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Human-Machine Interface Based on Gestures
Charvát, Jaroslav ; Beran, Vítězslav (referee) ; Bartoň, Radek (advisor)
Master's thesis "Human-Machine Interface Based on Gestures" depicts the theoretical background of the computer vision and gesture recognition. It describes more in detail different methods that were used to create the application. Practical part of this thesis consists of the description of the developed program and its functionality. Using this application, user should be able to control computer by gestures of both right and left hands and also his head. The program is primarily based on the skin detection that is followed by the recognition of palms and head gestures. There were used two essential methods for these actions, AdaBoost and PCA.
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VR Interactive Application
Valenta, Marek ; Kobrtek, Jozef (referee) ; Milet, Tomáš (advisor)
This document is primarily concerned with describing the development of an interactive virtual reality application. At the beginning is a description of the history of the VR, dating back to the 19th century. Following it is a description of the devices that are currently being used for the VR and for which this application is created. The Unity 3D development environment is presented, which is, together with the basic description of neural networks, a major part of the whole project. The other half describes the design and implementation of simulation of a magical world, including a new magic spell system that has not yet been used in any VR game, which is the recognition of hand gestures for spell creation by using neural network. The work also contains a description of the whole application, rooms and objects. The conclusion discusses the problems and dead ends that have been tried but failed.
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Game with Hand Gesture Control
Kartous, Petr ; Zemčík, Pavel (referee) ; Hradiš, Michal (advisor)
This work is focused on controlling the game by using hand gestures. The main part of the work is image segmentation and detection of the hand in picture. For the segmentation of the image are used techniques of skin detection and the background subtraction with adaptive model of the background. Also the methods of mathematical morphology to eliminate the noise from the image and the appropriate methods for transferring images of gestures to characteristic gestures in numerical form are mentioned. In the context of the work was a simple car race game created which is controlled by hand gestures. At the end there was a testing carried out to identify the advantages and disadvantages of used methods of image segmentation and to detect the used hand gestures. There were also several sets of gestures tested by which the game is controlled. The two sets which came out of the test most successfully are applicable depending on the quality of the hand gesture recognition.
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Intelligent Control Using Hand Gestures
Apjar, Martin ; Hyrš, Martin (referee) ; Šimek, Václav (advisor)
This work deals with a creation of the device suitable for capturing the gestures of the human´s hand, selection of suitable sensors, creation of service software and communication proposal. The device working is based on Arduino board with microprocessor from the company Atmel ATmega32u4. In the first part of the thesis a detailed search of the existing ways of solving the given problem was performed. The following sections are devoted to the design of my solution, the description of the fabrication of the model body and the description of the used materials. Further, the Thesis contains a description of all sensors and scanners and a detailed description of the supplied PCB. At the end we will find the program section where the control and sensor work is disassembled. The result of this work is a hand-held model and firmware.
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Computer vision and hand gestures detection and fingers tracking
Bravenec, Tomáš ; Wyrzykowski, Roman (referee) ; Frýza, Tomáš (advisor)
Diplomová práce je zaměřena na detekci a rozpoznání gest rukou a prstů ve statických obrazech i video sekvencích. Práce obsahuje shrnutí několika různých přístupů k samotné detekci a také jejich výhody i nevýhody. V práci je též obsažena realizace multiplatformní aplikace napsané v Pythonu s použitím knihoven OpenCV a PyTorch, která dokáže zobrazit vybraný obraz nebo přehrát video se zvýrazněním rozpoznaných gest.
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Tracking Judge Including Gestures in Agility
Palata, Petr ; Přibyl, Bronislav (referee) ; Herout, Adam (advisor)
This thesis focuses on tracking an Agility judge including his gestures. The beginning is dedicated to a brief introduction into Agility. After that, a conceptual system is presented and its parts are then described in the individual chapters. The thesis evaluates availa- ble open-source human trackers and integrates them into the system. Posture and hand recognition are done using two SVM classifiers trained with Bag of Words descriptors.
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Depth-Based Determination of a 3D Hand Position
Ondris, Ladislav ; Tinka, Jan (referee) ; Drahanský, Martin (advisor)
Cílem této práce je určení kostry ruky z hloubkového obrazu a jeho následné využití k rozpoznání statického gesta. Na vstupu je hloubkový obrázek, ve kterém je nejprve detekována ruka pomocí neuronové sítě Tiny YOLOv3. Následně je obrázek zbaven pozadí a z takto předzpracovaného obrázku je určena kostra ruky v podobě 21 klíčových bodů neuronovou sítí JGR-P2O. K rozpoznání gesta z klíčových bodů ruky byla navržena technika, která porovná kostru na vstupu s uživatelem definovanými gesty. Funkcionalita systému byla otestována na vytvořeném datasetu s více než čtyřmi tisíci obrázky.
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Gesture-Based Human-Computer Interface
Chaloupka, Jan ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This bachelor's thesis is about design and implementation of simple interface for hand gesture recognition. The interface is used as an extension of actual GUI elements. Skin color model is used for gesture segmentation, significant hand points (palm, fingers, fingertips) for gesture recognition. Designed interface is used for simple picture explorer controlling. Final application is capable of using simple gestures for scaling, rotation, pointing and click.
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Active prostetic hand
Brenner, Maximilian ; Sekora, Jiří (referee) ; Harabiš, Vratislav (advisor)
BACKGROUND: Based on mainly vascular diseases and traumatic injuries, around 40,000 upper limb amputations are performed annually worldwide. The affected persons are strongly impaired in their physical abilities by such an intervention. Through myoelectric prostheses, affected persons are able to recover some of their abilities. METHODS: In order to control such prostheses, a system is to be developed by which electromyographic (EMG) measurements on the upper extremities can be carried out. The data obtained in this way should then be processed to recognize different gestures. These EMG measurements are to be performed by means of a suitable microcontroller and afterwards processed and classified by adequate software. Finally, a model or prototype of a hand is to be created, which is controlled by means of the acquired data. RESULTS: The signals from the upper extremities were picked up by four MyoWare sensors and transmitted to a computer via an Arduino Uno microcontroller. The Signals were processed in quantized time windows using Matlab. By means of a neural network, the gestures were recognized and displayed both graphically and by a prosthesis. The achieved recognition rate was up to 87% across all gestures. CONCLUSION: With an increasing number of gestures to be detected, the functionality of a neural network exceeds that of any fuzzy logic concerning classification accuracy. The recognition rates fluctuated between the individual gestures. This indicates that further fine tuning is needed to better train the classification software. However, it demonstrated that relatively cheap hardware can be used to create a control system for upper extremity prostheses.
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Computer vision and hand gestures detection and fingers tracking
Bravenec, Tomáš ; Wyrzykowski, Roman (referee) ; Frýza, Tomáš (advisor)
Diplomová práce je zaměřena na detekci a rozpoznání gest rukou a prstů ve statických obrazech i video sekvencích. Práce obsahuje shrnutí několika různých přístupů k samotné detekci a také jejich výhody i nevýhody. V práci je též obsažena realizace multiplatformní aplikace napsané v Pythonu s použitím knihoven OpenCV a PyTorch, která dokáže zobrazit vybraný obraz nebo přehrát video se zvýrazněním rozpoznaných gest.
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