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Analysis of Parking Availability
Stránský, Václav ; Rozman, Jaroslav (referee) ; Marvan, Aleš (advisor)
This thesis deals with an analysis of parking availability. The task is to determine the occupancy of predefined parking places in the sequence of color images acquired by a fixed camera. The thesis describes the design, implementation, and testing of three utilized methods for car detection, i.e. background modelling, edge detection, and histogram comparison. These methods are combined in order to obtain a more robust and accurate solution. The proposed system has been successfully tested on several real scenarios.
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Detection of Vehicles in Image
Pomykal, Antonín ; Beran, Vítězslav (referee) ; Herout, Adam (advisor)
This work deals with the possibility of detection of cars in the image using the characteristics of cars with custom created image features , which are made pursuant to Haar-like features, and using methods of AdaBoost to train and their detection. We introduce the possibilities and types of custom picture features, OpenCV library, which was used in the implementation of the program, and we show the results and the success of this combination of detection algorithms.
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Visual Car-Detection on the Parking Lots Using Deep Neural Networks
Stránský, Václav ; Veľas, Martin (referee) ; Rozman, Jaroslav (advisor)
The concept of smart cities is inherently connected with efficient parking solutions based on the knowledge of individual parking space occupancy. The subject of this paper is the design and implementation of a robust system for analyzing parking space occupancy from a multi-camera system with the possibility of visual overlap between cameras. The system is designed and implemented in Robot Operating System (ROS) and its core consists of two separate classifiers. The more successful, however, a slower option is detection by a deep neural network. A quick interaction is provided by a less accurate classifier of movement with a background model. The system is capable of working in real time on a graphic card as well as on a processor. The success rate of the system on a testing data set from real operation exceeds 95 %.
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RoboAuto - Car Detection
Melo, Jakub ; Řezníček, Ivo (referee) ; Juránek, Roman (advisor)
This thesis deals with detection and tracking of cars viewed from behind. For the detection, Adaboost algorithm is used. The tracking is done using Kalman filter. In the first part of the work, theoretical background of the object detection and tracking is described. Experiments with classifier training and their results are presented in the second part of the work.
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Visual Car-Detection on the Parking Lots Using Deep Neural Networks
Stránský, Václav ; Veľas, Martin (referee) ; Rozman, Jaroslav (advisor)
The concept of smart cities is inherently connected with efficient parking solutions based on the knowledge of individual parking space occupancy. The subject of this paper is the design and implementation of a robust system for analyzing parking space occupancy from a multi-camera system with the possibility of visual overlap between cameras. The system is designed and implemented in Robot Operating System (ROS) and its core consists of two separate classifiers. The more successful, however, a slower option is detection by a deep neural network. A quick interaction is provided by a less accurate classifier of movement with a background model. The system is capable of working in real time on a graphic card as well as on a processor. The success rate of the system on a testing data set from real operation exceeds 95 %.
|
|
|
Analysis of Parking Availability
Stránský, Václav ; Rozman, Jaroslav (referee) ; Marvan, Aleš (advisor)
This thesis deals with an analysis of parking availability. The task is to determine the occupancy of predefined parking places in the sequence of color images acquired by a fixed camera. The thesis describes the design, implementation, and testing of three utilized methods for car detection, i.e. background modelling, edge detection, and histogram comparison. These methods are combined in order to obtain a more robust and accurate solution. The proposed system has been successfully tested on several real scenarios.
|
|
|
RoboAuto - Car Detection
Melo, Jakub ; Řezníček, Ivo (referee) ; Juránek, Roman (advisor)
This thesis deals with detection and tracking of cars viewed from behind. For the detection, Adaboost algorithm is used. The tracking is done using Kalman filter. In the first part of the work, theoretical background of the object detection and tracking is described. Experiments with classifier training and their results are presented in the second part of the work.
|
|
|
Detection of Vehicles in Image
Pomykal, Antonín ; Beran, Vítězslav (referee) ; Herout, Adam (advisor)
This work deals with the possibility of detection of cars in the image using the characteristics of cars with custom created image features , which are made pursuant to Haar-like features, and using methods of AdaBoost to train and their detection. We introduce the possibilities and types of custom picture features, OpenCV library, which was used in the implementation of the program, and we show the results and the success of this combination of detection algorithms.
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