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Handbook of Multimedia Information Retrieval, by Horst Eidenberger
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Multimedia information retrieval: That is the desire to make computers see, hear and understand like humans do. Is it possible to give perception to machines, to make them understand facial expressions, hummed melodies, stock charts and ECG curves? If yes, the computer would become an even more valuable companion in business and private life. Think of the possibilities in, for example, healthcare, home security, online customer support or market analysis. This book explains what is possible in multimedia information retrieval today and what is not. We introduce the basic concepts, explain why the first step is always summarization and the second classification, which is essentially applying human understanding of some context on the summary. We group and discuss the various methods that have been proposed for the summarization of audio, visual and other media information. In classification, we build on today's psychological understanding of human cognition. Successfully, we transfer concepts of human similarity perception on machine classification. We cluster machine learning methods by their approach, model and process. On top of that, we link back from the state of the art methods of multimedia information retrieval to human cognition: We propose artificial neural structures for the building blocks of media summarization and classification. The result is a balanced introduction into the field that starts from graduate IT knowledge and ends at the current frontiers of multimedia research.
- Sales Rank: #3035086 in Books
- Brand: Brand: Atpress
- Published on: 2012-09-07
- Original language: English
- Number of items: 1
- Dimensions: 8.27" h x 1.33" w x 5.83" l, 1.71 pounds
- Binding: Paperback
- 660 pages
- Used Book in Good Condition
Most helpful customer reviews
0 of 0 people found the following review helpful.
Comprehensive!
By K. Kaiser
This is a great work, I found it very informative. Over the last two years, I've tried several books that are variations on this theme - introductions to information retrieval and/or computer vision - but with this one, I feel like I am actually learning how to do it right. The first two chapters lay out the signal processing preliminaries, and get the book off to a fast start. Then, methods for media description and classification are explained in-depth. The level of complexity is raised from the first to the third part. That allowed me, as a half-way expert, to jump right to the point where the story becomes interesting for me. Throughout the book the emphasis is on practical algorithms and efficient application. The author's views are highly original and very similar to my own. I believe, this is a good read if you are a computer science student.
0 of 0 people found the following review helpful.
An excellent textbook for computer science students
By B. Hofreiter
This is a great book. Using a minimum of mathematics and a maximum of analogy and explanation expressed in a direct and readable style, the author brings multimedia retrieval theory as close to the everyday mind as might be possible. Throughout the book, the presentation is very dense but clear. Starting from basic concepts of signal processing and machine learning, the author develops a consistent theory of multimedia analysis as I have not seen it done before. Last but not least, I found some of the passages quite funny and entertaining.
0 of 0 people found the following review helpful.
The new reference
By Jacob von Brauchitsch
This book is the best presentation of this potentially confusing subject I have ever read. Within the range that this intends to cover, it is an outstanding reference. It carves out the common aspects of such diverse fields as signal processing, psychophysics, media theory, semiotics, psychological similarity and machine learning. It helps bridge the gap between audio signal processing and visual signal processing. I highly recommend this book for anyone who wants to learn the art of media analysis.
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