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Evaluation Of The Neural Network Object Detection In Multi-Modal Images
Ligocki, Adam
This paper studies the information gain of various data domains that are commonly usedin the modern Advanced Driving Assistant Systems (ADAS) to develop robust systems that wouldincrease traffic safety. We could see a fast growth of many Deep Convolutional Neural Networks(DCNN) based solutions during the last several years. These methods are state-of-the-art in objectdetection and semantic scene segmentation. We created a small annotated dataset of synchronizedRGB, grayscale, thermal, and depth map images and used the modern DCNN framework tool toevaluate the object detection robustness of different data domains and their information gain processunderstanding the surrounding environment of the semi-autonomous driving agent.
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Focus techniques of optical measurement of 3D features
Macháček, Jan ; Honec, Peter (referee) ; Janáková, Ilona (advisor)
This thesis deals with optical distance measurement and 3D scene measurement using focusing techniques with focus on confocal microscopy, depth from focus and depth from defocus. Theoretical part of the thesis is about different approaches to depth map generation and also about micro image defocusing technique for measuring refractive index of transparent materials. Then the camera calibration for focused techniques is described. In the next part of the thesis is described experimentally verification of depth from focus and depth from defocus techniques. For the first technique are shown results of depth map generation and for the second technique is shown comparison between measured distance values and real distance values. Finally, the discussed techniques are compared and evaluated.
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Polygonal Mesh Segmentation
Bezděčík, Ladislav ; Polášek, Tomáš (referee) ; Španěl, Michal (advisor)
This bachelor's thesis deals with the issues of segmentating 3D models of human jaws. It analyzes currently used methods and proposes, implements and tests possible improvement to these methods from user perspective. The proposal consists of using neural networks for topology recognition on jaw models, and possibly combining this topology with currently used segmentation methods. This thesis also analyzes and implements the possibility of automated expnansion of 3D model datasets converted to depth maps, used for neural network training.
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Image processing and depth maps to create an interactive model
Gelo, Lukáš ; Adámek, Roman (referee) ; Appel, Martin (advisor)
This bachelor’s thesis deals with creation of communication protocol for Intel® RealSense™ cameras in MATLAB, creation of program which finds certain objects in image using depth map and implementation of this program into mechatronic exponate. Theoretical part deals with methods of depth and distance scanning. It clarifies principles of contactless and nondestructive measurement of depth and distance along with comparison of their advantages and disadvantages.
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Realization of camera module for mobile robot as independent ROS node
Albrecht, Ladislav ; Appel, Martin (referee) ; Věchet, Stanislav (advisor)
Stereo vision is one of the most popular elements in the field of mobile robots and significantly contributes to their autonomous behaviour. The aim of the diploma thesis was to design and implement a camera module as a hardware sensor input, which is independent, with the possibility of supplementing the system with other cameras, and to create a depth map from a pair of cameras. The diploma thesis consists of theoretical and practical part, including the conclusion of results. The theoretical part introduces the ROS framework, discusses methods of creating depth maps, and provides an overview of the most popular stereo cameras in robotics. The practical part describes in detail the preparation of the experiment and its implementation. It also describes the camera calibration and the depth map creating. The last chapter contains an evaluation of the experiment.
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Dynamic Image Presentations Using Depth Maps
Hanzlíček, Jiří ; Brejcha, Jan (referee) ; Čadík, Martin (advisor)
This master's thesis focuses on the dynamic presentation of still photography using a depth map. This text presents an algorithm that describes the process of creating a spatial model which is used to render input photography so that the movement of virtual camera creates parallax effect due to depth in image. The thesis also presents an approach how to infill the missing data in the model. It is suggested that a guided texture synthesis is used for this problem by using rendering outputs of the model themselves as guides. Additional information in model allows the virtual camera to move more freely. The final result of the camera movement can be saved to simple video sequence which can be used for presenting the input photography.
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Visualization for Ray-tracing
Vozár, Jaroslav ; Pelikán, Josef (advisor) ; Kondapaneni, Ivo (referee)
The aim of this work is to extend the existing image-rendering program based on ray- tracing. As this existing program is used to teach computer graphics at the Faculty of Mathematics and Physics of the Charles University, expanding tools provide the way to a simpler understanding of the substance. This includes statistics, analytical maps and especially the ability to track the rendering ray directly in the 3D scene. The last mentioned extension is essential and most useful for understanding deeper ray-tracing principles. In addition to facilitating the understanding of one of the main rendering techniques in computer graphics, these extensions will also help create homework for computer graphics subjects.
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Automatic synchronization of projected and scanned images
Šura, Jakub ; Křivánek, Václav (referee) ; Appel, Martin (advisor)
This bachelor’s thesis deals with creating a software solution in MATLAB for automatic synchronization of scanned depth map and projected image capable of working with various RGB-D sensors. The tested sensors are two versions of Microsoft Kinect. Research deals with overviewing and classifying various depth map sensing technologies. It describes the evolution and classification of different technologies, compares their advantages and disadvantages, and presents their examples on current market.
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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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