DocumentCode :
2085755
Title :
Toys++ AR Embodied Agents as Tools to Learn by Building
Author :
Simeone, Luca ; Iaconesi, Salvatore
Author_Institution :
FakePress, Univ. La Sapienza, Rome, Italy
fYear :
2010
fDate :
5-7 July 2010
Firstpage :
649
Lastpage :
650
Abstract :
This paper presents a prototype for an augmented-reality based toy. Toys++ is grounded on the concept that the actual activity of building tangible artifacts can speed up learning processes. Toys ++ aims at assembling a framework that will allow the use of existing physical components of the toy as triggers. When the toy is placed under the webcam, a pre-trained 3D feature recognition system scans the entire figure, trying to identify some specific components. If any of these elements are recognized, the system will retrieve and show educational content from selected sources (texts, videos, pictures).
Keywords :
augmented reality; computer aided instruction; feature extraction; software agents; AR embodied agent; Toys++; educational content retrieval; figure scanning; learning tool; pretrained 3D feature recognition system; Artificial intelligence; Conferences; augmented reality; component; constructionism; enhanced learning; mathetics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Learning Technologies (ICALT), 2010 IEEE 10th International Conference on
Conference_Location :
Sousse
Print_ISBN :
978-1-4244-7144-7
Type :
conf
DOI :
10.1109/ICALT.2010.184
Filename :
5572598
Link To Document :
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