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Person Detection in Video
Marek, Lukáš ; Goldmann, Tomáš (referee) ; Dyk, Tomáš (advisor)
This bachelor thesis deals with the implementation of an application for detecting people in video footage. Both the application and the detection are implemented in Python. TKinter library is used to create the application. The OpenCV library and the YOLOv4 detection algorithm, which runs on a CUDA backend but can also run on the CPU, are used for detection.
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Pedestrian Detection and Recognition in a Multi-Camera System
Macák, Filip ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
The main purpose of this bachelor's thesis is to create an application for person detection and recognition from scenes captured in a multi-camera system. The output of the application is a video on which the detected persons are highlighted and each person is assigned an identification number through which it can be recognized across the input scenes. Several solutions to the problem of person detection and recognition were examined and the text of this work serves as an overview of these problems. The application is built on PyTorch and Torchreid libraries. A detector with a Faster-RCNN network is used for detection and recognition is based on the OSNet network. The application also includes a simple user interface to facilitate work with the application. The application serves as a demonstration of the state-of-the-art for person detection and recognition.
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Radar Signal Processing and Fusion of Information
Reich, Bořek ; Maršík, Lukáš (referee) ; Zemčík, Pavel (advisor)
This bachelor's thesis focuses on fusion of millimetr-wave radar and camera. It proposes appropriate procedure and usage of these sensors for object detection. Object detection in this bachelor's thesis is focused on people and provides additional information about detected person. It proposes convolution neural network as means of person detection and fusion of mmWave radar and camera data. When person is detected, distance of person from sensors is found in mmWave radar point cloud. Testing is performed on input data from both sensors in different situations, in poorly lit, unkwonwn scenes, with unknown people etc. Distance measuring is validated with reference data.
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Room Presence Detection in the Smart Home
Průdek, David ; Letavay, Viliam (referee) ; Pluskal, Jan (advisor)
The purpose of this thesis is to design and implement presence detection sensor which works with home automation. I focused on sensor implementation which needs for activity only available wearable electronics. Sensor placed in room can detect other devices and based on signal intensity it determines his location. For this case I chose Bletooth LE which is used to be implemented in the most of wearable electronics and recently new utilization of BLE was found for indoor navigation. Using this sensor for automation is ensured by system Home Assistant. Main benefit of this project is simply and cheap extend home automation capabilities for person detection in rooms, not only detection in large areas which offers GPS and Wi-Fi systems.
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Detekce osob v obraze pomocí Raspberry Pi
Svoboda, Lukáš ; Appel, Martin (referee) ; Matějásko, Michal (advisor)
This thesis describes the detection of people in the image using camera devices with focus on using a Raspberry Pi minicomputer. There were created algorithms processing image data and containing algorithms, which are able to distiguish whether it is incoming or outcoming person. Another role of these softwares is to send data to the ThingSpeak platform, where charts are made from the data. The detectors of people are based on Optical flow and ACF - Aggregate Channel features methods. All software was created in the development environment MATLAB/Simulink.
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Counting of People Passing Through a Door Using a Stationary Camera
Tichý, Ľuboš ; Behúň, Kamil (referee) ; Sochor, Jakub (advisor)
This bachelor thesis deals with counting of people passing through a door. It may be used in case, when we need to know, how many people there are in monitored room. The first part is a description of existing methods of counting people and the second part deals with used computer vision methods. Proposed system can count people, including distinguishing their motion direction. The last part contains an evaluation of the system.
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Multi-Person Tracking in Video from Mono-Camera
Vojvoda, Jakub ; Španěl, Michal (referee) ; Beran, Vítězslav (advisor)
Multiple person detection and tracking is challenging problem with high application potential. The difficulty of the problem is caused mainly by complexity of scene and large variations in articulation and appearance of person. The aim of this work is to design and implement system capable of detecting and tracking people in video from static mono-camera. For this purpose, an online method for tracking has been proposed based on tracking-by-detection approach. The method combines detection, tracking and fusion of responses to achieve accurate results. The implementation was evaluated on available dataset and the results show that it is suitable to use for this task. A method for motion segmentation was proposed and implemented to improve the tracking results. Furthermore, implementation of detector based on histogram of oriented gradients was accelerated by taking advantage of graphics processing unit (GPU).
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