National Repository of Grey Literature 32 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Using the Kinect sensor in detection of people
Janás, Lukáš ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
Bachelor thesis deals with the methods of people detection by using Microsoft Kinect. Depth image captured by this device is further processed by using standard algorithms from freely available OpenCV library. All of image processing methods are described in detail of their function and influence to image. The practical part of the work is focused on the realization of a simple program, which is serving for image segmentation and finding people.
Mapping the Motion of People by a Stationary Camera
Valchář, Vít ; Španěl, Michal (referee) ; Herout, Adam (advisor)
This thesis deals with detection and mapping the motion of people from a video record. It explains methods for image detection and their usage in real application. The output of this thesis are two applications, one for pedestrian detection and the second for displaying detected data.
Detection of security aids in image signal
Burdík, Vojtěch ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This work is devoted to the relatively new field of computer – computer vision. It focuses on the recognition of people, positioning and colour detection of clothing placed on person. The aim is to build an algorithm that would be able to locate the person in the picture and would make colours tests of clothing and helmets. For image processing were used OpenCV library functions and from algorithms was compiled program solving this problem. The output of the program is the answer, what colour is person at stated locations wearing, and if clothing and helmet are the same colour, the person is evaluated as properly dressed. The resulting program is then disassembled and parts of the code are in detail described in this work. There is explained how to use correctly each OpenCV function used in program.
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.
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.
Moving Objects Detection in Video Sequences
Havelka, Jan ; Ševcovic, Jiří (referee) ; Španěl, Michal (advisor)
The topic of this thesis is the recognition and detection of moving object and persons in video sequence and in the static image. Designed application uses the combination of background model for movement detection, histograms of oriented gradients method for person recognition and Lucas-Kanade method for object tracking.
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.
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.
Mapping of the Pedestrian Movement Trajectory in a Video Recording Captured by a Drone
Šťastný, Filip ; Tinka, Jan (referee) ; Orság, Filip (advisor)
This master's thesis deals with pedestrian detection using neural networks in a video record captured by drone. Pedestrians are tracked, and their GPS coordinates are calculated using digital elevation models and mapped based on their identity and an information provided by the drone.
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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