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Detection, Tracking and Classification of Vehicles
Vopálenský, Radek ; Herout, Adam (referee) ; Juránek, Roman (advisor)
The aim of this master thesis is to design and implementation in language C++ a system for the detection, tracking and classification of vehicles from streams or records from traffic cameras. The system runs on the platform Robot Operating System and uses the OpenCV, FFmpeg, TensorFlow and Keras libraries. For detection is used cascade classifier, for tracking Kalman filter and for classification of the convolutional neural network. Success rate for detection is 91.93 %, tracking 81.94 % and classification 63.72 %. This system is part of a comprehensive system, that can moreover calibrate video and measure of vehicles speed. The resulting system can be used for traffic analysis.
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Robotic Mirror
Vopálenský, Radek ; Materna, Zdeněk (referee) ; Kapinus, Michal (advisor)
The aim of this work is to design and implement a module through which robotic platform PR2 repeated movements of a man standing before her. User's movement is sensed using Kinect and detected by monitoring skeletal model. The embedded module can control robotic head, robotic arms and move the base in all directions. The work describes all the technologies used, description and design solutions and test results.
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Detection, Tracking and Classification of Vehicles
Vopálenský, Radek ; Sochor, Jakub (referee) ; Juránek, Roman (advisor)
The aim of this master thesis is to design and implement a system for the detection, tracking and classification of vehicles from streams or records from traffic cameras in language C++. The system runs on the platform Robot Operating System and uses the OpenCV, FFmpeg, TensorFlow and Keras libraries. For detection cascade classifier is used, for tracking Kalman filter and for classification of the convolutional neural network. Out of a total of 627 cars, 479 were tracked correctly. From this number 458 were classified (trucks or lorries not included). The resulting system can be used for traffic analysis.
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Detection, Tracking and Classification of Vehicles
Vopálenský, Radek ; Herout, Adam (referee) ; Juránek, Roman (advisor)
The aim of this master thesis is to design and implementation in language C++ a system for the detection, tracking and classification of vehicles from streams or records from traffic cameras. The system runs on the platform Robot Operating System and uses the OpenCV, FFmpeg, TensorFlow and Keras libraries. For detection is used cascade classifier, for tracking Kalman filter and for classification of the convolutional neural network. Success rate for detection is 91.93 %, tracking 81.94 % and classification 63.72 %. This system is part of a comprehensive system, that can moreover calibrate video and measure of vehicles speed. The resulting system can be used for traffic analysis.
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Detection, Tracking and Classification of Vehicles
Vopálenský, Radek ; Sochor, Jakub (referee) ; Juránek, Roman (advisor)
The aim of this master thesis is to design and implement a system for the detection, tracking and classification of vehicles from streams or records from traffic cameras in language C++. The system runs on the platform Robot Operating System and uses the OpenCV, FFmpeg, TensorFlow and Keras libraries. For detection cascade classifier is used, for tracking Kalman filter and for classification of the convolutional neural network. Out of a total of 627 cars, 479 were tracked correctly. From this number 458 were classified (trucks or lorries not included). The resulting system can be used for traffic analysis.
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Robotic Mirror
Vopálenský, Radek ; Materna, Zdeněk (referee) ; Kapinus, Michal (advisor)
The aim of this work is to design and implement a module through which robotic platform PR2 repeated movements of a man standing before her. User's movement is sensed using Kinect and detected by monitoring skeletal model. The embedded module can control robotic head, robotic arms and move the base in all directions. The work describes all the technologies used, description and design solutions and test results.
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