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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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Determining of Dron Localization Using Navigation Systems
Nosál, Jan ; Goldmann, Tomáš (referee) ; Drahanský, Martin (advisor)
The thesis describes problems of drone navigation using navigation systems with which the navigation modules that have been tested are able to work. Next the issue with flight path and the determination of the incline and direction of the flight of the drones was solved also. Drones are more and more popular devices used for military, agricultural and commercial purposes. The thesis contains information about most used navigation systems which we encounter every day especially in cars and aircrafts. There were tested two navigation modules for drone localization. Modules capable of handling five navigation systems GPS, Glonass, Galileo, Beidou, QZSS and they can communicate with the Arduino board and IMU controller for drone positioning.
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Determination of Gun Type and Position in Image Scene
Kolcún, Róbert ; Goldmann, Tomáš (referee) ; Drahanský, Martin (advisor)
The main goal of this work is to design an approach for classifying guns into two categories, with short and long weapons, and determining a position of guns in the image scene. This problem was solved using the classical approach as K-Nearest-Neighbour and SVM classification and using convolutional neural networks. In this work was made a comparison of these approaches with a resulting accuracy up to 90%. With the results of this work, it is possible to choose a right approach to this problem.
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Software Management
Kyzlink, Jiří ; Goldmann, Tomáš (referee) ; Orság, Filip (advisor)
The thesis deals with updating applications written for the .NET Framework platform and monitoring their status. Thesis solves both requirements with two frameworks. The first framework is based on the Squirrel.Windows library allowing updating the application to version selected by a user via the graphical or terminal user interface and it also supports release channels. The second framework simplifies registration of an application and its services to the consul health checking tool and also obtaining information about available application and services from the tool. Consul provides the ability to monitor availability and health of the registered applications and its services. Both frameworks are modular, targeting the broad range of applications with use of the .NET Standard. Frameworks were successfully internally deployed in Y Soft Corporation.
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Intelligent Recognition of the Smartphone User's Activity
Pustka, Michal ; Goldmann, Tomáš (referee) ; Drahanský, Martin (advisor)
This thesis deals with real-time human activity recognition (eg, running, walking, driving, etc.) using sensors which are available on current mobile devices. The final product of this thesis consists of multiple parts. First, an application for collecting sensor data from mobile devices. Followed by a tool for preprocessing of collected data and creation of a data set. The main part of the thesis is the design of convolutional neural network for activity classification and subsequent use of this network in an Android mobile application. The combination of previous parts creates a comprehensive framework for detection of user activities. Finally, some interesting experiments were made and evaluated (eg, the influence of specific sensors on detection precision).
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Estimate the Height of a Persons from the Video Data
Jelen, Vilém ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
The aim of this bachelor thesis is to create an application that can detect pedestrians and make an estimate of their height from the video data. In the main part of the thesis I introduced security cameras and image processing methods suitable for detecting and classifying objects. Based on the comparison of these methods, I realized the pedestrian detection using Histograms of Oriented Gradients. As the input parameters of the proposed height estimation algorithm, I used the position and properties of the camera and reference objects or points.
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Face Features Extraction Methods
Adamček, Ľubomír ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
The face has been one of the most attractive available human biometries for a long time due to it's easy and convenient way to obtain it. Possibilities of it's utilization are broad - from security, through monitoring up to enternainment industry. This work presents the domain of face biometry and analyses 3 extraction methods of facial features - PCA, LBP and HOG. A part of this work is also an efficient implementation of these algorithms including GUI designed to experiment with this implementation and to evaluate its performance on a set of images capturing people in various conditions.
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Wearables Development Technologies for YSoft SafeQ
Stárek, Jan ; Goldmann, Tomáš (referee) ; Orság, Filip (advisor)
Wearable devices grew in popularity in recent years. This fact contributes to increasing efforts to expand mobile and other applications to wearable devices. Exploring these possibilities, this thesis summarizes information on wearable devices and their typical operating systems, including available tools and restrains these systems offer. Based on the conclusion of theoretical part of this thesis an application for wearable devices is designed and implemented, specifically an application for printers that operate via SafeQ system developed in Y Soft Corporation.
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Determining Head Rotation in Video from Security Camera
Blucha, Ondřej ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
This thesis attempts to create an application to determine head rotation angle in video recorded from a security camera. The application consists of three parts: face detection, facial landmarks detection and determination of person's head rotation. The face detection has been implemented using Viola-Jones and HOG algorithms. Facial landmarks detection has been done using algorithm based on active shape model. Two methods to calculate the head rotation angles have been used: the first method works with anthropometric head features. The second method uses Perspective-n-Point algorithm to find the right rotation angles. Finally, all algorithms implemented have been tested and the proper parameters have been determined.
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