National Repository of Grey Literature 62 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Human Presence Detection and Applications in Smart Home Environments
Dostál, Pavel ; Juránek, Roman (referee) ; Černocký, Jan (advisor)
Práce se zabývá studiem detekce a rozpoznávání člověka a následnou implementací v prostředí softwaru Home Manager, což je projekt simulující chytrý dům s intelligentními zařízeními. Rozšíření o funkcionalitu rozpoznání uživatelů a narušitelů umožní lépe přizpůsobit chování zařízení preferencím jednotlivých osob. Použití rozpoznávání je demonstrováno na ukázce ovládání klimatizace v místnostech podle přítomnosti uživatelů. 
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).
Detection, Tracking and Classification of Vehicles
Vopálenský, Radek ; Sochor, Jakub (referee) ; Juránek, Roman (advisor)
The aim of this master thesis is to design and implement a system for the detection, tracking and classification of vehicles from streams or records from traffic cameras in language C++. The system runs on the platform Robot Operating System and uses the OpenCV, FFmpeg, TensorFlow and Keras libraries. For detection cascade classifier is used, for tracking Kalman filter and for classification of the convolutional neural network. Out of a total of 627 cars, 479 were tracked correctly. From this number 458 were classified (trucks or lorries not included). The resulting system can be used for traffic analysis.
Computer Vision as a Service
Jež, Adam ; Zemčík, Pavel (referee) ; Juránek, Roman (advisor)
The goal of this thesis is to create a web service for sharing and easy access to computer vision algorithms. Currently, there is a large number of algorithms and it's beneficial for their authors to simply share them with other people, even from other disciplines. The main part of the thesis consists of creating web service architecture and suggesting a method for request processing to run algorithms. Part of the implemented service is a web interface that allows use of algorithms with its own data, and client library that makes integration into other apps easier.
Vehicle Speed Estimation from Video
Hájek, Pavel ; Herout, Adam (referee) ; Juránek, Roman (advisor)
This master's thesis describes design and development of an application for estimation of vehicle speed from both recorded video file and from camera stream.  It explains the procecess of a camera calibration, vehicle detection and tracking and describes the robot operating system as a target platform. The application uses library OpenCV for most of tasks, to access video application uses a FFmpeg library. Results can be printed to the terminal window, they can also be logged to a file or published in ROS. Application is written in C++ language, some parts in Python.
Quality Check of Text in Forms
Moravec, Zbyněk ; Juránek, Roman (referee) ; Zemčík, Pavel (advisor)
Purpose of this thesis is the quality check of correct button text display on photographed monitors. These photographs contain a variety of image distortions which complicates the following image graphic element recognition. This paper outlines several possibilities to detect buttons on forms and further elaborates on the implemented detection based on contour shapes description. After buttons are found, their defects are detected subsequently. Additionally, this thesis describes an automatic identification of picture with the highest quality for documentation purposes.
Mushroom Detection and Recognition in Natural Environment
Steinhauser, Dominik ; Juránek, Roman (referee) ; Špaňhel, Jakub (advisor)
In this thesis is handled the problem of mushroom detection and recognition in natural environment. Convolutional neural networks are used. The beginning of this thesis is dedicated to the theory of neural networks. Further is solved the problem of object detection and classification. Using neural network trained for classification is solved also the task of localization. Results of trained CNNs are analised.
Head Pose Estimation from Photography
Szentandrási, Tamás ; Juránek, Roman (referee) ; Behúň, Kamil (advisor)
The aim of this work is to propose and implement a head pose estimation system using Random Forests, with photographic input. This work uses a version on Random Forests with using Fisher Linear Discriminant Analysis for node splits. It also uses a number of tools to achieve this goal, the OpenCV library, SQLiteCpp library, and the aflw database. This work created an accurate head pose estimation system reusable for future Computer Vision tasks.
Acceleration of Object Detection Using Classifiers
Juránek, Roman ; Zemčík, Pavel (advisor)
Detection of objects in computer vision is a complex task. One of most popular and well explored  approaches is the use of statistical classifiers and scanning windows. In this approach, classifiers learned by AdaBoost algorithm (or some modification) are often used as they achieve low error rates, high detection rates and they are suitable for detection in real-time applications. Object detection run-time which uses such classifiers can be implemented by various methods and properties of underlying architecture can be used for speed-up of the detection.  For the purpose of acceleration, graphics hardware, multi-core architectures, SIMD or other means can be used. The detection is often implemented on programmable hardware.  The contribution of this thesis is to introduce an optimization technique which enhances object detection performance with respect to an user defined cost function. The optimization balances computations of previously learned classifiers between two or more run-time implementations in order to minimize the cost function.  The optimization method is verified on a basic example -- division of a classifier to a pre-processing unit implemented in FPGA, and a post-processing unit in standard PC.
Movement Analysis of Vehicles on Crossroads
Benček, Vladimír ; Juránek, Roman (referee) ; Sochor, Jakub (advisor)
This thesis proposes and implements a system for movement analysis of vehicles on crossroads. It detects and tracks the movement of vehicles in the video, gained from the stationary video camera, which has the view of some crossroad. The trajectories are stored and their number and directions are analysed. The detection was made using cascade classifier. A dataset of 10500 positive and 10500 negative samples has been created to train the classifier. Vehicles are tracked using KCF method. For trajectory clustering, needed by analysis, the Mean Shift method is used. Testing showed, that the overall success of vehicle movement analysis is 92.77%.

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1 Juránek, Radim
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