By Shafiq ur Réhman, Li Liu (auth.), Xiaoyi Jiang, Matthew Y. Ma, Chang Wen Chen (eds.)
Whereas the cellular machine has develop into ubiquitous in people's everyday life not just as a cell phone but additionally as a media participant, a cellular laptop, and a private assistant, it truly is fairly very important to deal with demanding situations well timed in utilising complex trend acceptance, sign, details and multimedia processing options, and new rising networking applied sciences to such cellular platforms. The 15 articles during this state of the art survey foster interdisciplinary discussions and learn in cellular multimedia processing strategies, functions and platforms, and produce stimulus to researchers on pushing the frontier of rising new applied sciences and functions. This publication constitutes the completely refereed post-workshop complaints of the 1st overseas Workshop on cellular Multimedia Processing, WMMP 2008, held in Tampa, FL, united states, in December 2008, together with ICPR 2008, the nineteenth foreign convention on trend acceptance. The papers went via rounds of reviewing and development and are geared up in topical sections on accessibility and studying, server assisted model and networking functions, leisure, face and speech processing, and improvement environment.
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Extra resources for Mobile Multimedia Processing: Fundamentals, Methods, and Applications
Example text
12. Integral image interested. A pre-classification which filters these areas is therefore important and can speed the detection by ten times or more. In our research we found that a box filter computed using an integral image is very efficient and can be applied to mobile devices. In an integral image, at each pixel the value is the sum of all pixels above and to the left of the current position. The sum of the pixels within any rectangle can be computed in four table lookup operations on the integral image in constant time as shown in Figure 12.
Additionally, students can use the m-Test tool to take tests and evaluate their learning performance. Learning records of students are then stored in the m-Portfolio after students complete their learning tasks. Upon completion, learning portfolios of students are uploaded into the EDB of the HELLO server for instructors to review. QR Code and Augmented Reality-Supported Mobile English Learning System 45 Fig. 4. A scenario of learning activity: a student is talking with the virtual learning partner to practice conversation in a restaurant Fig.
The AR tool has the following operation procedures: tracking a marker via a camera and then taking a series of snapshots regarding this marker in real time; decoding the internal code of the marker (which refers to a virtual image); and overlaying the virtual image on a live video. To create AR applications, ARToolKit is one of the most widely used tracking libraries with more than 160,000 downloads. Developed by Kato in 1999 and subsequently released by the Human Interface Technology (HIT) Lab of University of QR Code and Augmented Reality-Supported Mobile English Learning System 41 Table 2.
