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Speed Measurement of Vehicles from Surveillance Camera
Jaklovský, Samuel ; Juránek, Roman (referee) ; Sochor, Jakub (advisor)
This master's thesis is focused on fully automatic calibration of traffic surveillance camera, which is used for speed measurement of passing vehicles. Thesis contains and describes theoretical information and algorithms related to this issue. Based on this information and algorithms, a comprehensive system design for automatic calibration and speed measurement was built. The proposed system has been successfully implemented. The implemented system is optimized to process the smallest portion of the video input for the automatic calibration of the camera. Calibration parameters are obtained after processing only two and half minutes of input video. The accuracy of the implemented system was evaluated on the dataset BrnoCompSpeed. The speed measurement error using the automatic calibration system is 8.15 km/h. The error is mainly caused by inaccurate scale acquisition, and when it is replaced by manually obtained scale, the error is reduced to 2.45 km/h. The speed measuring system itself has an error of only 1.62 km/h (evaluated using manual calibration parameters).
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Reconstruction of 3D Information about Vehicles Passing in front of a Surveillance Camera
Dobeš, Petr ; Sochor, Jakub (referee) ; Herout, Adam (advisor)
This master's thesis focuses on 3D reconstruction of vehicles passing in front of a traffic surveillance camera. Calibration process of surveillance camera is first introduced and the relation of automatic calibration with 3D information about observed traffic is described. Furthermore, Structure from Motion, SLAM, and optical flow algorithms are presented. A set of experiments with feature matching and the Structure from Motion algorithm is carried out to examine results on images of passing vehicles. Afterwards, the Structure from Motion pipeline is modified. Instead of using SIFT features, DeepMatching algorithm is utilized to obtain quasi-dense point correspondences for the subsequent reconstruction phase. Afterwards, reconstructed models are refined by applying additional constraints specific to the vehicle reconstruction task. The resultant models are then evaluated. Lastly, observations and acquired information about the process of vehicle reconstruction are utilized to form proposals for prospective design of an entirely custom pipeline that would be specialized for 3D reconstruction of passing vehicles.
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Software for Traffic Monitoring
Tesař, Filip ; Zahrádka, Jiří (referee) ; Španěl, Michal (advisor)
This thesis deals with detection and tracking of moving objects in video sequences. The aim of this work is design and implementation of an application, which uses video sequence capturing car traffic to acquire statistical data about each vehicle, such as its speed estimate and determination of its lane. The proposed application uses background subtraction method 'Mixture of Gaussians' and enables monitoring of multiple locations at the same time using independent cameras. The output data are saved into database and users are allowed to display statistics in graphs through a simple web interface.
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