberry Pi platform. The OpenCV library is used to detect product defects. Part of the work is also the selection of suitable hardware resources, including the Raspberry Pi microcomputer, lighting camera module, lens, relay modules and supporting structure.
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LED detection using SSE instruction set
Stachera, Tomáš ; Janáková, Ilona (referee) ; Honec, Peter (advisor)
The themes of this work is to make an instruction set for detection and counting LED in power supply control panel, with using SSE instruction set algorithm. The goal will be to compare function time for optimized and not optimized functions. The first part focuses on SSE instructions introduction, as well as on introduction of some functions using SSE instructions. The second part is dealing with algorithm for detection and counting LEDs and possibility of those algorithms optimizing with SSE instruction set. Next part introduces user interface for developed functions testing. On the very end I compare results of all functions and evaluate these results.
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Self-supervised learning in computer vision applications
Vančo, Timotej ; Richter, Miloslav (referee) ; Janáková, Ilona (advisor)
The aim of the diploma thesis is to make research of the self-supervised learning in computer vision applications, then to choose a suitable test task with an extensive data set, apply self-supervised methods and evaluate. The theoretical part of the work is focused on the description of methods in computer vision, a detailed description of neural and convolution networks and an extensive explanation and division of self-supervised methods. Conclusion of the theoretical part is devoted to practical applications of the Self-supervised methods in practice. The practical part of the diploma thesis deals with the description of the creation of code for working with datasets and the application of the SSL methods Rotation, SimCLR, MoCo and BYOL in the role of classification and semantic segmentation. Each application of the method is explained in detail and evaluated for various parameters on the large STL10 dataset. Subsequently, the success of the methods is evaluated for different datasets and the limiting conditions in the classification task are named. The practical part concludes with the application of SSL methods for pre-training the encoder in the application of semantic segmentation with the Cityscapes dataset.
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Goniophotometer
Ivor, Martin ; Janáková, Ilona (referee) ; Honec, Peter (advisor)
The thesis deals with the design of a goniophotometer and the GUI (Graphical User Interface), capable of evaluating the photometric parameters of light sources and luminaires. The introduction contains theoretical information about photometry, photometric parameters, light sources, lamps, as well as the theory of measuring these parameters, and basic globally used data formats, designed to store the parameters of light sources. The core of this thesis, then describes the hardware, that makes up the proposed device, and the software needed to control the measurement process, visualization and storing the results. The conclusion is an evaluation of the functionality of the described device, and the measurements that were mediated by it, and an overall summary of the results achieved.
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