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Moving Object Detection in Video
Buchtela, Radim ; Ševcovic, Jiří (referee) ; Herout, Adam (advisor)
This thesis is devoted to detection of moving object in video sequence. In this thesis are described in detail detection methods based on principle of Background subtraction. There are indtroduced strategies of background modeling and background model updating. This thesis deal also with problems of tracking objects in video, there is introduced one of possible approaches. Part of this thesis is application for function demonstration of detection methods and tracking method. On results are showed main advantages and disadvantages of implemented methods.
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Moving Object Detection in Video Using CUDA
Horák, František ; Nečas, Ondřej (referee) ; Herout, Adam (advisor)
This thesis deals with methods of moving object detection in video; by selecting and applying proper algorithms and implementing them with CUDA. Technology CUDA is described and wieved it's architecture and other parts. General principles of moving object detection are observed and modification are discussed. Final system is implemented and tested.
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Recognizing and Classification of Traffic Situations
Zbořil, Jiří ; Musil, Petr (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to identify and classify dangerous situations from surveillance cameras, monitoring traffic. An example of such situations is dangerous standing near by the road and car crash, on which this work focuses. The created system uses object detector, analyzing average images in given interval, K nearest neighbor and K Means algorithm and re-detection of enlarged local area in a frame to select anomaly candidates. Detected objects, that do not belong on the road are eliminated by attaching created road mask. At the very last phase, the interval, together with the classification is determined. Calculated F1 score is 0.645, S4 score 0.535 and precision of classification 80 %.
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Recognizing and Classification of Traffic Situations
Zbořil, Jiří ; Musil, Petr (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to identify and classify dangerous situations from surveillance cameras, monitoring traffic. An example of such situations is dangerous standing near by the road and car crash, on which this work focuses. The created system uses object detector, analyzing average images in given interval, K nearest neighbor and K Means algorithm and re-detection of enlarged local area in a frame to select anomaly candidates. Detected objects, that do not belong on the road are eliminated by attaching created road mask. At the very last phase, the interval, together with the classification is determined. Calculated F1 score is 0.645, S4 score 0.535 and precision of classification 80 %.
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Moving Object Detection in Video
Buchtela, Radim ; Ševcovic, Jiří (referee) ; Herout, Adam (advisor)
This thesis is devoted to detection of moving object in video sequence. In this thesis are described in detail detection methods based on principle of Background subtraction. There are indtroduced strategies of background modeling and background model updating. This thesis deal also with problems of tracking objects in video, there is introduced one of possible approaches. Part of this thesis is application for function demonstration of detection methods and tracking method. On results are showed main advantages and disadvantages of implemented methods.
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|
|
Moving Object Detection in Video Using CUDA
Horák, František ; Nečas, Ondřej (referee) ; Herout, Adam (advisor)
This thesis deals with methods of moving object detection in video; by selecting and applying proper algorithms and implementing them with CUDA. Technology CUDA is described and wieved it's architecture and other parts. General principles of moving object detection are observed and modification are discussed. Final system is implemented and tested.
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