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Automatic counting of people
Mitáček, Štěpán ; Číž, Radim (referee) ; Koutný, Martin (advisor)
This effort deals with the problem of effective counting of people in the room. Although more companies deal with this problem at present, but their systems are very expensive. For this reason I strive to find a cheaper solution for counting people using active infra- red sensors by which I want to perceive the passage of a person through the door or his presence in the room. In addition it is necessary to take into consideration the other various situations that may occur when a person comes into the room or when he/she leaves. These situations can be in many cases similar, but the output should be able correctly distinguish the possibilites. The result of this effort is detector which is able to detect correctly one person or more people passing the door. People can browse through a door one behind the other, but they also can pass in the doorway in random combinations.
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Crowd Density Estimation from a Photo
Ferencz, Adam ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
The aim of this thesis is to develop an aplication estimating the total number of people at a demonstration or at other public events. Input is a serie of photos from a drone or some other photos. The output are couloured maps according to people density in the place. Photos are placed in a topological map. Convolutional neural network MCNN is used for the crowd counting, which can generate a density map from the photo. Special method was proposed to correct the total amount of counted people when photographs overlap. The application is divided into server and web client. The server part generates density maps, saves data and runs an overlap correction algorithm. Client handles user inputs and provides an interactiv map with visualization.
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Crowd Density Estimation from a Photo
Ferencz, Adam ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
The aim of this thesis is to develop an aplication estimating the total number of people at a demonstration or at other public events. Input is a serie of photos from a drone or some other photos. The output are couloured maps according to people density in the place. Photos are placed in a topological map. Convolutional neural network MCNN is used for the crowd counting, which can generate a density map from the photo. Special method was proposed to correct the total amount of counted people when photographs overlap. The application is divided into server and web client. The server part generates density maps, saves data and runs an overlap correction algorithm. Client handles user inputs and provides an interactiv map with visualization.
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Automatic counting of people
Mitáček, Štěpán ; Číž, Radim (referee) ; Koutný, Martin (advisor)
This effort deals with the problem of effective counting of people in the room. Although more companies deal with this problem at present, but their systems are very expensive. For this reason I strive to find a cheaper solution for counting people using active infra- red sensors by which I want to perceive the passage of a person through the door or his presence in the room. In addition it is necessary to take into consideration the other various situations that may occur when a person comes into the room or when he/she leaves. These situations can be in many cases similar, but the output should be able correctly distinguish the possibilites. The result of this effort is detector which is able to detect correctly one person or more people passing the door. People can browse through a door one behind the other, but they also can pass in the doorway in random combinations.
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