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Tracking People in Video Captured from a Drone
Lukáč, Jakub ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
Práca rieši možnosť zaznamenávať pozíciu osôb v zázname z kamery drona a určovať ich polohu. Absolútna pozícia sledovanej osoby je odvodená vzhľadom k pozícii kamery, teda vzhľadom k umiestneniu drona vybaveného príslušnými senzormi. Zistené dáta sú po ich spracovaní vykreslené ako príslušné cesty v grafe. Práca si ďalej dáva za cieľ využiť dostupné riešenia čiastkových problémov: detekcia osôb v obraze, identifikácia jednotlivých osôb v čase, určenie vzdialenosti objektu od kamery, spracovanie potrebných senzorových dát. Následne využiť preskúmané metódy a navrhnúť riešenie, ktoré bude v reálnom čase pracovať na uvedenom probléme. Implementačná časť spočíva vo využití akcelerátoru Intel NCS v spojení s Raspberry Pi priamo ako súčasť drona. Výsledný systém je schopný generovať výstup o polohe detekovaných osôb v zábere kamery a príslušne ho prezentovať.
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Analysis of Facial Development Based on Anthropometric Properties
Oravec, Dávid ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
This bachelor thesis deals with anthropometry of human face, anthropometric landmarks, which are used to determine the distances and various relations between them. Our body is aging and consequently the position of anthropometric points is changing. The aim of this work is to determine anthropometric landmarks from photo of the human face and then to analyze the given face and how it develops over time. The model for facial landmark detection was trained and selected points which will be used to determine facial indices were chosen. Indices are used to find out how the face is evolving over time. Based on experiments we observe how the faces of men and women are changing over time.
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Algorithmic Solution for Determining the Age of a Person Based on 2D Photography Using Artificial Intelligence
Bednář, Pavel ; Goldmann, Tomáš (referee) ; Drahanský, Martin (advisor)
Automated person's age estimation from a facial image is one of the challenges in the field of artificial intelligence and machine learning. Age estimation is often a non-trivial complexity for a person, unlike other biological characteristics such as determining gender or race. Information about an individual's age is very important for certain situations. For example, when committing an offense or crime, the amount of the sentence is co-determined by age. This information can also be used in the analysis of customers of a commercial entity and the subsequent adjustment of the offer. The aim of this work is to be able to extract his age from a photograph of a human face. The algorithm consists of two modules. If the first module says that the person is under 14 years old, the image will go to the second module. Furthermore, another version of the algorithm is proposed with an added module focused on selected facial features. In all modules transformations are performed on the image and their results are averaged. Finally, the algorithm is evaluated on standard datasets for age estimation and compared with state-of-the-art methods in this area.
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Perimeter Monitoring and Intrusion Detection Based on Camera Surveillance
Goldmann, Tomáš ; Drahanský, Martin (referee) ; Orság, Filip (advisor)
This bachelor thesis contains a description of the basic system for perimeter monitoring. The main part of the thesis introduces the methods of computer vision suitable for detection and classification of objects. Furthermore, I devised an algorithm based on background subtraction which uses a Histogram of Oriented Gradients for description of objects and an SVM classifier for their classification. The final part of the thesis consists of a comparison of the descriptor based on the Histogram of Oriented Gradients and the SIFT descriptor and an evaluation of precision of the detection algorithm.
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Embedded Device for Robotic Arm Control
Kyzlink, Jiří ; Goldmann, Tomáš (referee) ; Orság, Filip (advisor)
This diploma thesis deals with a design and implementation of an embedded device (module), used to control a robotic manipulator. The module instructs servomotors of the manipulator to move according to the commands received via USB interface. The module consists of two double-sided printed circuit boards. The first one allows connection to the CAN bus, redundant and thus reliable power supply for servomotors as well as the whole module. The second board, compute oriented one, embeds powerful microcontroller used to communicate with the servomotors and to solve the kinematics tasks. As a part of the thesis a graphical user interface as well as a web-oriented interface were developed. Both interfaces allow full control of the manipulator. All the communicating buses, tools and methods used during the design and implementation phases of the work are described in the thesis. Finally, measurements proved improvement of the motion smoothness and response times in several orders of magnitude in comparison to the previous system.
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Weather Estimation Based on Images of Clouds
Kukaň, Tomáš ; Goldmann, Tomáš (referee) ; Orság, Filip (advisor)
The main purpose of this thesis is a creation of a simple mobile application that would be able to give weather predictions based on a cloud photo through the usage of convolu- tional neural networks. I have analyzed all types of clouds and joined them with weather prediction. Then there are the results of experiments with different neural networks archi- tectures and different datasets. In the end of this thesis I have described the creation of the Android application as well as the problems I had to solve.
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Detector of the Human Head in Image
Svoboda, Jakub ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
Detection of human head is an important part of person detection and identification algorithms. This thesis is focused on the detection of human head with methods based on neural networks. The majority the of conventional detectors can identify objects within a limited range of positions, whereas models based on neural networks offer a more robust approach. In this thesis we trained the current state-of-the-art models and compared their accuracy and speed. The most accurate model proved to be RetinaNet which has reached 85.15% AP. This detector can be used to improve current available algorithms for person detection, identification and tracking.
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Biometric Sensor for Hand Vein Recognition
Švestka, Jan ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
This work describes the area of the biometric sensor for identifying using hand veins. It proposes the construction of a sensor made up of a camera, an infrared LED, an ultrasonic distance meter and an Arduino development device. The sensor cover and removable arm support are modeled and constructed using 3D printing. A software with user-interface is created for a sensor. The work describes the experiments carried out to find the ideal lighting and camera parameters settings. It is possible to take a photo of a hand veins and identify a person stored in a database based on the captured image.
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