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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.
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Robust Detection of Moving Objects in Video
Klicnar, Lukáš ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
Motion segmentation is an important process for separating moving objects from the background. Common methods usually assume fixed camera, other approaches exist as well, but they are usually very computational intensive. This work presents an approach for scene segmentation to regions with coherent motion, which works faster than similar methods and it is capable of online processing with no prior knowledge of objects or camera. The main assumption is that the points belonging to a single objects are moving together and this applies as well in the opposite direction. The proposed method is based on tracking of feature points and searching for groups with similar motion by using RANSAC-based algorithm. Short-range repair of broken tracks is applied to increase the overall robustness of tracking. Found clusters are subsequently processed to represent separate moving objects.
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Moving Objects Detection in Video Sequences
Hochman, Zdeněk ; Juránek, Roman (referee) ; Španěl, Michal (advisor)
This thesis deals with moving objects detection in video sequences. The principal aim of such detection is to detect and locate motion in the image, separate individual objects, and track these objects. Subsequently, to eliminate shadows, the paper introduces method of motion detection based on Local Binary Patterns together with differential method above the HSV color space. The proposed method provides rapid and accurate movement detection in video sequences.
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Detection of moving objects in video
Hanek, Petr ; Přinosil, Jiří (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis focuses on OpenCV library and it’s methods. Created application is able to detect moving objects from static camera video thanks to background subtraction methods. This application can be used different modes: detection in area which is calculated by BFS algorithm and two slightly different modes for crossing line detection. The application is multi thread because of graphical user interface demands on processor performance. This application also has implemented Kalman filter for multi target tracking and Hungarian method which solves assignment problem.
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Advanced Analysis Of Moving Objects In The Image
Medynskyi, Ivan
This work is focused on the image processing using the OpenCV library and detectingmoving objects in video using convolutional neural networks. The created application can detectmoving objects in the video and contains additional functionality. The application includes theYOLO convolutional model, which helps to detect moving objects.
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Detection of moving objects in video
Hanek, Petr ; Přinosil, Jiří (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis focuses on OpenCV library and it’s methods. Created application is able to detect moving objects from static camera video thanks to background subtraction methods. This application can be used different modes: detection in area which is calculated by BFS algorithm and two slightly different modes for crossing line detection. The application is multi thread because of graphical user interface demands on processor performance. This application also has implemented Kalman filter for multi target tracking and Hungarian method which solves assignment problem.
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Moving Objects Detection in Video Sequences
Hochman, Zdeněk ; Juránek, Roman (referee) ; Španěl, Michal (advisor)
This thesis deals with moving objects detection in video sequences. The principal aim of such detection is to detect and locate motion in the image, separate individual objects, and track these objects. Subsequently, to eliminate shadows, the paper introduces method of motion detection based on Local Binary Patterns together with differential method above the HSV color space. The proposed method provides rapid and accurate movement detection in video sequences.
|
|
|
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.
|
|
|
Robust Detection of Moving Objects in Video
Klicnar, Lukáš ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
Motion segmentation is an important process for separating moving objects from the background. Common methods usually assume fixed camera, other approaches exist as well, but they are usually very computational intensive. This work presents an approach for scene segmentation to regions with coherent motion, which works faster than similar methods and it is capable of online processing with no prior knowledge of objects or camera. The main assumption is that the points belonging to a single objects are moving together and this applies as well in the opposite direction. The proposed method is based on tracking of feature points and searching for groups with similar motion by using RANSAC-based algorithm. Short-range repair of broken tracks is applied to increase the overall robustness of tracking. Found clusters are subsequently processed to represent separate moving objects.
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