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Wheel Alignment Measuring Systems
Kliš, Kamil ; Blaťák, Ondřej (referee) ; Hejtmánek, Petr (advisor)
This bachelor thesis deals with issues of wheel alignment measuring systems. The prime chapter of this bachelor thesis specifies the basic parameters of the wheel suspension geometry. In the next chapter of wheel alignment measuring systems are described. In the final chapter I was dealing with development of the measuring devices and modern trends.
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Design and Implementation of a System for Checking the Boxes Completeness
Filipský, Dalibor ; Pásek, Jan (referee) ; Jirgl, Miroslav (advisor)
This thesis describes the design and implementation of a system for checking the boxes completeness. Thesis is divided into several parts. The first part includes an introduction into the manufacturing process and also devices, for which the system is designed. The second part consists of system design and a description of hardware components used for the system. The third part deals with the creation of a scheme used for connection an electrical switchboard. The fourth part is focused on a design of mechanical constructions, such as construction plan used for vision sensors connection, lighting system and design mechanical parts of stopper. A simulator of the system for checking the boxes completeness is described in the fifth part. It is used for a demonstration of functionality and controllability of the system. The sixth part deals with enabling of a communication between particular sub-systems, such as vision sensors, control panel and control system. The seventh part is focused on creation of the software required for the control system, HMI panel and deals with the configuration of pair vision sensors. In the final part there are some illustrations of designed system in real process of manufacturing.
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Person Identification for Surveillance
Hopjan, Tomáš ; Juránek, Roman (referee) ; Hradiš, Michal (advisor)
This project deals with camera system surveillance and identification of humans. Motion detection and identification methods are presented. The main issue is people tracking using multiple camera system. Identification of individuals is accomplished using processing of decomposed colors histograms. Based on the experiments benefits and problems are introduced.
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Design of communication network infrastructure
Vinter, Ivan ; Sedlák, Petr (referee) ; Novotný, Vít (advisor)
This thesis is focused on the complex design of communication infrastructure using 3 technologies for the new headquarters of JIMI CZ a.s.. These technologies are computer network, IP camera system and Wifi coverage. The thesis discusses the concepts associated with the technologies mentioned above. The final part of the thesis is focused on the selection of components and the design of the communication infrastructure itself, along with its economic evaluation.
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Detection and Recognition of Persons in a Multi-Camera System
Martinček, Ľuboš ; Beran, Jan (referee) ; Goldmann, Tomáš (advisor)
This thesis deals with the detection and recognition of people in a multi-camera system. In this thesis I describe general camera systems and their development and methods used for detection and recognition of persons. Based on this information, in the second part of the project I describe the design and implementation of a multi-camera system that is able to detect and recognize people. This thesis implements a combination of a YOLO detector and an Omni-Scale neural network based feature extractor.
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Detecting a Partially Obscured Face in Image Data
Kedra, David ; Sakin, Martin (referee) ; Goldmann, Tomáš (advisor)
This bachelor thesis deals with the analysis of problems related to detecting partially occluded faces in camera systems and discusses current machine learning detectors. The aim was to find solutions useful for detecting hardly visible faces. For this reason, artificial occlusions were generated into datasets for training the YOLOv7, YOLOv7-tiny and RetinaNet models. A computer application that uses these detectors is presented. The models are compared with existing solutions in terms of quality and speed. The trained models perform better on most test datasets. YOLOv7 is the most accurate on the modified WIDER FACE and UFDD datasets with average precisions of 86 % and 89 % at a minimum IoU of 50 %. On the third dataset with face masks, the existing detector RetinaFace outperformes the others. According to the speed/quality ratio, YOLOv7-tiny is the most effective.
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Sledování včel na vstupu včelího úlu
NOVOTNÝ, Petr
The main goal of this work is to design and put into operation a camera system for an intelligent beehive located at the Experimental and Educational Apiary of the Biological Center of the ASCR, v. VI in the area of the Dendrological Garden on Branišovská Street No. 31 in Č. Budějovice and to create software for monitoring, counting and space identification of bees at the entrance of a beehive.The system will consist of cameras connected to the Raspberry Pi where it will be processed using the image processing method. The obtained data will be processed on the server and stored in the database. Part of the obtained results will be displayed using Grafana's visualization tools.
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Easily Configurable Visual Inspection System for Industrial Applications
Andrla, Ondřej ; Špaňhel, Jakub (referee) ; Španěl, Michal (advisor)
The aim of this thesis is to create a prototype of an easily configurable camera system, used to control products on an automated assembly line. The thesis is especially focused on the issue of LED detection. Their very presence in the image is detected and the system also evaluates whether the LED is lit and, if so, in what color. The final solution allows the user to easily define control metric for searching for circular objects in the image in a configuration application with a graphical user interface. The configuration is saved in a JSON file. Furthermore, a runtime which independently processes the recording from the camera, checks the products and reports on them to other components of the system based on the configuration was implemented. The system uses the Hough circular transformation to detect objects in the image. To test the efficiency of the system, a dataset was created using the FitKit tool with a LED matrix. When testing the runtime on the dataset, the overall accuracy of LED detection was 97,79%.
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Pedestrian Detection and Recognition in a Multi-Camera System
Macák, Filip ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
The main purpose of this bachelor's thesis is to create an application for person detection and recognition from scenes captured in a multi-camera system. The output of the application is a video on which the detected persons are highlighted and each person is assigned an identification number through which it can be recognized across the input scenes. Several solutions to the problem of person detection and recognition were examined and the text of this work serves as an overview of these problems. The application is built on PyTorch and Torchreid libraries. A detector with a Faster-RCNN network is used for detection and recognition is based on the OSNet network. The application also includes a simple user interface to facilitate work with the application. The application serves as a demonstration of the state-of-the-art for person detection and recognition.
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