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People Detection Using Radar
Bartko, Jakub ; Zemčík, Pavel (referee) ; Maršík, Lukáš (advisor)
Cieľom tejto práce je výzkum použiteľnosti techník hlbokého učenia na mračnách bodov generovaných radarmi, ktoré operujú v pásme milimetrových vĺn; na účely porozumenia 3D scénam a rozpoznávania osôb. Radar je systém, ktorý využíva rádiové vlny na získavanie informácií o vzdiaľenosti a smere k objektu a o jeho rýchlosti. Na základe týchto dát je možné určiť pozíciu každého detekovaného bodu v priestore. Množina takýchto bodov sa nazýva mračno bodov. Hlboké neurónové siete navrhnuté na prácu s riedkymi mračnami bodov v 3D môžu byť natrénované na segmentáciu radarových mračien, detekciu a klasifikáciu objektov a sledovanie ich pohybu v priestore. Systémy, ktoré sú na nich postavené, môžu predstavovať veľký pokrok v oblasti interpretácie 3D scén autonómnymi strojmi. V rámci tejto práce bol model budujúci na súčasnom stave techniky natrénovaný na detekciu a klasifikáciu objektov a osôb, na základe radarových mračien bodov v 3D. Na ukážku robustnosti natrénovaného modelu a priamočiarosti jeho zapojenia na riešenie významných úloh z reálneho sveta, bola implementovaná aplikácia na počítanie a klasifiká ciu ľudí. Presnosť využitých metód aj výsledného systému bola dôkladne vyhodnotená na súbore dát vytvorenom v rámci tejto práce z radarových mračien bodov, ktorý pozostáva z viac, než 19 500 anotovaných objektov.
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Mapping the Motion of People by a Stationary Camera
Bartl, Vojtěch ; Zemčík, Pavel (referee) ; Herout, Adam (advisor)
The aim of this diploma thesis is to obtain information on the motion of people in a scene from the record of the stationary camera. The procedure to detect exceptional events in the scene was designed. Exceptional events can be fast-moving persons, or persons moving in di erent places than everyone else in the scene. To trace the motion of persons, two algorithms were applied and tested - Optical flow and CAMSHIFT. The analysis of the resulting motions is performed by monitoring the progress of motion, and its comparison with the other motions in the scene. The analysis result is represented by detected exceptional motions that can be found in the video. The areas where the motion occurs in the scene, and where the motion is the most common are also described together with the motion direction analysis. The exceptional motion parts extracted from the video represent the main result of the work.
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Moving Persons Detection and Tracking
Johanová, Daniela ; Zahrádka, Jiří (referee) ; Španěl, Michal (advisor)
This bachelor's thesis deals with the person detection using RGB-D Microsoft Kinect sensor. Human body detector is based on the method Combohod which uses both color and depth information from Kinect sensor. The aim of the thesis was to create a person detector whose functionality is demonstrated by proposing a statistical application that collects statistical information about the people who passed the shop window. At the end of the thesis the experiments with the detector under varios different conditions are described.
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Pedestrians Tracking in a Video Record from a Stationary Camera
Trnkal, Milan ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
This bachelor thesis focuses on pedestrians tracking from camera. In this work, I have introduced several methods of computer vision suitable for detection and classification of people. I proposed an algorithm for detecting and tracking pedestrians based on detection of movement. The application uses a Histogram of Oriented Gradients and SVM classifier together with color histograms for identification of pedestrians. Pedestrian's trajectories are then rendered to the output. Last part of the thesis deals with testing and evaluation of the results of the algorithm.
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Microwave radar sensor data processing focused on detecting the trajectory of people
Uher, Adam ; Slováček, Miroslav (referee) ; Valach, Soběslav (advisor)
This bachelor ‘s thesis deals with a topic of people detection and tracking their movement in regions of interest. The individual methods that can achieve people detection are analyzed. To implement people detection and tracking their movement microwave radar sensor IWR6843AoPEVM from Texas Instruments is chosen for this task. This hardware and its software are described in detail. Then simulation is conducted to track people in a queue and its results are evaluated. Different advantages and disadvantages of individual methods are compared with each other. Finally, there’s a summary of possible implementations for this device and target platform is chosen to verify its functionality.
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Sensor fusion for detecting and locating people in a room
Vondráček, Jakub ; Dobossy, Barnabás (referee) ; Najman, Jan (advisor)
This diploma thesis deals with the problem of fusion of several sensors for the purpose of detecting and locating people in a room. It is primarily about using measured sensors and implementing them in such a way that their connection creates a system that has obvious advantages compared to more expensive single sensor solutions. In the first part of the work, research is carried out, which presents the basic issues of detection, localization and counting of people in rooms. To be used in the practical part of the work, it is also indicated here which specific sensors can be used to achieve these functions and which control units are suitable for such a system. Finally, it summarizes specific components and software tools, which are further supplemented in the practical part of the work. The rationale for this selection is also included. The second part of the thesis describes the specific design of the resulting system, which can perform the functions of detection, localization and counting of people in the room. This practical proposal is described including all starting points, connections and especially the algorithm that was used for sensor fusion. The entire system is subsequently tested, based on which its functioning is evaluated. In the last section of the thesis, the created system is supplemented with a model of a cover and wall mount.
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People Detection Using Radar
Bartko, Jakub ; Zemčík, Pavel (referee) ; Maršík, Lukáš (advisor)
Cieľom tejto práce je výzkum použiteľnosti techník hlbokého učenia na mračnách bodov generovaných radarmi, ktoré operujú v pásme milimetrových vĺn; na účely porozumenia 3D scénam a rozpoznávania osôb. Radar je systém, ktorý využíva rádiové vlny na získavanie informácií o vzdiaľenosti a smere k objektu a o jeho rýchlosti. Na základe týchto dát je možné určiť pozíciu každého detekovaného bodu v priestore. Množina takýchto bodov sa nazýva mračno bodov. Hlboké neurónové siete navrhnuté na prácu s riedkymi mračnami bodov v 3D môžu byť natrénované na segmentáciu radarových mračien, detekciu a klasifikáciu objektov a sledovanie ich pohybu v priestore. Systémy, ktoré sú na nich postavené, môžu predstavovať veľký pokrok v oblasti interpretácie 3D scén autonómnymi strojmi. V rámci tejto práce bol model budujúci na súčasnom stave techniky natrénovaný na detekciu a klasifikáciu objektov a osôb, na základe radarových mračien bodov v 3D. Na ukážku robustnosti natrénovaného modelu a priamočiarosti jeho zapojenia na riešenie významných úloh z reálneho sveta, bola implementovaná aplikácia na počítanie a klasifiká ciu ľudí. Presnosť využitých metód aj výsledného systému bola dôkladne vyhodnotená na súbore dát vytvorenom v rámci tejto práce z radarových mračien bodov, ktorý pozostáva z viac, než 19 500 anotovaných objektov.
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Microwave radar sensor data processing focused on detecting the trajectory of people
Uher, Adam ; Slováček, Miroslav (referee) ; Valach, Soběslav (advisor)
This bachelor ‘s thesis deals with a topic of people detection and tracking their movement in regions of interest. The individual methods that can achieve people detection are analyzed. To implement people detection and tracking their movement microwave radar sensor IWR6843AoPEVM from Texas Instruments is chosen for this task. This hardware and its software are described in detail. Then simulation is conducted to track people in a queue and its results are evaluated. Different advantages and disadvantages of individual methods are compared with each other. Finally, there’s a summary of possible implementations for this device and target platform is chosen to verify its functionality.
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Pedestrians Tracking in a Video Record from a Stationary Camera
Trnkal, Milan ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
This bachelor thesis focuses on pedestrians tracking from camera. In this work, I have introduced several methods of computer vision suitable for detection and classification of people. I proposed an algorithm for detecting and tracking pedestrians based on detection of movement. The application uses a Histogram of Oriented Gradients and SVM classifier together with color histograms for identification of pedestrians. Pedestrian's trajectories are then rendered to the output. Last part of the thesis deals with testing and evaluation of the results of the algorithm.
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Moving Persons Detection and Tracking
Johanová, Daniela ; Zahrádka, Jiří (referee) ; Španěl, Michal (advisor)
This bachelor's thesis deals with the person detection using RGB-D Microsoft Kinect sensor. Human body detector is based on the method Combohod which uses both color and depth information from Kinect sensor. The aim of the thesis was to create a person detector whose functionality is demonstrated by proposing a statistical application that collects statistical information about the people who passed the shop window. At the end of the thesis the experiments with the detector under varios different conditions are described.
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