Nick Rushby (auth.), Jhing-Fa Wang, Rynson Lau (eds.)'s Advances in Web-Based Learning – ICWL 2013: 12th PDF

By Nick Rushby (auth.), Jhing-Fa Wang, Rynson Lau (eds.)

ISBN-10: 3642411746

ISBN-13: 9783642411748

ISBN-10: 3642411754

ISBN-13: 9783642411755

This e-book constitutes the refereed lawsuits of the twelfth overseas convention on Web-Based studying, ICWL 2013, held in Kenting, Taiwan, in October 2013.
The 34 revised complete papers provided have been rigorously reviewed and chosen from approximately 117 submissions. The papers are prepared in topical sections on interactive studying environments, layout, version and framework of e-learning structures, customized and adaptive studying, net 2.0 and social studying environments, clever instruments for visible studying, semantic internet and ontologies for e-learning, and Web-based studying for languages learning.

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Extra info for Advances in Web-Based Learning – ICWL 2013: 12th International Conference, Kenting, Taiwan, October 6-9, 2013. Proceedings

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Upper Saddle River (1989) 7. : Image analysis and computer vision: 1999. Computer Vision and Image Understanding 78, 222–302 (2000) 8. : Computer Imaging: digital image analysis and processing. CRC Press (2005) 9. : Histogram modification techniques*. Computer Graphics and Image Processing 4, 209–224 (1975) 10. : Background modeling and subtraction by codebook construction, pp. 3061–3064 (2004) 11. : Background Subtraction Enhancement using Segmentation. In: Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, SNPD 2008, pp.

Cascade classifier established in OpenCV (Open Computer Vision Library) [2] is directly utilized for marking the areas of human face. The marked human face is regarded as the hidden Background Subtraction for excluding the upper and lower areas of the face. It tends to focus the morphology process on hand areas in the next phase after skin color detection. 7(a)) displays the upper and lower areas excluding the face, after face detection. Edge Detection. Edge detection is a fundamental problem in image processing and computer vision, aiming to mark the spots with brightness change in the image.

This study tends to introduce gesture identification into the human-computer interaction design, expecting to instantaneously catch the users gestures through the visual identification of a computer and transforming them into effective information for interacting with a digital evaluation system. Such a new-styled interactive method would break through the restrictions of traditional interaction that the users could enter the designated evaluation system, without touching any interactive devices, for online tests.

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Advances in Web-Based Learning – ICWL 2013: 12th International Conference, Kenting, Taiwan, October 6-9, 2013. Proceedings by Nick Rushby (auth.), Jhing-Fa Wang, Rynson Lau (eds.)


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