By A. Ranjith Ram, Subhasis Chaudhuri
This e-book provides a number of video processing methodologies which are worthy for distance schooling. the inducement is to plan new multimedia applied sciences which are compatible for higher illustration of educational video clips through exploiting the temporal redundancies found in the unique video. This solves a number of the concerns on the topic of the reminiscence and bandwidth hassle of lecture video clips. some of the equipment defined within the booklet specialize in a key-frame dependent process that's used to time cut back, repackage and retarget tutorial video clips. the entire tools want a preprocessing step of shot detection and popularity, that is individually given as a bankruptcy. we discover these frames that are well-written and specific as key-frames. A super-resolution established snapshot enhancement scheme is advised for refining the key-frames for greater legibility. those key-frames, besides the audio and a meta-data for the mutual linkage between a number of media elements shape a repackaged lecture video, which on a programmed playback, render an estimate of the unique video yet at a considerably compressed shape. The ebook additionally provides a legibility retentive retargeting of this educational media on cellular units with restricted show measurement. some of these applied sciences give a contribution to the enhancement of the outreach of distance teaching programs. Distance schooling is now an immense company with an annual turnover of over 10-12 billion money. we predict this to extend quickly. Use of the proposed expertise can assist convey academic movies to those that are much less endowed by way of community bandwidth availability and to these in all places who're even on a circulation by means of providing it successfully to cellular handsets (including PDAs). hence, expertise builders, practitioners, and content material services will locate the fabric very useful.
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Extra resources for Video Analysis and Repackaging for Distance Education
The computational complexity is signiﬁcantly lower than a number of previously reported approaches. The issue of adapting video streams to different types of terminals with different capabilities such as screen size, amount of available memory, processing power and the type of network access is discussed in . 4 Content re-creation 33 activities. Two different models for transcoding have been examined: rate reduction and resolution reduction. A video transcoding method is proposed in  which combines the use of different transcoding tools to transcode compressed video bit streams to various target bit rates while maintaining a good subjective/objective video quality.
A method for structuring lecture videos is presented in  which supports both topic indexing and semantic querying of multimedia documents for distance learning applications. Here the authors aim at linking the discussion topics extracted from the electronic slides with the associated video and audio segments. Two major techniques in this approach include video text analysis and speech recognition. A video is ﬁrst partitioned into shots based on slide transitions, then for each shot, the embedded video texts are detected, reconstructed and segmented as high-resolution foreground texts for commercial optical character recognition (OCR).
They provide an overview of advanced technologies that facilitate experiencebased learning at a distance, reduce the cost of distance education, increase access to education and integrate formal education into the fabric of everyday life. Having discussed some of the relevant literature on a general purpose e-learning system, we now focus on various video analysis techniques relevant to the elearning. 1 Video shot detection and recognition 23 an e-learning environment. 1 reviews the methods for video shot detection and recognition.