Ebook Fundamental Media Understanding, by Horst Eidenberger
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Fundamental Media Understanding, by Horst Eidenberger
Ebook Fundamental Media Understanding, by Horst Eidenberger
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Media understanding is the science/art of identifying semantic structures in digital media objects such as audio, biosignals, images, text and videos. Computational media understanding should do what our senses and cognition do: immediate understanding of events as diverse as watching a bird and listening to a speech. This book introduces the reader with the state-of-the-art methods applied today for media summarization and for the categorization of events. In contrast to related publications, it does not focus on one type of media but considers all the above-named as well as a few others. The author endeavors to identify similarities between the methods employed in audio retrieval, image understanding, text summarization and many other research domains. It turns out that a number of significant parallels do exist. Structuring the methods along common criteria and discussing their similarities and differences breaks the ground for a new research discipline: true computational understanding of multimedia content.
- Sales Rank: #8982066 in Books
- Published on: 2011-09-14
- Original language: English
- Number of items: 1
- Dimensions: 8.27" h x .51" w x 5.83" l, .64 pounds
- Binding: Paperback
- 260 pages
From the Author
Please see the book website atpress.info for more information and materials.
About the Author
Horst Eidenberger is associate professor of applied computer science at the Vienna University of Habilitation in 2005. He has published several books and more than 70 scientific papers in journals and at international conferences. His research interests include content understanding, machine learning and signal processing.
Most helpful customer reviews
0 of 0 people found the following review helpful.
Great introductory book
By Dustin
This is a really nice book as it gives just enough detail to new students so that they can decide if this is something they want to pursue or not. It introduces all important terms, concepts, and ideas of the field. I think some of the presented ideas and views are really unique. The book could blaze the trail for a whole new research discipline. I like the author's figures for showing the ideas behind all the methods employed in this area. And it is a good reference to keep handy at all times.
0 of 0 people found the following review helpful.
My favorite reference for feature extraction and classification
By Klaus
This is my favorite reference for feature extraction and classification. The book gives a development of content-based media analysis, along with practical knowledge on how to apply the theory, and also gives numerous hints for practical applications. The author manages to work out the principles behind the feature extraction methods. For example, I was not aware of the central role of the convolution operator. The building blocks help to understand that most features are just variations of a few ideas. To my knowledge there is no other book that covers all of these areas: audio and image retrieval, EEG, but as well text retrieval and genome analysis. I was surprised to find that these diverse media have so much in common. The chapters are arranged keeping in mind the different key research areas which should be learned by a student. Apart from providing an overview, every chapter has abundant key references which direct the student for in-depth understanding of a particular area. If you're not already an expert in all of the areas covered here, read this book. If you are, read it too.
0 of 0 people found the following review helpful.
Good high-level overview - sparse on details
By manny
Good overview of techniques and approaches in the various domains (finance, text, video, etc.) Light on the math (by design) and at-times too high-level.
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