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Device for the traffic situation evaluating
Gábel, Matej ; Honec, Peter (referee) ; Janáková, Ilona (advisor)
The bachelor's thesis deals with the implementation of a device for evaluating the traffic situation, specifically by traffic signs detection. In this work, I tried different methods of traffic sign recognition, where the resulting implementation on hardware is done using convolutional neural networks. More precisely, it is the YOLOv5 architecture, which is suitable for recognizing traffic signs in real time.
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Person Following by Spot Light Using Camera
Rajnoch, David
This paper describes design of person tracking system connected to spot light fixture. System is able to track actor or narrator walking on stage in theatre. System is designed to be easy to use and configure. Several issues connected with such tracking is mentioned in text below.
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Product quality control
Pitrun, Tomáš ; Janáková, Ilona (referee) ; Boštík, Ondřej (advisor)
The bachelor’s thesis deals with the industrial inspection of defects on injection molding based on computer recognition. Part of the work is a description of injection molding technology and defects that may occur with this technology. The detection application is implemented in Python on the Raspberry Pi platform. The OpenCV library is used to detect product defects. Part of the work is also the selection of suitable hardware resources, including the Raspberry Pi microcomputer, lighting camera module, lens, relay modules and supporting structure.
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Recognizing Faces within Image
Svoboda, Pavel ; Žák, Pavel (referee) ; Švub, Miroslav (advisor)
The essence of face recognition within the image is generally computer vision, which provides methods and algorithms for the implementation. Some of them are described just in this work. Whole process is split in to three main phases. These are detection, aligning of detected faces and finally its recognition. Algorithms which are used to applied in given issue and which are still in progress from todays view are mentioned in every phase. Implementation is build up on three main algorithms, AdaBoost to obtain the classifier for detection, method of aligning face by principal features and method of Eigenfaces for recognizing. There are theoretically described except already mentioned algorithms neural networks for detection, ASM - Active Shape Models algorithm for aligning and AAM - Active Appearance Model for recognition. In the end there are tables of data retrieved by implemented system, which evaluated the main implementation.
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Image object detection
Pluskal, Richard ; Petyovský, Petr (referee) ; Richter, Miloslav (advisor)
The thesis deals with design of a program for entering various types of geometric objects in an image for the purpose of their further processing. The program should also contain algorithms to ease object entering (e.g. refining manually entered object position). In the first part there is a brief description of the computer vision and its basic methods used in the work as well as introduction of the OpenCV image processing library. The following part describes three types of geometric primitives that are implemented for now. Because the output of the program is in universal XML format, there is short chapter about the XML. After that, there are summarized some methods for searching of parametric description of geometric primitives in an image. The final chapter describes the proposed system and evaluates possibility and suitability of its usage for various types of images.
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Image Completion Using Depth Maps
Valeš, Ondřej ; Brejcha, Jan (referee) ; Čadík, Martin (advisor)
The aim of this thesis is to design and implement aplication for dataset driven scene completion utilizing data from similar dataset images and test the posibility of generating data used in reconstruction directly from depth map. For scene matching in dataset novel modification of GIST descriptor including depth data is used. Furthermore, depth maps can be used to split reconstructed image into parts with similar depth, simplifying reconstruction process. Part of this thesis is also computing GIST descriptors for datset images and implementation of tools for searching datset for similar images using depth maps.
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Image Texture Representation and Detection
Zachar, Tomáš ; Ševcovic, Jiří (referee) ; Španěl, Michal (advisor)
This bachelor's thesis presents methods used for texture classification and implements programme which is able to realize simple classification and which is capable of generating dynamic bank of filters according to actual texture library. For feature extraction is used combination of Gabor filters with Hu-moments. As classifier there is used algorithm SVM.
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Face recognition in digital images
Hauser, Václav ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
This master thesis deals with the detection and recognition of faces in the image. The content of this thesis is a description of methods that are used for the face detection and recognition. Method described in detail is the principal component analysis (PCA). This method is subsequently used in the implementation of face recognition in video sequence. In conjunction with the implementation work describes the OpenCV library package, which was used for implementation, specifically the C ++ API. Finally described application tests were done on two different video sequences.
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Detection of Person in Image
Bednář, Luboš ; Mlích, Jozef (referee) ; Herout, Adam (advisor)
This work deals with detection of person in image. At the beginning, there are described some methods to be used for this type of detection. Of these we chose a method histograms of oriented gradients. For classification we use SVM. Part of this work is the design and implementation of a simple detector.
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