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National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Multi Object Class Learning and Detection in Image
 Chrápek, David ; Hradiš, Michal (referee) ; Beran, Vítězslav (advisor)
This paper is focused on object learning and recognizing in the image and in the image stream. More specifically on learning and recognizing humans or theirs parts in case they are partly occluded, with possible usage on robotic platforms. This task is based on features called Histogram of Oriented Gradients (HOG) which can work quite well with different poses the human can be in. The human is split into several parts and those parts are detected individually. Then a system of voting is introduced in which detected parts votes for the final positions of found people. For training the detector a linear SVM is used. Then the Kalman filter is used for stabilization of the detector in case of detecting from image stream.
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Supporting children's interest in the history of their region in educational programs of The Hussite Museum of Tábor
 NIMRICHTROVÁ, Kateřina
This bachelor thesis examines the role of museum education in developing positive relationship of children and youth towards history of the region, in which they live and the history in general. Selected activities of the Hussite Museum of Tábor are described while considering their respective impact on children's interest in history of their region and on cultivating their understanding of cultural heritage. The introduction defines the term "cultural heritage" and considers the educational potential of museums and galleries. The following part assesses current state of museum education in the Hussite Museum. The third part describes individual programs of the Hussite museum, focusing on those educational goals, methods and contents which support the participants of these programs in developing their interest in the history of the region.
Detailed record
Multi Object Class Learning and Detection in Image
 Chrápek, David ; Hradiš, Michal (referee) ; Beran, Vítězslav (advisor)
This paper is focused on object learning and recognizing in the image and in the image stream. More specifically on learning and recognizing humans or theirs parts in case they are partly occluded, with possible usage on robotic platforms. This task is based on features called Histogram of Oriented Gradients (HOG) which can work quite well with different poses the human can be in. The human is split into several parts and those parts are detected individually. Then a system of voting is introduced in which detected parts votes for the final positions of found people. For training the detector a linear SVM is used. Then the Kalman filter is used for stabilization of the detector in case of detecting from image stream.
Detailed record

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