Abstract
The exponential growth of video data produced by surveillance cameras, cell phones and movie post-production creates the need to process big-data using methods that are able to produce instantaneous result. Video summarization can be accomplished and represented in several manners. The achieved summaries might be a sequence of images or short videos. In our method, an input video is divided into segments. From each segment we calculate key frames using three different key frame definitions, to summarize the video data. The contribution of this paper is to describe how to incorporate techniques that extract on the fly results.
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Mpountouropoulos, N., Tefas, A., Nikolaidis, N., Pitas, I. (2014). Visual Information Analysis for Big-Data Using Multi-core Technologies. In: Pan, JS., Snasel, V., Corchado, E., Abraham, A., Wang, SL. (eds) Intelligent Data analysis and its Applications, Volume I. Advances in Intelligent Systems and Computing, vol 297. Springer, Cham. https://doi.org/10.1007/978-3-319-07776-5_32
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DOI: https://doi.org/10.1007/978-3-319-07776-5_32
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07775-8
Online ISBN: 978-3-319-07776-5
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