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Augmented Reality for Desk Games
Bačovčin, Juraj ; Kapinus, Michal (referee) ; Beran, Vítězslav (advisor)
This bachelor thesis deals with the realization of a chosen board game for an interactive table. The goal is to design, implement and test a new user-friendly user interface of the game application without losing any key aspects defining board gaming. The resulting program is executable on the ARTable3 workspace capable of projecting any image onto the touch table and capturing real-time events from its surface. It has undergone proper functional and usability testing, making it possible to consider it fully functional and ready for any expansions proposed in the final sections of this document.
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User Hand Detection in Depth Data
Malík, Pavol ; Šimon, Martin (referee) ; Beran, Vítězslav (advisor)
The aim of this thesis is to detect hand of user above the interactive table and show its position with respect to the table. Used sensor was Kinect so the depth data approach was selected. The detection is realized using registration method SAC-IA, which works on the template matching principle. Thesis deals with existing solutions of hand detection as well as procedure used in this work. Dataset was defined, containing hand templates and testing scenes, from which the classifier was evaluated. Final testing was performed on more than a hundred objects and the success rate reached 82 %.
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Augmented Reality for Desk Games
Bačovčin, Juraj ; Kapinus, Michal (referee) ; Beran, Vítězslav (advisor)
This bachelor thesis deals with the realization of a chosen board game for an interactive table. The goal is to design, implement and test a new user-friendly user interface of the game application without losing any key aspects defining board gaming. The resulting program is executable on the ARTable3 workspace capable of projecting any image onto the touch table and capturing real-time events from its surface. It has undergone proper functional and usability testing, making it possible to consider it fully functional and ready for any expansions proposed in the final sections of this document.
|
|
|
User Hand Detection in Depth Data
Malík, Pavol ; Šimon, Martin (referee) ; Beran, Vítězslav (advisor)
The aim of this thesis is to detect hand of user above the interactive table and show its position with respect to the table. Used sensor was Kinect so the depth data approach was selected. The detection is realized using registration method SAC-IA, which works on the template matching principle. Thesis deals with existing solutions of hand detection as well as procedure used in this work. Dataset was defined, containing hand templates and testing scenes, from which the classifier was evaluated. Final testing was performed on more than a hundred objects and the success rate reached 82 %.
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