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Detection of moving objects in video
Hanek, Petr ; Přinosil, Jiří (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis focuses on OpenCV library and it’s methods. Created application is able to detect moving objects from static camera video thanks to background subtraction methods. This application can be used different modes: detection in area which is calculated by BFS algorithm and two slightly different modes for crossing line detection. The application is multi thread because of graphical user interface demands on processor performance. This application also has implemented Kalman filter for multi target tracking and Hungarian method which solves assignment problem.
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Optical Localization System with a Pan/Tilt Camera
Senčuch, Daniel ; Musil, Petr (referee) ; Beran, Vítězslav (advisor)
The effective surveillance of large critical areas is crucial for their security and privacy. There is no publicly available and acceptable solution of automating this task. This thesis aims to create an application utilizing a combination of a pan-tilt robotic manipulator and a visible-spectrum camera. Based on the pan-tilt unit's position and camera's images, the application searches for semantically significant changes in the captured environment and marks these regions of interest.
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Re-Identification of Vehicles by License Plate Recognition
Špaňhel, Jakub ; Juránková, Markéta (referee) ; Herout, Adam (advisor)
This thesis aims at proposing vehicle license plate detection and recognition algorithms, suitable for vehicle re-identification. Simple urban traffic analysis system is also proposed. Multiple stages of this system was developed and tested. Specifically - vehicle detection, license plate detection and recognition. Vehicle detection is based on background substraction method, which results in an average hit rate of ~92%. License plate detection is done by cascade classifiers and achieves an average hit rate of 81.92% and precision rate of 94.42%. License plate recognition based on Template matching results in an average precission rate of 60.55%. Therefore the new license plate recognition method based on license plate scanning using the sliding window principle and neural network recognition was introduced. Neural network achieves a precision rate of 64.47% for five input features. Low precision rate of neural network is caused by small amount of training sample for some specific license plate characters.
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Motion Detection in Video Sequences
Chadim, Petr ; Štancl, Vít (referee) ; Švub, Miroslav (advisor)
This thesis deal with a problem of motion detection in video sequence. The basic principle of method Bacground subtraction and the algorithm for searching differences between frames were described in details. Great attention is made for actualization of referential frame. Part of this thesis is a localization of motion object. The result of this thesis is an application for testing of motion detector in different environments.
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Moving Object Detection in Video Using CUDA
Horák, František ; Nečas, Ondřej (referee) ; Herout, Adam (advisor)
This thesis deals with methods of moving object detection in video; by selecting and applying proper algorithms and implementing them with CUDA. Technology CUDA is described and wieved it's architecture and other parts. General principles of moving object detection are observed and modification are discussed. Final system is implemented and tested.
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Vehicle Speed Measurement by a Stationary Camera
Juřica, Tomáš ; Špaňhel, Jakub (referee) ; Herout, Adam (advisor)
This Bachelor's thesis deals with the problematic of car speed measurement from video footage captured by a stationary camera. Development of a tool focused on reaching maximum accuracy of measurements with minimal user effort has been covered in this work. Perception of scene dimensions is acquired by using known points in the scene, which are manually marked. The influence of the way of annotating car position and input video quality on maximal reachable accuracy has also been discussed in this work.
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Fire Detection in Images and Video
Poledník, Tomáš ; Juránková, Markéta (referee) ; Přibyl, Bronislav (advisor)
This bachelor's thesis deals with fire detection in image and video. Attention is paid to the existing methods and known approaches to fire detection. Based on the analysis of the described methods, a fire detector, monitoring the attributes of its colour and motion, is designed, implemented and tested. The implemented detector achieves true positive detection rate of up to 90%.
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Motion Detection in Video
Půček, Petr ; Bartl, Vojtěch (referee) ; Herout, Adam (advisor)
This bachelor thesis deals with motion detection in video recorded on stationary camera. It describes the process of solution and implementation of motion detection app on Windows platform using OpenCV library for image processing. These principles of image analysis and processing can be used in any other systems.
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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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Tracking of Military Objects in a Videosignal
Hamada, Ondřej ; Váňa, Jan (referee) ; Orság, Filip (advisor)
First part of this thesis briefly describes the main problems of object tracking in video and methods to deal with them. Main attention is paid towards usage of these methods for target tracking in videos taken by both normal and thermal camera. It propose solution to this problem based on the kernel-based method which uses mean-shift algorhitm and on the template matching. Both tracking methods results are supervised and corrected by Kalman filter. Proposed solution is implemented using C++ with OpenCV library.
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