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Route control
Dolobáč, Dávid ; Janáková, Ilona (referee) ; Richter, Miloslav (advisor)
This thesis sets itself the task to detect geometric changes, located on a previously known route, which is considered as a template or pattern. Geometric changes represent rigid transformations of objects in a scene, specifically their rotation, displacement and their combinations. Another type of change is the addition of new or removal of original objects. The original route is captured with a monocular camera and by using methods of photogrammetry, a 3D model of a scene in a point representation is reconstructed from the video sequence. In the same manner, a 3D model of the scene containing changes is created, but this model captures only the local section of the original route. This local point cloud is registered in the 3D model of the original route, so that the 3D models can be directly compared with each other. The investigated space is divided into cubic voxels of the same size which are successively traversed and the degree of similarity of local surfaces is investigated for each of them. The solution results in 3D points from both clouds marked as changed or unchanged. The mentioned methods are tested on real data in scenarios with different geometric modifications of the scene and the evaluation of change detection is implemented as in the case of a binary classifier.
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Visual Anomaly Detection in Industrial Production
Hrabica, Jan ; Richter, Miloslav (referee) ; Horák, Karel (advisor)
This thesis deals with the problem of unary classifiers for anomaly detection in industrial production. It starts with a discussion of classification as a general problem, classification methods and some of their evaluations, and then discusses the main categories of architectures used. Practical part describes the process of scene creation for the acquisitions of a datesed. Acquired dataset is then used for teaching a classifier, on which is then performer a number of experiments to determine its performance.
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Stereo reconstruction of vehicles' cross section
Boch, Jan ; Richter, Miloslav (referee) ; Honec, Peter (advisor)
This master thesis deals with the design of a stereo system for processing vehicle images and subsequent reconstruction of their 3D model. The aim of the thesis is to reconstruct the vehicle model to control its dimensions and load on which restrictions are imposed in case of the use of critical transport infrastructure (tunnels, bridges). The thesis begins with a mathematical description of scene capture and continues with a research of theoretical possibilities of system configuration. One Intel RealSense 3D camera and one RGB camera were chosen as the most suitable configuration. The software solution works with the design of several different algorithms of which it is worth mentioning reconstruction using depth maps or triangulation.The resulting models in the last chapter contain data only from the aforementioned 3D camera. The model from the 3D camera could not be improved with the images from the RGB camera and camera can therefore be declared redundant. Resulting 3D model is still sufficient for the purpose of vehicle inspection and in case of continued work, another, more optimal configuration should be designed.
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3D reconstruction
Vít, Luboš ; Honec, Peter (referee) ; Richter, Miloslav (advisor)
The thesis focuses on 3D measurement using line scan cameras. In response to the emphasis on quality and automatization of production nowadays, the line scan cameras are the appropriate devices providing accuracy for a belt product inspection. The first part of the thesis discusses the desing theory of optics, sensoring and image processing. The realisation of designing a mathematic instrument for evaluation of 3D shape, designing a test workspace and the main sensoring of the scene with processing with basic measuring algorithms is a content of the second part of the thesis.
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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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Person Identification Based on Locomotion
Pražák, Ondřej ; Richter, Miloslav (referee) ; Horák, Karel (advisor)
This paper deals with study of human movement and using that in identification. In the first part of my work are explained characteristics of human movement and factors which take effect on these characteristics. Practical part is dealing with design of program which is solving mentioned problems. The input of program is created by video sequence with lateral movement of human. The program is finding coordinates of lower limbs joints. From this coordinates are created locomotion characteristics used for human identification. Matching of time behaviors is based on correlation.
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3D simulation toolbox
Matyskiewicz, Jiří ; Babinec, Tomáš (referee) ; Richter, Miloslav (advisor)
This project deals with the design and implementation of the extensible programmable environment intended for the creation of various 3D simulations, specifically targeted for testing of the algorithms and creation of applications from the field of computer vision and robotics. Environment VISIMBOX was implemented in c# programming language and uses OpenGL as back-end for hardware accelerated rendering.
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Self-supervised learning in computer vision applications
Vančo, Timotej ; Richter, Miloslav (referee) ; Janáková, Ilona (advisor)
The aim of the diploma thesis is to make research of the self-supervised learning in computer vision applications, then to choose a suitable test task with an extensive data set, apply self-supervised methods and evaluate. The theoretical part of the work is focused on the description of methods in computer vision, a detailed description of neural and convolution networks and an extensive explanation and division of self-supervised methods. Conclusion of the theoretical part is devoted to practical applications of the Self-supervised methods in practice. The practical part of the diploma thesis deals with the description of the creation of code for working with datasets and the application of the SSL methods Rotation, SimCLR, MoCo and BYOL in the role of classification and semantic segmentation. Each application of the method is explained in detail and evaluated for various parameters on the large STL10 dataset. Subsequently, the success of the methods is evaluated for different datasets and the limiting conditions in the classification task are named. The practical part concludes with the application of SSL methods for pre-training the encoder in the application of semantic segmentation with the Cityscapes dataset.
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Pattern recognition
Pelc, Matěj ; Richter, Miloslav (referee) ; Horák, Karel (advisor)
This paper proposes robust algorithm for detection of traffic signs in well light conditional. The algorithm uses colour based segmentation method for finding red traffic signs. Fast radial symmetry method FRS is used for identification of constituent shapes. Traffic signs are divided into four classes on the basis of the method.
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