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Person's identification by means of bipedal locomotion
Krzyžanek, Jakub ; Richter, Miloslav (referee) ; Horák, Karel (advisor)
The aim of this thesis is to recognize a walking person in a sequence of images by defining his or her reference points to compare the course of their movement and then to identify the scanned person. Methods „k-means“ and „mean shift“ are used to obtain the silhouette of the person. However “environment model estimation” method is used here before those mentioned above. It is a type of a difference method and it helps to specify the scanning area and shortens the time of segmentation. During the search for the reference points the thesis focuses on three areas: the centre of the head and both ankle joints. Those points are later determined on the previous image sequence and compared with the real locations of the centre of the head and ankle joints marked by the user. The thesis also focuses on comparing the movement courses of those points and tries to identify the people whose walks are being scanned. Problematic situations which occurred during the whole process are analyzed in the end. The result of the thesis is an algorithm which can locate a moving person in an image sequence (video) and determine the reference points (centre of the head and ankles) to compare them and identify the scanned person.
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Biometric Sensor for Hand Vein Recognition
Švestka, Jan ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
This work describes the area of the biometric sensor for identifying using hand veins. It proposes the construction of a sensor made up of a camera, an infrared LED, an ultrasonic distance meter and an Arduino development device. The sensor cover and removable arm support are modeled and constructed using 3D printing. A software with user-interface is created for a sensor. The work describes the experiments carried out to find the ideal lighting and camera parameters settings. It is possible to take a photo of a hand veins and identify a person stored in a database based on the captured image.
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Recognition of persons clothing in the video signal
Mlýnková, Barbora ; Kříž, Petr (referee) ; Přinosil, Jiří (advisor)
This paper is dealing with the detection clothes characteristics in the picture, for the use of person identification. These characteristics are described and categorized. It also deals with the design of the database structure, which works with masks and categories of characteristics for their processing. This work uses haar cascades to detect face and to determine the position of clothing for the purpose of color detection
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Biometric Gateway Using Camera to Identify People
Jelen, Vilém ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
Biometric gateways are used to quickly and accurately identify people. Of the biometric characteristics, iris, face and fingerprints are commonly used. By combining them, better identification results can be achieved. The aim of this thesis is to create such a biometric gateway together with the control application. A combination of iris of both eyes and face is used, which is captured by cameras from three angles to increase accuracy. Neural networks are used to detect and extract face features. Iris recognition is realized using Daugman's algorithm.
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Database of non-biometric and soft biometric human traits
Mlýnková, Barbora ; Říha, Kamil (referee) ; Dvořák, Pavel (advisor)
This paper is dealing with the detection of secondary biometric and nonbiometric characteristics in the picture, for the use of person identification. These characteristics are described and categorized. It also deals with the design of the database structure, which works with masks and categories of characteristics for their processing. This work might be practically used for machine learning.
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Monitoring the Movement of Visitors in Museum Exhibitions
Viskupič, Matej ; Dyk, Tomáš (referee) ; Drahanský, Martin (advisor)
The aim of this work is to propose a new system of monitoring visitors in museums. Incontrast to existing methods, the problem is solved here only using camera technology. This requires addressing three sub-problems: (1.) detection of visitors in camera streams using a convolutional neural network; (2.) camera configuration to exactly determine the position of the detected persons within the monitoring area; and (3.) identification and tracking the detected persons. The outcome of the proposed solution is the heatmap of most visited places, the map of visitor trajectories and the statistic of visits for individual exhibits. This monitoring method can contribute towards improved evaluation of visitor experience and more effective selection and positioning of the exhibits.
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Deep Neural Networks for Person Identification
Duban, Michal ; Herout, Adam (referee) ; Hradiš, Michal (advisor)
This master's thesis deals with design and implementation of convolutional neural networks used in person re-identification. Implemented convolutional neural networks were tested on two datasets CUHK01 a CUHK03. Results, comparable with state of the art methods were acheved on these datasets. Designed networks were implemented in Caffe framework.
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Monitoring the Movement of Visitors in Museum Exhibitions
Viskupič, Matej ; Dyk, Tomáš (referee) ; Drahanský, Martin (advisor)
The aim of this work is to propose a new system of monitoring visitors in museums. Incontrast to existing methods, the problem is solved here only using camera technology. This requires addressing three sub-problems: (1.) detection of visitors in camera streams using a convolutional neural network; (2.) camera configuration to exactly determine the position of the detected persons within the monitoring area; and (3.) identification and tracking the detected persons. The outcome of the proposed solution is the heatmap of most visited places, the map of visitor trajectories and the statistic of visits for individual exhibits. This monitoring method can contribute towards improved evaluation of visitor experience and more effective selection and positioning of the exhibits.
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Biometric Sensor for Hand Vein Recognition
Švestka, Jan ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
This work describes the area of the biometric sensor for identifying using hand veins. It proposes the construction of a sensor made up of a camera, an infrared LED, an ultrasonic distance meter and an Arduino development device. The sensor cover and removable arm support are modeled and constructed using 3D printing. A software with user-interface is created for a sensor. The work describes the experiments carried out to find the ideal lighting and camera parameters settings. It is possible to take a photo of a hand veins and identify a person stored in a database based on the captured image.
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Biometric Gateway Using Camera to Identify People
Jelen, Vilém ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
Biometric gateways are used to quickly and accurately identify people. Of the biometric characteristics, iris, face and fingerprints are commonly used. By combining them, better identification results can be achieved. The aim of this thesis is to create such a biometric gateway together with the control application. A combination of iris of both eyes and face is used, which is captured by cameras from three angles to increase accuracy. Neural networks are used to detect and extract face features. Iris recognition is realized using Daugman's algorithm.
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